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Say you want to make a jacket.

Ricky Ho reaches for that example twice in our conversation without seeming to notice he is doing it, which is how you can tell it is the shape his mind actually runs on. The jacket has to be good. It has to land in the United States for under seven dollars. And from those two constraints, an enormous number of questions unfold that a reasonable person would have no way to answer.

"Should I be going to China or should I be going to Vietnam or should I be going to Cambodia?"

And suppose you pick a country. You are still nowhere, because now you have to pick a factory, and this is the part Ricky says people badly underestimate.

"Many of these suppliers, you won't find publicly available information on them. Like these factories barely have websites online. It's very hard to even like verify if they're legit."

Which is why, for decades, the answer to this problem was an airplane. You flew to a trade show. You stood in a hall and met people, because meeting them was the only available proxy for knowing anything about them. Ricky calls this "obviously a very expensive and time-consuming process," which is the understatement of a man who has built the alternative.

The alternative starts with an unglamorous act of accumulation. SourceReady buys customs data, and it buys it the hard way.

"We basically get customs data from over 85 different countries. So we go government by government getting shipment data."

Government by government. And there is no API for that sentence. But it is 85 separate procurement relationships, and the reason it is worth doing is that shipment records are one of the few places where companies tell the truth involuntarily. A supplier controls its website. But it does not control the manifest.

And assemble enough of those manifests and you can run the question backwards. Instead of asking a factory who it is, you ask the record who ships to whom, and the answer arrives as a map.

"If I wanna make this jacket and I wanna find out who are the suppliers making this jacket for Calvin Klein, we can literally build you a list of all of the vendors that match this description."

But a list of vendors is not yet an answer, and here Ricky arrives at the problem that actually interests him, which is not discovery at all.

It is judgment.

"As a brand or retailer, if you're sourcing a product, how do you actually know which suppliers have good quality? Because quality is very subjective. There is no universal metric for quality."

And then he does the thing that separates a person who has thought about this from a person who has merely encountered it. He points out that the obvious source of information is worthless.

High quality, he says, is not something you would just take at face value, and then he breaks off mid-sentence to put it as a question instead. "Like if a supplier on their website says, 'We make high quality,' do you believe that? I mean, every supplier on their website will say high quality."

The claim is not false. But the claim is empty. When every participant in a market makes the identical assertion, the assertion stops transmitting anything, and you are back to the airplane.

So Ricky went looking for a signal the supplier cannot author. And he found the analogy in a place that has nothing to do with manufacturing.

"Similar to how Google ranks websites based on the quality of backlinks, we will rank suppliers based on the quality of the customers they work with."

And Google's original insight was that a page cannot credibly vouch for itself, but other pages can vouch for it, and the pattern of who vouches is harder to fake than the page's own copy. But Ricky's version swaps the noun. A factory cannot credibly vouch for itself. Its customers can, not by saying anything, but by continuing to place orders that appear in the manifests.

And he makes it concrete immediately.

"If I know that this factory, if seventy percent of their customers are on the higher premium segment, then more likely than not, this factory is gonna be more kind of quality driven than a factory that does ninety percent Target and Walmart."

Meet a factory that tells you its main customer is Walmart and something happens in your head whether you approve of it or not. Meet one whose main customer is Lululemon and something else happens. Ricky's argument is not that the bias is correct. It is that the bias is already operating, on a sample of one anecdote, and he would rather run it across every shipment record in 85 countries.

And the same trick shows up again on a different question, and once you have seen it twice you start seeing the method rather than the feature. Minimum order quantity is a number suppliers rarely publish, and it determines whether a small brand can work with them at all. So do not ask. But look at what they ship.

"On average, this supplier, most of their shipments are around five hundred to a thousand pieces, so most likely their minimum order quantity is around five hundred."

Infer the thing they won't tell you from the thing they can't hide. That is the whole company, applied twice.

Now, who is this actually for. Ricky's answer surprised me, because I expected procurement departments and got something closer to a cultural observation.

"So the most common entrepreneurship that exists today is basically building a brand."

And his reasoning runs like this. Platforms lowered the barrier to commerce. Anyone with an audience now faces the question of how to monetize it, and sponsorship income is not a business because you do not control it. So the creator builds something to sell. He reaches for the obvious example.

"Even, like, MrBeast, he builds Feastables, and the reason for that is once you have a product that you can actually sell yourself using your traffic, that becomes a recurring revenue."

"This whole physical supply chain is traditionally so out of reach to regular people, but it's also, ironically, the most common startup in the world."

The most common startup in the world sits behind the least accessible knowledge in the world. And most people are not going to build software, because they do not know how and could not sell it if they did. But a clothing line, a water bottle, chocolate — those are legible. People can picture themselves doing it. And the moment they try, they hit a wall made of things nobody told them existed.

Ricky's example is chocolate, and it is a good one because it sounds so harmless.

"Because it's food, you need FDA approval. So when you find a supplier, you can't just, like, find some random factory to make this. You need to find an FDA-certified factory."

Then the question that actually lands.

"For a random creator, do they know where to find FDA-certified factories, and do they even know to look for the certifications that they might need to sell?"

Not whether they can find one. But whether they know to look. That is a different and much crueler kind of ignorance, because it does not announce itself. And supplements are the same, and he is blunt about why. "You're putting stuff in people's mouths."

This is where the conversation stops being about technology, and where Ricky is at his least promotional.

"They get burned by the wrong supplier. They'll work with some random supplier in China that doesn't ship the goods and then they get scammed. There's all types of problems that you would not foresee, and then you're like 20K down the drain."

And twenty thousand dollars, from someone who had to save it. And when he describes the moment the mistake finally surfaces, he stops sounding like a founder describing a market and starts sounding like someone who has watched it happen to people he liked.

"The impact of that decision does not come until later, and they're like, 'Oh, shit, I fucked up.'"

He is right that it compounds, and he is precise about the arithmetic in both directions. Save twenty or thirty cents on a unit and order fifty thousand units and you have made thousands of dollars from a single decision, in a category where gross margins run 40 or 50 percent before marketing. Get the same decision wrong and a 40 percent tariff you never saw coming arrives with the container and a twenty-thousand-dollar bill.

Which is why the last few years have made his job harder and his product more necessary at the same time. For twenty years the answer to where to manufacture was China, and he says so without any of the geopolitical throat-clearing the topic usually attracts. "Whatever you wanna make, just go to China." Tariffs and tension broke the default, and what replaced it is not another default but a genuine optimization problem with too many variables for an amateur.

And Pakistan and India for denim. Vietnam for athleisure, because Pakistan and India do not have the infrastructure for it. Forty-five percent tariffs on some goods out of China that make the old answer economically dead. And a small brand founder who has no idea any of this is true.

"If you're not in the supply chain every day, how would you know if tariffs increased in Vietnam two months ago because of some new law that passed?"

His framing of what the software is for follows from that, and it is the most careful sentence he says all hour.

"Supply chain is an optimization problem. It's like you have all these different knobs and things that you can tune, but to a regular person, they don't know what are the impacts of tuning these different things."

Not that the machine decides. That the machine holds the variables, and you supply the objective — and he is emphatic that the objective is not always cost. Maybe you want premium and will pay for it. The tool cannot know that. You have to say it.

Ricky sold his last supply-chain company at 23, so his optimism about small teams is not free-floating. And he thinks three or four people can build a ten-million-dollar brand now, and given what he has already done I am not inclined to argue with the arithmetic.

But I am not sure the hardest part is the part he has solved.

Because everything SourceReady does is downstream of a decision it cannot make for you. It will tell you which factories serve premium brands, what a fair price looks like, which certifications the category demands, which country's infrastructure fits the product. All of that used to be a moat and now it is a query. What it will not tell you is whether the thing is worth making, and the creator with an audience and no idea what to sell is not actually blocked on sourcing intelligence. They are blocked on taste.

Ricky's bet is that the sourcing wall was the real one, and that the people stopped by it were stopped by information rather than by judgment. And he may well be right. The manifests are real, the arithmetic on twenty cents times fifty thousand units is real, and the twenty thousand dollars people lose to a factory that never ships is extremely real.

Honestly, I don't know which wall was load-bearing. I know the jacket is easier to source than it has ever been, and that nobody has yet built the thing that tells you whether to make the jacket.

Guest Bio: Ricky Ho

Ricky Ho is the Co-Founder and CEO at SourceReady, an AI-powered global sourcing platform that helps retailers, brands, and independent creators identify and vet manufacturers using customs shipment data pulled from more than 85 countries. A Forbes 30 Under 30 honoree, Ho became known for applying data-driven supplier ranking — using the quality of a factory’s existing customer base as a proxy for its own production quality — to a sourcing industry historically built on opaque, relationship-gated information. SourceReady launched in December 2024, positioning itself against pay-to-play incumbents like Alibaba by offering unbiased, data-backed supplier matching.

Previously, Ho founded Treelab, a supply-chain ERP startup backed by Sequoia Capital and Tencent. He raised $22 million for the company and sold it at age 23, giving him a rare second run at the global sourcing and supply-chain problem before turning 30.

Hey,

Thanks for reading this. I mean that. There’s a lot of content out there competing for your attention, and you spent some of it here. I hope it was worth it. Even better, I hope it prompted you to think about something differently enough that you’d share it with someone who’d get something out of it too.

I started this podcast because tactics never stuck with me. What stuck were stories — business biographies, autobiographies, the decisions people made and why they made them. The principle only clicks once you know the story behind it.

So I built the thing I wanted to listen to. Every week I have two conversations with people who build in technology and product. Then I write the essay in my premium newsletter (Taste Maker) to distill the principles and reflect on the narrative — one that puts you inside the conversation, through my eyes. What caught me off guard. What I kept thinking about after we hung up. Where the principle actually lives once you strip away the jargon.

I make this for myself first. If you read the way I do, you’ll want it too.

PS — If you want to pitch coming on the show, or you know someone I should talk to, shoot me an email at caden@hey.com with "January752" in the subject line so it gets past my filters. I'm not optimizing for famous guests. I'm optimizing for interesting conversations, even from people who aren't LinkedIn influencers.

Listen to this episode on Spotify or Apple Podcasts

Before Adnan Malik built the company, he lost the same argument from both sides of it.

On one side he was running demand generation for a health-tech SaaS business, holding a budget, trying to buy leads that were worth buying. “We have the money, we have the cash,” he says, “but, you know, whenever you’re spending, you get, you know, all sort of bogus leads.” The leads landed in the pipeline. And sales worked them. And sales closed some of them, because sale at the end is sale, and the wrong customers churned out the back a year later. That is the vendor’s version of the problem.

On the other side he was the buyer. Over the course of his career he implemented seven or eight different SaaS tools, and he is unsparing about how that went.

“I used to spend so much time, like months, and we still make the wrong decision.”

Months. Still wrong. But he offers the reason without any defensiveness, and it is the most honest sentence in the conversation, because it is a limit rather than a failure.

“Because humanly, I can only look at maybe three or five different tools. I cannot speak to fifty different companies.”

And that is a person describing the ceiling on his own attention. Not his diligence, not his budget, not his seniority. The number of vendor conversations a working adult can actually hold in a quarter while also doing the job they were hired for.

And what he wanted, in those months, did not exist.

“There was no company where, you know, I can just call like, like a free call and say, ‘Hey, you know, I’m looking for this software, you know, as per experience, as per my needs, recommend me.’”

And he co-founded SoftwareFinder in 2019 with two colleagues, all three of them out of marketing and sales. It is bootstrapped, no outside money, and by his account it has grown about 110 percent a year for five years. They got a customer in the first month. “And then we never looked back,” he says, which is the kind of line founders use to compress a great deal of anxiety into six words.

But the interesting part of the company is not the growth rate. It is the diagnosis underneath it, which Adnan states as plainly as if it were common knowledge, and which I do not think is common knowledge at all.

The people buying business software are almost never technology people.

“If someone in your company is looking for HR software, it’ll be your HR manager. If someone is looking for project management software, it’ll be your project manager. If someone is looking for, you know, marketing automation, it’ll be your digital marketing person or demand gen person, right?”

And then the flat verdict.

“They’re not trained on how to shortlist technologies because that’s not their background. Their background is something else. Now they have a need for a software.”

Read that last sentence again, because it is doing something careful. He does not say they are bad at it. But he says they have a need. The need arrived at their desk, unaccompanied by any of the skills required to meet it, and they are going to meet it anyway because nobody else is going to.

I described to him the stereotype I have watched play out inside mid-market companies, which is that marketing ends up on HubSpot, sales ends up on Salesforce, and finance ends up on NetSuite, and every one of those vendors wins the deal on its own terms. What the company gets is three systems that were each chosen well in isolation and that now have to be lashed together with API connections nobody budgeted for. Adnan agreed, and then pushed it further than I had, into the specific questions those buyers do not think to ask.

And his consultants ask how fast the company expects to grow. Not because growth is nice, but because the answer changes the recommendation. Buy for the company you are and you may spend two years earning the sentence he quotes back with visible distaste.

“Oh, I’ve outgrown this software, now I need to switch.”

“Which is the worst thing to do,” he says. And then data migration. And rerouting the APIs. The whole apparatus rebuilt because a decision made by a well-meaning marketer in month one did not account for month thirty. And the cost of getting it wrong is not a bad quarter. In his phrasing, implementing the wrong tool “can really dent your business,” because your attention shifts to repairing the choice instead of to growth.

So here is the compression the company actually sells.

“We cut down their research time from anywhere from two to three months to, 10-minute phone call.”

Two to three months, into ten minutes. And it sounds like marketing until you notice what is being compressed. Not the reading. Not the demos. The part being removed is the buyer’s obligation to become, temporarily and badly, a technology analyst.

And I want to be careful here, because the unglamorous thing in this business is the thing that works. Craft in this market is not the matching engine. It is that a human being picks up a phone, spends 10 or 15 minutes, and asks a marketer about their growth curve and their existing stack and the departments they have not thought about yet. But Adnan is not romantic about it. He describes it as a service business and says so repeatedly, and he built a proprietary system in-house to help the consultants match rather than replace them.

The detail that persuaded me most is a small one, and it is the kind of thing you only do on purpose.

“If we’re recommending five, we try to make sure that we recommend three large and two small.”

Two slots, held open, every time, for companies with no brand and no budget to buy their way onto anyone’s list. And he is candid that some of the best software he sees comes from firms nobody has heard of. Reserving two of five for them is a decision that costs him something and that no buyer would ever notice was made.

All of which loops back to why he never raised money, and to the only piece of founder advice in the conversation I would repeat without qualification.

Adnan’s rule is not that venture capital is bad. It is that bootstrapping is a bet on a market that already exists.

“If you wanna do bootstrap, you have to do bootstrap where the market is ready. The demand is there. People are looking for, you know, a solution that you’re gonna be providing.”

And if you are building something nobody has asked for yet, something that requires teaching an entire market that it has a problem, he does not hedge.

“Then good luck.”

And he knew software buying was already happening at enormous volume. He knew buyers were already frustrated, because he had been one. There was nothing to teach the market. But there was a better way to serve a demand that was going to exist whether or not he showed up. That is what let him ask his own first question, the one he says every founder should answer before anything else, which is where the initial dollar is going to come from.

He is gentler about the founders who cannot do this than I expected him to be. When I raised the wealth math of entrepreneurship, the years of flatlined or negative net worth that mass-market financial advice never accounts for, he did not turn it into a courage story. And he talked about savings. Fifty thousand, a hundred thousand, two hundred thousand of your own money, and the plain fact that a young founder a couple of years into working has not accumulated it.

“When you’re young, you don’t have that kind of saving, and you rely on that seed funding.”

No shame in the sentence, and no advice attached to it either. It is a constraint, described accurately. He is unusually good at that.

The last thing we got to is the shift that has rearranged his channel, and it is where his content library turned out to be an accident of good fortune. Two years ago, he says, roughly 90 percent of software research started with a Google search. Now about 55 percent of software-buying searches begin inside a language model, counting Google itself, which he notes is “pretty much becoming LLM” now that the AI overview sits on top and people have stopped scrolling past it.

And SoftwareFinder spent six years as a content website and accumulated something like 200,000 pages. Those pages are now being read by the models, and his traffic has climbed about 350 percent in a year. He is clear-eyed that this is a structural windfall rather than genius. But marketplaces had the corpus. SaaS companies that spent a decade winning at SEO are watching the channel drain, losing traffic and therefore losing leads, and they are hunting for replacements.

But notice that the shift does not touch the thing underneath. A marketer who asks a language model which HR system to buy is still a marketer who was never trained to evaluate HR systems. The research got faster. And the confidence went up. But the competence did not move.

Which is the whole business, and Adnan has been on both ends of it. He was the vendor buying bogus leads because nobody in the middle was sorting the buyers. And he was the buyer spending months on three or five tools out of fifty because nobody in the middle was sorting the vendors. The data, the 200,000 pages, the matching system, the hundreds of software sitting in every category, all of it is scaffolding around ten minutes on a telephone with someone who knows which questions you forgot to ask.

Guest Bio: Adnan Malik

Adnan Malik is the Co-Founder and CEO at Software Finder, a B2B software marketplace that pairs buyers with vetted vendors through a live consultative phone call rather than a self-serve directory. Rising to prominence for building the company entirely without outside funding, he became known for a bootstrap-first playbook that prioritized revenue in the first three months over product polish. Founded in 2019, Software Finder has sustained roughly 110% year-over-year growth for five consecutive years and is reported to have reached approximately $20 million in annual recurring revenue.

Previously, in his last role before founding Software Finder, Malik led marketing and sales for a health-tech SaaS company, where he encountered firsthand the lead-quality problem that became his company’s founding thesis: buyers spending months evaluating software with no reliable, human-vetted source of truth. He co-founded Software Finder with two colleagues who shared that same marketing and sales background, betting that a phone-based consulting layer could compress a two-to-three-month buying research cycle into a single ten-minute call.

Earlier in his career, Malik worked across client success and implementation roles inside SaaS companies before moving into sales and marketing leadership. He holds a degree from London Metropolitan University and is based in New York.

Hey,

Thanks for reading this. I mean that. There’s a lot of content out there competing for your attention, and you spent some of it here. I hope it was worth it. Even better, I hope it prompted you to think about something differently enough that you’d share it with someone who’d get something out of it too.

I started this podcast because tactics never stuck with me. What stuck were stories — business biographies, autobiographies, the decisions people made and why they made them. The principle only clicks once you know the story behind it.

So I built the thing I wanted to listen to. Every week I have two conversations with people who build in technology and product. Then I write the essay in my premium newsletter (Taste Maker) to distill the principles and reflect on the narrative — one that puts you inside the conversation, through my eyes. What caught me off guard. What I kept thinking about after we hung up. Where the principle actually lives once you strip away the jargon.

I make this for myself first. If you read the way I do, you’ll want it too.

PS — If you want to pitch coming on the show, or you know someone I should talk to, shoot me an email at caden@hey.com with "January752" in the subject line so it gets past my filters. I'm not optimizing for famous guests. I'm optimizing for interesting conversations, even from people who aren't LinkedIn influencers.

Listen to this episode on Spotify or Apple Podcasts

Somewhere there is a phone call happening that Ashley Aruffo will never sit in on, and it is the call her whole company exists to produce.

A buyer at some large manufacturer is on the line with one of its suppliers. Routine check-in, the kind that usually runs on pleasantries. And then the buyer says something that is not on the agenda, which is that the supplier’s financial viability is looking a little weak, and here are the five reasons why.

There is a beat on the other end.

“Whoa. How’d you know that?”

Ashley delivers the supplier’s line with the timing of someone who has heard it relayed back to her many times. “That’s that special moment,” she says, “where you’re like, ‘Okay. I would’ve never known to ask that question,’ and it’s true, and it’s been validated, and there’s a little bit of shock.”

I want to be precise about what is strange here. It is not that the buyer has secret information. But the buyer has ordinary information, assembled correctly, about a company it has been doing business with for years. The shock in that room is the sound of a relationship discovering it was never really examined.

Ashley runs product and operations at Craft, which she describes as the Zillow for companies, though she says that mostly as a shortcut for people who do not live in supply chain. What Craft actually does is deconstruct a company’s supply base into as many touch points as it can identify, then grade what it finds. It works with more than 36 government agencies. It brings in over 40 streams of data and multi-sources all of it. She has been there five years, and before that she went into product straight out of college and, in her telling, did every single job a startup has.

She says the thing early, without ceremony, the way people say things they have stopped hearing as strange.

“Most people don’t actually know, first of all, who their first-tier suppliers are.”

First-tier, not the subcontractor’s subcontractor. The companies whose names are on the contracts.

She is careful to separate the cases. Small businesses doing niche work know everything, she says, down to the temperature of the cart carrying whatever they build. Large enterprises are not like that. “They’re stratified. They’ve got all of these different groups that they work with.” The knowledge exists somewhere in the org and it exists nowhere in particular, which for operational purposes is the same as not existing.

And for a long time the industry’s answer to this was a survey.

You send your supplier a form. Do you deliver on time. Do you work in countries you shouldn’t. How do you process your materials. What’s the quality. A category manager collects the answers and, as Ashley puts it, “the survey gets answered, and then you’re off to the races, and you have your own products that you’re building.”

Sit with the shape of that. And the party being checked fills out the check. Nobody in the chain treats this as absurd because the alternative was nothing, and a form returned is more than no form at all. This is how a great many high-stakes industrial processes actually run, on an artifact everyone quietly knows is theater, until something better exists.

I have watched a smaller version of this from the inside. One of my early jobs was in the produce supply chain, where a truck of grapes coming up from Peru can carry three million dollars of value and a popped tire can end the whole thing in a ditch. The uncertainty is not exotic. And it is a tire. But even there the visibility ran out fast, and I could not tell you who drove the truck. Ashley’s version of that question is blunter. “Do I even know who drove my grapes to the building? Probably not, right?”

What changed first was not intelligence. It was observation.

She dates it to about four years ago, then catches herself and revises upward. But whenever it was, five or six vendors came to market claiming they could infer relationships between companies from shipping records. The mechanism is unglamorous and clever. Every shipment carries an HS code, and that code tells you within eight digits what is moving and how often. Assemble millions of those and you can watch who ships to whom without asking anyone anything.

Which produces conversations like the one Ashley describes running herself. You ask a company whether it has operations in a particular country. It says no. And you say, more or less pleasantly, that its shipping records show a great deal of metal moving back and forth, so are we sure nobody in that country is inside the components.

And the data was a mess. But it sold anyway. “Craft was able to sell it in like Excel spreadsheets to companies for tens of thousands of dollars,” she says, “because people just wanted to get that visibility that no one was responding in their surveys.” Five figures for a spreadsheet, because the spreadsheet was the first thing that was not a form the supplier filled out about itself.

But observation is not knowledge, and Ashley has a word for the difference. She calls the first one visibility, and the second one traceability, and the whole conversation turns on the gap between them.

“So traceability is, okay, I’ve seen the outside world. There’s a whole lot of noise. How do I deconstruct my product and kind of find that line of providence?”

The noise is the problem, and the noise has a specific shape, and this is where the work stops looking like artificial intelligence and starts looking like janitorial labor.

But forty sources are talking about companies. And are they talking about the same companies?

“What do I mean by entity resolution?” Ashley says. “I mean, is company A, company A?”

“ABC Company, ABC Company LTD, ABC Company LLC, right? Are we all talking about the same company, right?”

Three strings. One question. It is the least impressive-sounding problem in the entire field and it sits underneath everything else. She reaches for her own name to make it concrete, the way you do when you want someone to feel a distinction rather than agree to it. Ashley Arrufo, Ashley Arruto. Two Ts in the middle. A fuzzy match will happily call those one person, and it will be wrong, and nothing downstream will tell you.

Because here is what happens if you get that wrong at the front. You build a monitoring system on top of it. Then you build a diligence platform that writes deep research reports. Then you tag everything against entities that were never correctly separated in the first place. “And I start tagging all of this information wrong, I feed you the crappiest report.”

And the report still looks like a report. That is the part that should frighten people.

There is a register shift when she talks about this stretch of the work, and it is worth noting because it runs against how everyone else in her industry talks right now. She does not pitch it. But she almost apologizes for it and then refuses to.

“Sometimes people say it’s like the garbage collection, but it is. We are literally cleaning as much as we possibly can to get the right intel.”

I have interviewed a lot of people building things on top of frontier models over the last two years, and the pattern is nearly always to describe the reasoning layer and skip the plumbing. Ashley does the opposite, because in her market the plumbing is the product. Anyone can ask a model about a company. The model will answer confidently. What Craft is selling, in her framing, is that you do not have to go check — and she is honest that most customers check anyway. “Mostly people do fact check even on top of what we do, but our power is that, like, when they check they’re more confident.”

That is a smaller claim than the industry standard and a much harder one to fake.

The stakes stop being abstract when she gets to the government work. Billions of dollars flow into American innovation funding every year, toward small businesses coming out of labs, universities, someone’s garage. Historically anyone could apply, patent in hand. And some of those patented innovations, she says plainly, ended up in the Chinese patent market — American money funding innovation into countries the money was never meant to reach.

So Craft’s team spent this past year working backwards through how that actually happens. But it is rarely a heist. It is structure. Shell companies. Six locations where the org chart says one. A foreign investor buying into a grant recipient and taking a board seat, which is a perfectly legal way to sit close to something you would like to understand. Ashley’s own summary is a list of questions rather than accusations. “Is that person really tied to that person and who’s on their board, you know?”

And every one of those questions is the same question as ABC Company LTD. It is identity. Whether two names are one thing.

And this is where her own history folds back on itself in a way she notices out loud.

Six or seven years ago, by her own reckoning, she was at a five- or six-person startup automating the extraction of information out of mortgage documents. The technical founder had it mapped, and it worked, and it needed one thing the company could not obtain. Training samples. Which meant trust, at volume, from institutions handling the most sensitive financial paperwork most people ever sign.

She is unsentimental about how that went.

“My first big hurdle that I had to jump with the team then was like, how do we engender trust to get this information and get as many samples as possible as a tiny little startup? And the answer was like, we candidly couldn’t do it.”

They were acquired by Black Knight, an organization that processes over 80 percent of mortgages in the world and already had the relationships. The bottleneck was not solved so much as routed around, which she describes without any of the flinching that usually attends that kind of story.

What she says about the present is the same sentence with one noun swapped.

“I’m not like bartering for data. I’m try- now I’m bartering for, you know, the right model and the r- right infra for the job.”

Same job. New currency. The scarce thing used to be samples and now it is judgment about which model is worth pointing at which task, and she is emphatic that you do not hammer the most expensive model at everything, that Craft stays model-agnostic and runs its own evaluation infrastructure precisely so that question stays open.

Meanwhile, the competition she actually loses to is not another vendor.

“90% of the time, you know, we’re still competing against a spreadsheet.”

Someone at a desk, gathering intelligently by hand, doing the entity resolution in their own head without calling it that. And she says this without contempt. It is where the work has always lived.

Near the end I ask her what she likes now, given that the VP job took away the part she loved, which was being set loose on a problem and fixing it herself. She loves chaos. She says so directly, and then says that the same ambiguity that is fine among five people in one room will derail a distributed team, so she stopped building clickable prototypes nobody remembered and started bringing one slide to every call.

But the answer she lands on is not about slides.

It is about the fact that she has now worked with some of these people for four or five years.

“I know exactly their reaction, and I also know the areas that are like not incredibly strong, but we’re all talking about it with each other.”

Craft exists because, at scale, you cannot know who anyone is. You infer it. You cross-reference 40 sources, you grade them, you decide whether three strings are one entity, and when you do it well a supplier on a phone call says whoa because a stranger has correctly described their situation without ever asking them a question.

And the thing she names as the payoff, after five years of building the machine that resolves strangers into knowns, is a small group of people whose reactions she does not have to resolve at all. And she just knows them. No sources to grade, no fuzzy match to worry about, no report that could be confidently wrong.

The rest of the world still has to be inferred.

Guest Bio: Ashley Aruffo

Ashley Aruffo is the VP of Product and Operations at Craft, a San Francisco-headquartered supply chain intelligence company that maps supplier networks and delivers risk insights to procurement professionals, risk analysts, and government agencies. Rising to prominence over five years with the company, she became known for building intelligence products for the defense industrial base, where Craft now works with more than 36 government agencies and resolves over 40 streams of data into a single verified picture of a company. Craft raised a $32 million Series B in February 2023 led by BAM Elevate, with participation from Greycroft, Uncork Capital, High Alpha, ServiceNow Ventures, and Point Field Partners, and holds a five-year, $28 million contract with the Secretary of the Air Force for supplier risk and intelligence technology.

Previously, she served as Division Head of Product, Applied AI at Black Knight, the mortgage technology company that acquired her prior employer. She arrived there through HeavyWater, a Philadelphia machine-learning startup whose AIVA product automated the extraction of income, asset, and insurance information from mortgage documents, and which Black Knight acquired in June 2018. At HeavyWater she confronted the constraint that defines small machine-learning companies: a startup cannot earn the customer trust required to obtain the training samples its models need, a bottleneck the acquisition resolved by handing the team access to an established book of lending clients.

Earlier in her career she worked as a Product Manager at Energage, an employee-engagement software company, after entering product directly out of college and, by her own account, performing every job a startup has to offer. Her work has spanned B2B and B2C products, though she has concentrated on enterprise software built for narrowly defined jobs.

Hey,

Thanks for reading this. I mean that. There’s a lot of content out there competing for your attention, and you spent some of it here. I hope it was worth it. Even better, I hope it prompted you to think about something differently enough that you’d share it with someone who’d get something out of it too.

I started this podcast because tactics never stuck with me. What stuck were stories — business biographies, autobiographies, the decisions people made and why they made them. The principle only clicks once you know the story behind it.

So I built the thing I wanted to listen to. Every week I have two conversations with people who build in technology and product. Then I write the essay in my premium newsletter (Taste Maker) to distill the principles and reflect on the narrative — one that puts you inside the conversation, through my eyes. What caught me off guard. What I kept thinking about after we hung up. Where the principle actually lives once you strip away the jargon.

I make this for myself first. If you read the way I do, you’ll want it too.

PS — If you want to pitch coming on the show, or you know someone I should talk to, shoot me an email at caden@hey.com with "January752" in the subject line so it gets past my filters. I'm not optimizing for famous guests. I'm optimizing for interesting conversations, even from people who aren't LinkedIn influencers.

Listen to this episode on Spotify or Apple Podcasts

The two established players in military weapon storage had systems with 87 and 270 different components. Tom, who’d never owned a firearm, designed one with a single moving part. He credits the whole thing to not knowing what a weapon rack was supposed to look like. “I never saw the box,” he tells me — and the line reframed how I think about beginner’s mind as a competitive advantage.

It is 2001, and Tom Kubiniec is running a telemarketing business in upstate New York that sells backup tapes and hard-drive cabinets to hospitals. His phone rings. The man on the other end asks whether Tom can store an MP5.

“Sure,” Tom says. He is a sales guy. Sure is always the right answer. Then he asks the follow-up question that will define the next twenty-five years of his life.

“What’s an MP5?”

“A little submachine gun,” the man tells him. Tom starts laughing. He asks who this is. It is the FBI. They are, the man explains, struggling with weapon storage.

Tom tells him to give him a week.

He has never held a firearm. He does not know what an armory looks like. He runs a company called Greenline Data whose flagship product line is tape racks, sold under the domain name TapeRack.com. He has spent the last decade convincing IT departments to lock up their hard drives after the HIPAA laws came out. That is his beat. Guns are not his beat. But it is 2001, this is long before Google, and Tom starts digging through Yahoo and the other search engines nobody remembers now, and what he finds surprises him. The military is transitioning from the M16 to the M4 — a modular platform with attachments and optics and a lot more parts moving through a lot more armories than the old system was ever designed to hold. Nobody has caught up. The equipment they use to store weapons has not changed to match the equipment they store.

He calls a manufacturer he already works with — one of his tape-rack suppliers — and starts sketching.

I want to stop the story here for a second, because when Tom tells me this on our call, sitting in front of a wall of Cradle Grid racks that will eventually equip most of the US military’s small-arm armories, I keep waiting for the part where he explains how he learned about weapon storage. There isn’t one. He never learned it. He just started designing storage that would fit the problem the FBI had described, using the vocabulary of a man who thinks about how to hang things on tape racks for a living.

“Everybody was trying to solve a problem saying, look, this is what we have. This is the problem. How do we fix it? I didn’t have access to a lot of that. So I came at it — you know, people say, wow, you’re really thinking outside the box.”

“I never saw the box.”

Most of what I hear founders say about beginner’s mind is a retroactive story. They tell it after they’ve won, and the story flatters them: I was naive, I didn’t know it couldn’t be done, so I did it. That is not really what Tom is describing. Tom is describing something more specific. The two established weapon-storage systems on the market when Tom entered had 87 different brackets and 270 different components. Tom designed his rack with one moving part — a single upper cradle that adjusts by hand, tool-free, so an armorer can walk up to it with anything from a small submachine gun to a belt-fed machine gun to a shoulder-launch rocket system, adjust it in real time, and walk away.

He got to a one-moving-part answer because he was not carrying the last decade of assumptions about what a weapon rack needs to look like. His competitors were. He walked into Home Depot with a notepad — literally, he tells me, he went to Home Depot and walked the aisles asking himself how America stores stuff in general — because the reference material available to him was the reference material available to a civilian.

I want to name what this is, because it isn’t a personality trait and it isn’t an origin story. It is a design method. The method is: refuse to look at the prior art until you have solved the problem your own way at least once, and then look at the prior art with the answer already in your hand.

Tom uses the method still. That is the part that surprised me. Twenty-three years into this — an interval long enough for anyone’s beginner’s mind to have calcified into a set of professional convictions — he still does the same thing on new problems. He tells me he closes his door, sits at his desk with a piece of paper, and draws. Doodles, mostly. He is one of those people whose meeting notes are half sketchpad. He drives a 25-to-35-minute commute deliberately, keeps the audio off, and talks out loud to himself in the car, giving a speech to an empty passenger seat until he talks his way into a corner and then talks his way out. He isolates first, solving in a bubble, and only then brings the problem to his team, or to outside consultants — with one rule he refuses to break: he never tells them what he has come up with before they take their own shot at it.

“The minute I show them how far I am, once they see what I’ve got, they build from there. Their creativity is forever jaded because they saw a prototype.”

The word he keeps using is jaded. Not tired. Jaded — as in, the second you see the reference answer, some part of you commits to it and stops being able to see anything else. It is what he thinks happens to whole industries and to individual careers — and it is the one thing he refuses to let happen inside his own house.

There is a scene later in the conversation where he describes running timed brainstorms. Small group, never large. He sets a timer for five minutes and asks for normal ideas. Then he breaks, resets the timer, and asks for the craziest, stupidest ideas anyone in the room can produce. He drives everyone to laugh, to be loud, to be ridiculous, on purpose — because his experience is that the stupid ideas and the good ideas share a border, and that if he can get the room comfortable enough to be stupid, sometimes what surfaces is neither. Sometimes what surfaces is something ingenious that only looked stupid because nobody had permission to say it yet.

I keep coming back to the fact that Tom is a heavy metal guitarist. He tells me this early — professional guitar player out of high school, Iron Maiden and Judas Priest era, tended to that end of his career before he got into sales. And in the middle of our conversation, when I put it to him that his facilitation style sounds like what the best music producers do — set up the room, give the artist permission to be terrible, use their taste to direct without dictating. I relate it back to Rick Rubin describing himself, on David Senra’s podcast, as “lazy”. Rubin said he’d rather be walking on a beach than in the studio, but he keeps coming back because every couple of weeks there is a breakthrough, and the dopamine hit is enough to carry him to the next one.

That is the actual practice under the beginner’s-mind story. It is not naivete. It is the discipline of protecting the conditions under which a not-yet-obvious answer can show up. Isolation, then a room built for stupid ideas, then the willingness to sit with a problem long enough that the answer arrives on its own timeline instead of being forced by the deadline. It is patience masquerading as instinct.

I think about what would have happened if the FBI had called a company that already made weapon racks. They would have gotten another weapon rack, probably with a few clever improvements to the existing 87 or 270 components. It would have solved the immediate problem and locked in the underlying assumptions for another decade. The armory would still be difficult to operate. The armorers would still be doing the same unnoticed dance around the same badly designed hardware. Nobody would have looked at a Home Depot aisle and thought about it.

The company Tom actually built is called SecureIt Tactical, and by 2011 it was the primary supplier to the US military for armory design and weapons storage. In 2016 they carried the same design philosophy into the consumer market, and consumer products are now about 85% of the business. They made the Inc. 5000 twice in three years. The military line is called Cradle Grid now. The consumer line uses the same single-moving-part logic.

Tom tells me all of this the way you tell the story of a thing that mostly worked. Not the way you tell a founding myth. He talks about the sequestration years when the government contracting dried up and he went nine months without a single order, sold his plane, was preparing to sell his house. He talks about the CEO coach he hired on a three-year contract because he needed someone to tell him to stop reinventing the company every Monday morning. He talks about firing fast. He talks about a market that is down 56% over the last three years, in which his sales are flat, and which he describes as exciting to be in for exactly the reasons a normal executive would describe as terrifying.

But he keeps coming back, when I let him, to the box he never saw. He says it again near the end of our call, unprompted, in a different context. Twenty-three years in, and he still describes his own advantage as the thing he did not know when he started. Every time he draws a new component alone in his office, every time he sets the timer in a brainstorm, every time he holds his own idea back from the room, he is trying to reproduce the conditions of a phone call in 2001 when a stranger asked him about a weapon he had never heard of, and he answered before he had time to know he shouldn’t.

You can only do something for the first time once. Tom’s whole method is a way of pretending, over and over again, that it is still the first time.

Guest Bio: Tom Kubiniec

Tom Kubiniec is the President and CEO of SecureIt, the leading authority in small arm storage and armory design for both military and consumer markets. Rising to prominence in the early 2010s, he became widely recognized as the primary civilian supplier to the US military for weapons storage and armory design services after winning a critical US Army Special Forces Command survey contract in 2007. Under his leadership, SecureIt appeared on Inc. Magazine’s fastest-growing companies in America list twice within three years, reaching No. 3812 on the Inc. 5000 with 167% three-year revenue growth.

Previously, as founder of Greenline Data, he built one of the largest B2B sellers of backup tape storage racks through TapeRack.com before pivoting to secure laptop storage under HIPAA regulations in the mid-1990s. That pivot — physical storage of sensitive hardware — became the direct bridge into weapon storage when an FBI agent called in 2001 asking whether Tom could store an MP5 submachine gun. He became known for treating military armory design as a first-principles product problem: after spending 18 months on the road surveying every US Army Special Forces armory, he invented and patented CradleGrid™, a weapon storage platform built around a single moving part that replaced competing systems with 87 to 270 separate components.

His career began with Jet Computer Products, which he co-founded in 1987 as a B2B computer supplies company, where he spent seven years developing the sales and distribution instincts that would later define SecureIt’s consumer launch. Before that, he performed professionally as a heavy metal guitarist — a background he credits with developing the creative instincts and pattern-breaking temperament he applies to product design and company culture today.

Hey,

Thanks for reading this. I mean that. There’s a lot of content out there competing for your attention, and you spent some of it here. I hope it was worth it. Even better, I hope it prompted you to think about something differently enough that you’d share it with someone who’d get something out of it too.

I started this podcast because tactics never stuck with me. What stuck were stories — business biographies, autobiographies, the decisions people made and why they made them. The principle only clicks once you know the story behind it.

So I built the thing I wanted to listen to. Every week I have two conversations with people who build in technology and product. Then I write the essay in my premium newsletter (Taste Maker) to distill the principles and reflect on the narrative — one that puts you inside the conversation, through my eyes. What caught me off guard. What I kept thinking about after we hung up. Where the principle actually lives once you strip away the jargon.

I make this for myself first. If you read the way I do, you’ll want it too.

PS — If you want to pitch coming on the show, or you know someone I should talk to, shoot me an email at caden@hey.com with "January752" in the subject line so it gets past my filters. I'm not optimizing for famous guests. I'm optimizing for interesting conversations, even from people who aren't LinkedIn influencers.

Listen to this episode on Spotify or Apple Podcasts

Ben Rennie wrote his book Lessons in Creativity partly with AI — first as a ghostwriter, which broke his voice inside a paragraph, and then as a coach he had to instruct to disagree with him.

Ben Rennie is trying to finish the last three chapters of a book he has been writing for four years, and the language model on the other end of his prompt has just handed him back a sentence he would never in his life have written. It says something like wonderful day. He reads it back. It is grammatically fine. It could go into the manuscript, and no reader would flag it. But it is not his. He has never used the phrase in a conversation, has never used it in an email, would not use it in a room. And here it is, in the paragraph he has just asked a machine to draft for him because he is exhausted and his thumbs are done.

“It was such a weird experience,” he tells me, “to think that this wasn’t my words. This wasn’t me.” His tone of voice had changed inside a paragraph. His writing style had changed inside a paragraph. He had not authorized any of it. He had just plugged the machine in.

Ben — who runs the Sydney and Los Angeles design studio Reny, who chairs Design Declares Australia, who has spent nineteen years in rooms where the client is Nike or Patagonia or the NBA — was not expecting to find out about the future of his profession while a chatbot was quietly re-writing him. But that, he tells me on the call, is what happened. He tried to use AI the way an exhausted author is supposed to. He asked it to finish. It agreed to finish. And in agreeing, it produced sentences with a stranger’s cadence and passed them off, briefly and confidently, as his.

He caught it inside a paragraph. Most people, he suspects, do not.

Ben’s book, Lessons in Creativity, came out on May 1st in Australia and now sits in Barnes & Noble, Target, Amazon, Heathrow’s WH Smith, and airports across three continents. It was runner-up for Australian Business Book of the Year. It was written, in the end, mostly by hand — and specifically by voice, dictated into a phone and cleaned up on a keyboard later. It was written partly at his friend’s writing room up in Byron Bay, in far northern New South Wales, where the trees are quiet and the internet is optional. It was also, in its last stretch, written with an AI system Ben was still figuring out how to talk to. This essay is really about that stretch. Because when Ben describes what he learned there, he is describing the thing I have been trying to name for a year of doing this podcast and could not.

Everyone I’ve interviewed who works seriously with AI has told me some version of the same story. They say the tool didn’t remove the work. It moved it. What used to be the boring part — writing the paragraph, staging the code, formatting the deck — is now cheap. What used to be the invisible cost of doing the work — knowing whether the paragraph is any good, whether the code is doing the right thing, whether the deck’s third slide is a lie — is now the visible part. The struggle didn’t go anywhere. It rescheduled itself. It moved from the part you could excuse by exhaustion to the part you cannot excuse by anything.

Ben lives this in a very specific way. When he tried AI as a ghostwriter, the machine agreed too easily. It agreed with his prompts, then it agreed with itself, then it agreed to write “wonderful day” into a chapter about creative confidence. He shut it down. He tried something else. He told the machine to be a coach — a sounding board, a devil’s advocate, a critic who would sit in the writing room with him and beat up his structure. This started to work. And then, he says, “I actually found it was being too nice to me. It was agreeing with me all the time.”

Hold that image for a second, because it is what the AI conversation almost never talks about. Not the machine that is stealing his job. The machine that is agreeing with him too much. The failure mode wasn’t that AI was aggressive or wrong. It was that AI was accommodating. It liked his ideas. It liked his sentences. It thought his chapter structure was strong. He read those responses back and — because Ben is fifty and has been ambushed by his own audience enough times to know what real feedback feels like — he could tell the room was faking.

So he did the thing that only somebody who has been in the actual room does. He gave the machine permission to disagree with him. “I needed to give it some parameters,” he says. “Don’t agree with me. Beat this thing out. I’ll kick the shit out of this thing.” What Ben has just done is describe the interior craft of every good editor Ben has ever worked with, and he has done it to a language model. He has told the machine that its default of niceness is a bug. He has instructed it on what to do with its own trained tendency to please. He has, in other words, taught it — the way a writer teaches a first-year editor — that the point isn’t validation. The point is the manuscript.

The reason this matters, and the reason it keeps landing on me as we talk, is that Ben is exposing the second failure mode of the AI story. The first failure mode is the one on the front page of every technology magazine — AI takes your job. The second is quieter and, I think, worse. AI agrees you were right about your job. It agrees that your paragraph is publishable. It agrees the strategy is sound. It agrees that the deck’s third slide is fine. It reschedules the struggle to a room you now walk into alone — the room where somebody has to tell you your paragraph is not publishable, and it isn’t going to be the machine.

Ben, on the call, is generous about all of this. He is not a doomer. When I ask him what happens to the design profession as AI generates art and knocks out landing pages and drafts case studies, he does not tell me the profession is over. We discuss Kevin Kelly, the founder of Wired. “People always say (AI) is taking jobs. And Kevin Ask’s, whose job?
Who do you know?” Ben says he thinks about that a lot. He does not know, personally, anyone who has lost a job to AI. He is sure the people exist. But the specific person, the one whose life changed on a Tuesday when a model shipped — he cannot name them. “I like his conversation around AI,” Ben says. “He’s always been at the forefront of technology in such a positive way and tries to ensure that we’re building things for good.”

The Kevin Kelly move, for Ben, is not to litigate whether AI is good or bad. It is to notice what happens to a craft when the friction on the boring part disappears. Ben came into his industry through print work. He watched print become graphic design, watched graphic design become UX, watched UX become behavioral design, watched behavioral design become the systemic-design frame he now teaches at universities. He is not new to the story where the tool eats the previous version of the tool. He is new to the version where the tool arrives already trained on his voice, and everyone else’s, and the design work he now has to do is figuring out what to make out of a world that already looks like it has been made.

I ask him what he tells the young designers on his team, and he says the thing you’d expect a nineteen-year founder to say and mean it. “We can’t control the future. What do I need to do to be present now? What are the things I need to make now? What sort of business do I need to make now?” He is not offering it as a slogan. He is offering it as the exact way he has himself lived through five previous versions of the field is over. Each time, he says, the answer was the same. Do the work. Do it while the world argues about whether it counts. Publish anyway. Ship anyway. He mentions a novel called The Last Policeman, which he read as one of the fifteen-minute summaries he has admitted to me are a bad habit. The novel is about the world ending. The main character is a policeman who continues, all the way through the apocalypse, to do his job. Ben says it left an impression on him. “That’s the thing he was put on the earth to do.”

I take this the way it is offered — not as a heroic pose but as a defense of continuing to make while the argument rages. Then Ben, without meaning to, tells me the harder version of the same idea. He is talking about writers, but he could be talking about anyone. He says that when he started dictating into a phone instead of typing, his relationship to the work changed. He didn’t need the keyboard. He didn’t need to be at the desk. He could talk into the phone in his car and edit the transcript later, and the words would come out looking reasonably like his. It was, he says, one of the better uses of technology he had personally found. He built the efficiency around himself — a piece of AI he had actually taught what to keep and what to strip, one dictation session at a time.

Which is a version of what I have been finding myself. I use Claude to draft. I dictate into a mic, get a document back that would have taken me an hour to type, and then have to make a decision most of the AI conversation is not equipped to help me with. The decision is whether I know what I just said well enough to defend it in front of somebody who read it. That decision has not gotten easier. If anything, it has gotten sharper — because now I can produce a thousand words in the time it used to take me to type two paragraphs, and if I present a document I don’t fully own, I get caught faster. AI didn’t remove that risk. It rescheduled it. It moved the moment of accountability from did I finish this draft to do I actually know what this draft is saying.

Ben, in his book, has an image for the space AI leaves the rest of us to sit in. He borrows it from Seth Godin, whose book The Dip argues that the point of any hard thing is the dip — the middle stretch where the enthusiasm has gone and the finish is not yet visible, and the only sensible move is to keep going. Ben says he thinks AI is the dip. “There’s heaps of opportunity that is given to us through AI, but it’s the dip. It’s the unknown. We don’t know what’s going to happen in this little valley of terrifying AI world. But all we can do, I think, is push on and do the work and be really good at the work we’re gonna do.”

I think Ben has this right, and I want to end on the sharper implication. The reason a lot of people in design and technology feel demoralized right now is not that AI has removed the meaningful part of their work. It is that AI has removed the part that used to feel like doing the work — the friction, the typing, the drafting, the slow accumulation of pages that felt, cumulatively, like proof. That felt-friction is gone. What is left is the thing the felt-friction always contained — the hard question about whether the paragraph, the code, the deck, the design, was any good. The struggle is still there. It just doesn’t announce itself with sore fingers anymore.

Ben caught the machine writing “wonderful day” into his manuscript inside a paragraph. Most people, he suspects, do not. What he learned in that paragraph is what the rest of us are about to learn. The tool did not finish the book. The tool arranged the ambush.

Guest Bio: Ben Rennie

Ben Rennie is the CEO and Co-Founder of Reny, a B Corp-certified creative studio with offices in Sydney and Los Angeles. Rising to prominence over nearly two decades building the agency, he became known for pairing brand and design work for Nike, Patagonia, Chanel, Gore-Tex, and the NBA with a systemic approach to design that accounts for downstream environmental and social impact. He currently chairs Design Declares Australia, a movement repositioning design as a solution to the climate crisis, and sits on the advisory board of the Surfrider Foundation.

Rennie founded his design and strategy agency in 2009, growing it into a studio that has worked with Adidas, Canon, Westpac, Australia Post, and Tourism Australia, and more recently expanded the client roster to include community-focused work for the Utah Jazz. In 2019 he was invited to speak at Parliament House to Australia’s Prime Minister and national leaders on the role of design in public policy. He has since spoken at TEDx, SXSW, and Vivid Sydney.

His book Lessons in Creativity, published May 1, 2025, was runner-up for Australian Business Book of the Year and reached retail distribution at Barnes & Noble, Target, and Amazon in the United States, alongside WH Smith in the United Kingdom and Whitcoulls in New Zealand. The book draws on Rennie’s own career, including a period in which his agency stepped away from fossil fuel and banking clients to realign with sustainability-focused work.

As host of a Substack newsletter followed by more than 22,500 subscribers, he writes on creativity, systemic design, and the intersection of technology and human behavior.

Hey,

Thanks for reading this. I mean that. There’s a lot of content out there competing for your attention, and you spent some of it here. I hope it was worth it. Even better, I hope it prompted you to think about something differently enough that you’d share it with someone who’d get something out of it too.

I started this podcast because tactics never stuck with me. What stuck were stories — business biographies, autobiographies, the decisions people made and why they made them. The principle only clicks once you know the story behind it.

So I built the thing I wanted to listen to. Every week I have two conversations with people who build in technology and product. Then I write the essay in my premium newsletter (Taste Maker) to distill the principles and reflect on the narrative — one that puts you inside the conversation, through my eyes. What caught me off guard. What I kept thinking about after we hung up. Where the principle actually lives once you strip away the jargon.

I make this for myself first. If you read the way I do, you’ll want it too.

PS — If you want to pitch coming on the show, or you know someone I should talk to, shoot me an email at caden@hey.com with "January752" in the subject line so it gets past my filters. I'm not optimizing for famous guests. I'm optimizing for interesting conversations, even from people who aren't LinkedIn influencers.

Listen to this episode on Spotify or Apple Podcasts

About twenty minutes into the call, Logan Yonavjak does something that, in retrospect, was the whole conversation in a single move. She diagnoses Steve Jobs.

I have spent the last few minutes walking her through the wilderness years — the part of Jobs’s story that the more careful biographies have only recently learned how to handle. Becoming Steve Jobs. Creative Selection. A new book about his twelve years between getting kicked out of Apple at thirty and returning at forty-two. The Macintosh ahead of its time and commercially a failure. NeXT bleeding tens of millions until they killed the hardware division and kept the operating system. Pixar before anyone had figured out the movie business. A one-hit wonder in his thirties, by most fair readings. A man burning through other people’s money on two companies that were going nowhere.

Then Logan, who has spent the prior quarter of an hour explaining the constructs her platform measures, offers this:

“Steve Jobs’ case, I’m inferring from what I’ve heard about him that he maybe wasn’t as relationally intelligent as he was cognitively sophisticated or good at holding systems in his mind. So he would’ve probably scored high on the strategic complexity piece, which is one of our constructs, but lower on the relational intelligence.”

That sentence is the whole platform doing what it does, performed live on a famous case. The Readiness Engine, which Logan and her co-founder Benji Whitehurst built to score founders along six developmental dimensions drawn from adult developmental psychology, just took the most-written-about technology executive of the last fifty years and named the gap. Two construct scores, one diagnostic. The kind of read that, in the era when this work was being done by hand, took a trained scorer hours and a transcript. Logan does it in a sentence, and the sentence sounds correct.

This is the thing The Readiness Engine measures, and it is the thing about leadership that most companies still try to assess by gut. The six constructs that her research team pulled from adult developmental psychology — chosen because they correlate with positive startup outcomes like follow-on rounds and exits — are things like strategic complexity, relational intelligence, emotional resilience, and identity flexibility. That last one is the construct she reaches for when someone else might say coachability. People who score lower on identity flexibility are more wedded to who they currently are. They take feedback as a referendum on themselves rather than as a data point about the work. The platform reads it in their language. Not in what they say about their leadership style on a forced-choice assessment that anyone can game by asking an LLM how an INTJ would answer. In how they actually talk through a forty-five-minute scenario interview. In what they reach for when the questions don’t have right answers.

The kicker is the negative space. Logan’s platform doesn’t just analyze what someone says. It analyzes what’s missing. If you’re hiring for a sales role and across forty-five minutes of conversation about how this candidate handles difficult clients, the word empathy never surfaces — or any concept adjacent to putting themselves in another person’s shoes — that absence is the evaluation. It’s not a judgment. It’s a flag. The person didn’t talk about the thing the role most needs. A consultant could do this in 2010, charging by the hour, and a few of them could do it well. The platform does it across a thousand candidates at the cost of an API call.

I ask her about a case she has actually seen, because it is one thing to score Steve Jobs from across the historical record and another thing to score someone whose company you are trying to scale. She tells me about a founder her platform diagnosed who would have screened well on every traditional measure. He was relationally adept. He built teams that felt safe. People on his team told him hard things, which is harder to engineer than most CEOs will admit. He should have been, by the conventional reading, a model leader.

The platform said something else. Specifically, it said that he lingered too long in the feedback-collection phase. He could absorb data from his team beautifully, and then he could not turn that data into a pivotable decision. The harmony bias — the worry about hurting feelings, the wanting everyone to feel heard — became gravity. He couldn’t get out of it fast enough for a startup that needed to move.

Here is the prescription she gave him, and it is the part I want to dwell on, because it inverts the move most coaching engagements will sell you. She didn’t tell him to round out his weakness. She told him to find a person, fast, who would sit next to him and push him into faster decisions. The harmony bias didn’t get coached out. It got complemented in. The fix wasn’t an intervention; it was an org-chart change. Get a faster operator in the seat next to you, give them the authority to break the listening loop when it has gone on long enough, and let your own complementary strength do its work without dragging the company down with it.

This is where the conversation found its through-line, because it is also the thing the Jobs biographies have been working out for the last decade. The version of Jobs who came back to Apple in 1997 didn’t show up alone. He showed up empowering Jony Ive, who supplied the design taste, and Tony Fadell, who supplied the consumer-hardware instinct, and Ed Catmull, who had been quietly teaching Jobs about management at Pixar for years and who Jobs later said had taught him more about leading creative teams than anyone else. The myth of the singular genius collapses into the more interesting story the moment you start counting the seats around the conference room.

This is also where Logan goes after the myth directly, and I should say I had not expected her to.

“We have this myth in our society of the individuals,” she says. “A lot of the authors that I’ve read that kind of like hinge on this is Ayn Rand. This idea that there are these individually brilliant humans who can solve all the problems on their own and don’t really require team members to succeed. We just live in a very individualistic culture in the US, so we think we have to take it on all by ourselves and solve all the problems alone. I think this is pointing to the fact that you might just not have all of those — we call them constructs — in place. But that’s okay, because if you have the right team members, you can be very successful.”

She is talking about the platform but she is also talking about the country. The lone-genius story is what made the Jobs myth possible in the first place — the genius who terrorized his way to brilliance, who saw what no one else could see, who needed only obedience from the people around him. That story made for a great founder myth. It also predicted, almost perfectly, the version of Jobs who would get kicked out at thirty. The version who came back was the one who had learned to do the opposite — to do the demos for the team rather than make the team perform for him, to give people like Jony and Tony the creative control and treat his own job as the work of making them better.

I should disclose something here, because the essay would be dishonest without it. I am the kind of reader who will read five different biographies of the same person to get past the first one’s mythology. I have done it with Jobs. I have done it with a few others. The thing you find, every time, is the same thing Logan’s framework is reading: the singular brilliance does not produce sustained organizations on its own. The brilliance plus the team complement produces them. The biographies disagree about almost everything except this, and even the ones that want to sell you the lone genius end up, eventually, naming the team. Ed Catmull’s name appears in every honest accounting of why Apple became Apple after 1997. The myth is the marketing. The team is the company.

The Readiness Engine, in this telling, is not really an AI story. It is an old idea — adult developmental psychology has been mapping these levels for decades, and the human-scored transcript work has been going on for years — that became cheap enough to deploy at scale. What used to take a trained scorer days now takes minutes, and what used to cost a consulting engagement now sits inside the hiring stack. The constructs were always there to be measured. The cost of measuring them is what changed.

What it gives you, when it works, is not a judgment. It is a vocabulary. You can look at the founder who is lingering in the feedback loop and name what the gap is — identity flexibility, or the way strategic complexity gets translated into action, or emotional resilience under decision pressure — and you can decide whether to coach for it, or to wait for it to develop naturally over the decadal cycles Logan says these capacities tend to move on, or to hire around it. Often the answer is the third, because the third is the fastest. The other two are not wrong. They are just slower than the company needs.

There is an analogy I tried out on her a few minutes earlier in the call, about muscle-tearing. Strength comes from tearing the muscle and rebuilding it stronger. Emotional maturity, the analogy went, comes from tearing the ego the same way — putting it under enough stress that flight-or-fight stops being your default response to critical feedback, extracting the self from the work so the work can be evaluated honestly. Logan picked it up and ran with it. Most resistance to change, she said, comes from the emotional body. Resistance comes up before change happens, for everybody. The people who have built systems around themselves — a cohort of trusted critics, a coaching practice, a breathing exercise, a meeting ritual where work gets torn apart by peers — are not the people who don’t feel that resistance. They are the people who have gotten used to feeling it, and who know that the resistance is the sign that the change is about to be possible.

The Readiness Engine measures, among its six constructs, whether the person opposite the camera has built those systems. Whether they describe a feedback ritual that actually exists in their week. Whether they reach for the language of growth or the language of defense. Whether, when asked an open-ended question about a hard scenario, they name what they don’t know or perform confidence they haven’t earned. The negative space tells you. The platform reads the negative space at scale. The consultant who used to do this work charged hundreds of dollars an hour to do it once. The platform can do it across an entire org and tell you where the fixed mindsets cluster, which is almost always — Logan said this almost as an aside — at the top.

That part is structural. A fixed-mindset CEO produces a fixed-mindset org. The defensiveness flows down the chart because the people who report to the CEO learn very quickly which version of themselves to bring to the room. The leaders most allergic to feedback are, in Logan’s data, the leaders whose companies most need to change. They are also, almost by definition, the leaders least likely to commission an assessment that might say so. There is an irony there that her platform sits inside but cannot really resolve, except by being commissioned by the next layer up — the board, the PE firm, the growth-equity investor — who has the standing to ask.

When we sign off, what stays with me is not the Jobs diagnosis. It is the founder with the harmony bias, whose prescription was a person rather than a plan. The most generous reading of leadership coaching, even at its best, is that it tries to grow what is not yet there. Logan’s reading, hardened by twenty years of watching capital flow toward companies whose leadership did or didn’t survive contact with growth, is more specific and less polite. Often the gap isn’t yours to close. Often the gap is somebody else’s strength. The work, then, is naming it precisely enough to know who that somebody is.

Six numbers. One Steve Jobs question, asked across forty years of biography and answered, finally, in a vocabulary that tells you what to do.

Guest Bio: Logan Yonavjak

Logan Yonavjak is the Co-Founder and CEO of Readiness Engine, a leadership analytics platform that applies adult developmental psychology and AI to measure the inner operating system of founders and executives. Rising to prominence in the mid-2020s, she became known for bringing rigorous behavioral science to a problem historically left to gut instinct — evaluating whether a leader will perform when complexity and pressure peak. At Readiness Engine, she and co-founder Benji Whitehurst built a platform that assesses six psychological constructs correlated with positive startup outcomes, using transcript analysis of video interviews and existing meeting recordings rather than easily-gamed forced-choice assessments.

Previously, Yonavjak spent nearly two decades directing capital toward impact-driven companies as an investor and sell-side advisor, channeling hundreds of millions of dollars into natural capital, agtech, foodtech, and conservation infrastructure. She co-founded a sell-side advisory firm in that era, advising on capital raises and go-to-market strategy for high-growth impact businesses. Her FINRA Series 63, 65, and SIE certifications — earned in 2021 — reflect the formal finance infrastructure she built beneath that work.

Her academic foundation spans two graduate degrees from Yale: an MBA in Asset Management from Yale School of Management and a Master of Forestry, supplemented by a BA from UNC Chapel Hill. At Yale, she co-founded the Responsible Investing Group, the Low Carbon Business Plan Case Competition, and Restituo Advisors — a student venture focused on low-carbon ETF development — demonstrating an early pattern of institution-building alongside technical study.

As a contributor to Impact Entrepreneur and author of more than eleven publications on environmental finance and conservation investing, she has long worked to translate complex capital allocation frameworks into actionable guidance for practitioners building businesses where financial returns and positive impact are inseparable goals.

Hey,

Thanks for reading this. I mean that. There’s a lot of content out there competing for your attention, and you spent some of it here. I hope it was worth it. Even better, I hope it prompted you to think about something differently enough that you’d share it with someone who’d get something out of it too.

I started this podcast because tactics never stuck with me. What stuck were stories — business biographies, autobiographies, the decisions people made and why they made them. The principle only clicks once you know the story behind it.

So I built the thing I wanted to listen to. Every week I have two conversations with people who build in technology and product. Then I write the essay in my premium newsletter (Taste Maker) to distill the principles and reflect on the narrative — one that puts you inside the conversation, through my eyes. What caught me off guard. What I kept thinking about after we hung up. Where the principle actually lives once you strip away the jargon.

I make this for myself first. If you read the way I do, you’ll want it too.

PS — If you want to pitch coming on the show, or you know someone I should talk to, shoot me an email at caden@hey.com with "January752" in the subject line so it gets past my filters. I'm not optimizing for famous guests. I'm optimizing for interesting conversations, even from people who aren't LinkedIn influencers.

Listen to this episode on Spotify or Apple Podcasts

Rob Walling has invested in 211 SaaS companies, runs MicroConf, and sold Drip in 2016 without ever taking venture money. His 1-9-90 rule says only 1% of startups should raise VC — and that the rest of us have been brainwashed by what he calls the venture industrial complex. He includes himself in the brainwashed.

Rob Walling is saying no, and he is not saying it once. He lines the noes up, one after another, the way you wave off a stack of bad ideas being slid across a table at you.

“It’s like, no, no, no, no, no,” he says.

What he is refusing is a story. The story goes like this: you have an idea for a software company, so you raise money, and you try to become Uber, and then you try to become Facebook, and if you do not clear that bar you have failed. Rob has spent twenty-five years and six companies demonstrating that the story is optional, and he still cannot quite get over how many people accept it as physics.

“This bullshit narrative,” he calls it, “that everybody who does a startup has to raise funding. It’s just not true.”

He has a rule for this. He says it the way a man says a thing he has said on a hundred podcasts and still means. Of all the software startups that get born into the world, he figures about one percent should even consider raising venture capital. About nine percent should consider some other kind of funding — friends and family, an angel round, the non-venture money he runs an accelerator to provide. And the rest, the ninety percent, should bootstrap. One, nine, ninety. He can recite it in his sleep.

The number that stops me is not the ninety. It is the one.

Because I have spent my whole adult life inside an industry that behaves as if the number is closer to a hundred. I have watched roadmaps get bent toward whatever story raises the next round. I have watched a marketplace feature get greenlit not because customers wanted it but because marketplaces carry higher valuations. And I got, as I tell Rob somewhere in the middle of our conversation, red-pilled on the whole thing when all of my friends got laid off at once. I got lucky. I kept my job. But I watched a year of other people’s lives get spent chasing a valuation multiple, and I could not un-see it after that.

Rob has a longer version of the same disillusionment, and he dates it precisely.

“The venture industrial complex has brainwashed us all,” he says. “Me included, back in the early 2000s.”

That last clause is the one I keep turning over. He does not exempt himself. He is not standing outside the machine describing it to me from a clean distance — he is a former believer, someone who once assumed, like everyone around him, that the only way to build something real was to raise buckets of money and swing for a decacorn. The 1-9-90 rule is not a theory he arrived at in a business-school seminar. It is the shape of a mind that changed.

Here is the part the venture story cannot account for, the part Rob keeps returning to. There are, by his count, fifty or sixty thousand B2B SaaS companies in the world doing real revenue. Boring ones. Companies that started as an email tool or an invoicing utility or a scheduling widget and grew into businesses that pay their founders extremely well. None of them will ever be written about. None of them will trend. They are, he says, and this is the image I cannot shake afterward, like an iceberg under the water.

“If folks go to tinyseed.com slash portfolio,” he tells me, “they can see, I don’t know, there’s like boring B2B SaaS businesses that I’ve invested in. And it just gives you an idea of the types of things, the niches you can be in.”

The tip of the iceberg is the part everyone sees. The Ubers. The Facebooks. The companies that raise enough money to buy the attention. What Rob spends his days doing — through TinySeed, the accelerator he built for exactly these founders, and MicroConf, the conference he has run for the bootstrapped crowd for over a decade — is funding the part underwater. The mass of it. The businesses that do not photograph well.

Drip was one of them. It is the proof he reaches for when I ask him to make the abstract concrete, and it is worth sitting inside the story for a moment, because it is the whole argument in miniature. In 2012 Rob wanted a small email-capture widget for websites. He and his co-founder Derek Reimer built it. It did not take off. It took fourteen months of grinding — nine of them after the public launch — to reach what Rob considers strong product-market fit, and even that came only after he made a hard call on incomplete information and turned an email tool into a marketing automation platform.

What made it work was not a war chest. It was a gap. On one side sat the cheap, dumb email tools — MailChimp, AWeber, Constant Contact — none of which could automate anything. On the other side sat the expensive marketing automation platforms, the Marketos and Infusionsofts, with their four-hundred-dollars-a-month floors and their two-thousand-dollar onboardings and their annual commits. In between was a whole population of people who just wanted to pay fifty or a hundred bucks a month and not talk to a salesperson. Drip slid into that middle. No venture money required. Just a founder who had been listening long enough to hear the gap that nobody was filling.

“It wasn’t luck,” Rob says, and then, because he is honest, he immediately complicates it. “I also happened to see the gap.”

We spend a while on luck, because Rob refuses to pretend it did not matter and equally refuses to let it become the whole explanation. His framing is the cleanest I have heard. Luck, he says, is a multiplier. Not a cause — a multiplier. It scales whatever you have already built. He points at Basecamp, at Jason Fried and DHH, whom he once asked directly why the company succeeded. Their answer was luck and timing, one and two. But Rob does the arithmetic underneath the modesty. Basecamp is doing, he guesses, somewhere north of a hundred million a year. Strip the luck out entirely and you are still looking at a ten- or twenty-million-dollar business.

“It’d still be a great fucking business,” he says.

That is the sentence the venture narrative has no slot for. A great business that is merely great. A ten-million-dollar-a-year company that will never be a headline and will make its founders wealthy and free for the rest of their lives. Rob mentions, almost in passing, DHH describing how he and Fried simply split four million dollars off the bottom line at the end of a year — the kind of number you do not get to keep at a venture-backed startup, where the money belongs to the next round before it ever reaches you.

The whole time we talk, I keep thinking about opportunity cost, because that is what the venture story actually costs the ninety percent who buy it. Not just the companies that raise and fail. The ones that raise and, in doing so, agree to chase a size they never needed, on someone else’s timeline, until the thing that could have been a wonderful ten-million-dollar business gets managed into the ground reaching for a hundred. You can pull profit out of a bootstrapped company every year it exists. You can sell it someday if you want. Either way it belongs to you, and the decisions belong to you, and nobody in a board meeting gets to bend your roadmap toward a multiple.

Rob is not anti-ambition. This is the thing people miss about him. He wanted, badly, to build a multimillion-dollar business, and he did it more than once. He is anti-VC-narrative. He is against the single story that got installed in all of us — him first, back in the early 2000s — that says the raise is the beginning of the journey and the size of the raise is the measure of the ambition.

Near the end I find myself thinking about the founders he funds. The ones building something niche and unglamorous, the invoicing tool, the scheduling widget, the boring vertical SaaS nobody will ever cover. They are not failing to be Uber. They were never trying to be Uber. They are down under the surface where most of the actual water is, building businesses that will quietly make them free, and the only reason it looks like nothing is happening down there is that the part of the ocean we photograph is the tip.

Rob spends his life pointing at the water under the tip. Ninety percent of it, by his count.

Guest Bio: Rob Walling

Rob Walling is the Co-Founder of TinySeed, a year-long remote accelerator for bootstrapped and non-unicorn SaaS founders, and the Founder of MicroConf, the original community for self-funded software entrepreneurs. Rising to prominence in the mid-2000s through prolific writing and podcasting, he became one of the most recognized voices in the bootstrapped SaaS movement — widely regarded as the practical counterpoint to the venture-capital-centric startup narrative.

Previously, he co-founded Drip, an email marketing and automation platform, in 2012. Alongside co-founder Derek Reimer, he bootstrapped Drip from a small email capture utility to a full marketing automation suite, achieving strong product–market fit after 14 months of grinding and eventually reaching millions in annual recurring revenue. Drip was acquired by Leadpages in 2016, the liquidity event Rob has described as his “never have to work again” moment. Through TinySeed, which he founded with Einar Vollset, he has since funded more than 200 SaaS companies, with a reported millionaire rate of 43% across the portfolio.

His earlier career included developer-for-hire roles at a credit card company, a startup, and a consulting firm in the early 2000s, followed by a stint as a real estate investor (four properties, seven units in Los Angeles) before fully committing to bootstrapped software. His first small software win, NET Invoice — invoicing software that generated $2,000–$4,000 per month — proved the model was viable without outside funding.

As host of Startups for the Rest of Us, a weekly podcast he has published without interruption since 2010, Rob has shipped over 738 episodes and accumulated more than 15 million downloads. He is also the author of Start Small, Stay Small (2010), a foundational text for developer-entrepreneurs, and The SaaS Playbook (2023).

Hey,

Thanks for reading this. I mean that. There’s a lot of content out there competing for your attention, and you spent some of it here. I hope it was worth it. Even better, I hope it prompted you to think about something differently enough that you’d share it with someone who’d get something out of it too.

I started this podcast because tactics never stuck with me. What stuck were stories — business biographies, autobiographies, the decisions people made and why they made them. The principle only clicks once you know the story behind it.

So I built the thing I wanted to listen to. Every week I have two conversations with people who build in technology and product. Then I write the essay in my premium newsletter (Taste Maker) to distill the principles and reflect on the narrative — one that puts you inside the conversation, through my eyes. What caught me off guard. What I kept thinking about after we hung up. Where the principle actually lives once you strip away the jargon.

I make this for myself first. If you read the way I do, you’ll want it too.

PS — If you want to pitch coming on the show, or you know someone I should talk to, shoot me an email at caden@hey.com with "January752" in the subject line so it gets past my filters. I'm not optimizing for famous guests. I'm optimizing for interesting conversations, even from people who aren't LinkedIn influencers.

Listen to this episode on Spotify or Apple Podcasts

Marcelo Calbucci is describing a product manager who has done everything right, and who is about to make a mistake.

The setup is mundane on purpose. The customer wants tags. They’ve asked for tags. Ten support tickets came in this month asking for the same thing — the ability to label their files, their emails, organize them their own way. The product manager pulls the tickets together and walks into the leadership meeting with a clean story. This is important. Lots of people are asking for it. Here is the evidence.

“And you go to the leadership,” Marcelo says, half-acting the part, “and it’s like, this is so important. Lots of people are asking for it.”

He lets the picture hang there for a second, because the picture is the trap.

“The real question is like, wait a second. Why are they trying to do that? What exactly are they trying to do?”

I’ve watched a lot of product people walk into that exact meeting. I’ve been in the room for the version where the tickets win and the team ships the tags and nobody asks the second question. So I want to know what Marcelo thinks the second question reveals. He answers with the rest of the story.

“Maybe what they need is a consolidated list at the end of the month, because they have to provide a report to someone.” He pulls the thread one more turn. “And you’ll be like, wait a second. You don’t need tagging to do that.”

Marcelo Calbucci is the author of The PRFAQ Framework, the book he published in January 2025 adapting Amazon’s Working Backwards process for people who don’t have Amazon’s resources behind them. He has the résumé to make the claim land: roughly seven years at Microsoft, where he led engineering at Bing; about two years at Amazon, on a product and engineering team inside the HR organization, watching the PRFAQ machine run at full scale; six startups co-founded across Seattle and London over 18 years; more than $40 million raised across them. He wrote his first software at 12 and sold a CRM tool for MS-DOS at 16. We’re on a video call in late February, the book just out, and I’ve steered us toward the question everyone is asking him: where does AI fit in a methodology that is fundamentally about writing?

His answer is not the answer I expected from someone whose whole brand is a writing framework. It’s more useful than that. It’s a line — a border he draws straight down the middle of all the writing a person does at work, with the model on one side and the human alone on the other.

On one side: the tactical. The résumé. The pattern-based document where the shape is already known and ten thousand good examples already exist in the world. “If you’re doing things that are more tactical,” he says, “you need to write your own résumé — it doesn’t require a lot of strategy there.” Hand it to the model. It has seen more résumés than you ever will. The same goes, he says, for the tagging feature, once you’ve established that tagging is actually what’s needed. “Oh, let me research all the ten ways there are to do tagging, all the examples, all the patterns.” That is exactly the work a language model is built to do. “You’re not gonna create that much value by doing the work yourself. So you might as well leverage the LLM.”

On the other side: the strategic. And here his voice changes — not louder, just firmer, the way someone gets when they’re saying the part they actually care about.

“When you ask ChatGPT, like, create a business plan, or create a strategy for an app, or for a website, or for a podcast, whatever — you are telling AI, do the thinking for me, and just gimme the results. You are losing so much by doing that.”

I ask him to be precise about what’s being lost, because “losing so much” could mean the output is worse, and that’s not quite his claim.

It’s not about whether the idea is good, he tells me. It’s that your brain was never engaged. The plan arrives fully formed, and you skipped the part where producing it forced you to confront what you didn’t know. “The writing helps you think about what you don’t know,” he says, “and forces you to do some research to come back and finish the writing.” The model removes that friction. It does the research and the writing in one motion, and hands you a document you never had to struggle toward — which means you never found the holes, because finding the holes was the struggle.

This is the inversion at the center of how he thinks, and it took me the back half of our conversation to see how completely it reorganizes the AI question. Most people frame AI writing as a quality problem: is the output good enough? Marcelo frames it as an engagement problem. The output might be excellent. That’s not the point. The point is what happens — or doesn’t — inside the head of the person who was supposed to do the thinking.

Which is why the tagging story matters so much to him, and why he keeps the two halves of it apart. There’s the question of whether to build tagging — strategic, the kind of thing where the writing has to surface the real customer problem hiding under the stated one. And there’s the question of how to build tagging well once you’ve decided it’s right — tactical, ten patterns, hand it to the model. The PRFAQ is for the first. A PRD, the product requirements document engineers actually build from, is for the second. And the failure mode he sees everywhere is people running an LLM over the first kind of question, generating a confident plan for the wrong feature, and never noticing because the document looked so finished.

“It is very rare,” he tells me, “when you should use an LLM for most requirement docs.” He says it almost as a correction to himself, mid-thought, as if he’s surprised by how far the principle extends once he follows it honestly. The more strategic the document, the less the model should touch the core of it.

He’s careful, though, not to turn this into a prohibition. He uses AI. He’s emphatic that you can hand the model your assumptions and ask it to argue against them, ask it to surface the questions you haven’t thought of, ask it to brainstorm. “Not that you can’t use ChatGPT to ask questions and help you brainstorm certain things,” he says. “But you want to do the core of the thinking.” The model is allowed in the room. It just doesn’t get to be the one who decides what the room is for.

There’s a version of this distinction that sounds like a productivity tip — use AI for the boring stuff, do the important stuff yourself. But the longer he talks, the clearer it gets that he’s describing something closer to a discipline, and the discipline is harder than it sounds, because the model is so good and so fast that refusing it requires you to choose friction on purpose.

He gives me the harder case, the one where the line gets blurry. A premium feature — something behind a paywall, something that decides whether a user upgrades or churns. On the surface it’s just a feature, the same as tagging. But the questions underneath it are strategic ones. Are we going to lose users who feel this should be free? Where does it sit in the plan? “That is very strategical,” he says. “Because now we are talking about, hey, are we gonna lose users if they don’t pay?” His ruling: that one should have been a PRFAQ before it was ever a PRD. You do the strategic writing first — by hand, with the blank page, finding the holes — and only then do you let the model help you execute.

The work, in other words, is knowing which kind of writing you’re doing before you reach for the tool. And the temptation runs entirely one direction. Nobody is tempted to hand-write their résumé from scratch for the joy of the struggle. The temptation is always to let the model take the strategic document too, because it can, and because the result looks just as polished, and because the polish hides the fact that no one did the thinking.

I tell him this is starting to sound less like advice about AI and more like advice about character — the willingness to do the slow version when a fast version is sitting right there, indistinguishable from the outside. He doesn’t disagree. He reframes it in the language he uses for everything else.

“You’re moving from a bias to action,” he says, “to a bias to impact.”

That phrase had come up earlier in our conversation, aimed at a different target — the product manager who measures himself by how much he ships. But it lands differently here, pointed at the AI question. Bias to action is what a language model is perfectly built to serve. It will produce, instantly, on demand, a plan, a strategy, a business case, as much as you want, as fast as you can ask. It is the most powerful bias-to-action engine ever made. And that, in Marcelo’s telling, is exactly the danger. The thing that makes it irresistible is the thing that lets you skip the only part that mattered.

I keep coming back to that product manager from the start, the one with the ten tickets and the clean story. He didn’t do anything lazy. He gathered evidence, he found a pattern, he built a case. In a bias-to-action world he is a model employee. He shipped. And he shipped the wrong thing, because the writing he needed to do — the slow, strategic kind that would have forced him to ask what the customer was actually trying to accomplish — was precisely the kind a tool could have done for him in 30 seconds, leaving the real question unasked.

The tags would have worked. The feature would have shipped. The tickets would have closed. And somewhere a customer would still be exporting their tagged files by hand at the end of every month, building the report they needed all along, wondering why the thing they asked for didn’t give them the thing they wanted.

That was never the easy part. It only looked easy because a machine could do it.

Guest Bio: Marcelo Calbucci

Marcelo Calbucci is the author of The PRFAQ Framework, a six-time founder, and a seasoned CPO/CTO with 25 years in technology spanning Microsoft, Amazon, and 18 years of startup building across Seattle and London. Rising to prominence in the Seattle startup ecosystem through the 2000s and 2010s, he became known for translating enterprise innovation practices into frameworks accessible to founders and product leaders at any stage — culminating in his 2025 book adapting Amazon’s Working Backwards process for organizations of all sizes.

Previously, as a product and engineering leader at Amazon, Calbucci led a team inside the company’s HR organization, an experience that gave him a firsthand view of the PRFAQ process operating at full scale — with months-long document cycles, financial modeling, and cross-functional research teams backing major bets. Before Amazon, he spent approximately seven years at Microsoft, where he led engineering at Bing, then left to pursue 18 years of entrepreneurship, raising more than $40M across multiple startup ventures and studios in Seattle and London.

Earlier in his career, he helped build foundational institutions in the Seattle tech community, including what became the GeekWire Awards and the GeekWire 200. He currently organizes the Acquired Seattle meetup and Seattle Flow, two communities for operators and founders in the Pacific Northwest.

As the author of The PRFAQ Framework, Calbucci distills the Working Backwards methodology into a one-to-two-week process for individual contributors, startup founders, and executives who lack Amazon’s organizational infrastructure — arguing that the framework’s real value is teaching innovators to think critically about whether an idea is worth building at all.

Hey,

Thanks for reading this. I mean that. There’s a lot of content out there competing for your attention, and you spent some of it here. I hope it was worth it. Even better, I hope it prompted you to think about something differently enough that you’d share it with someone who’d get something out of it too.

I started this podcast because tactics never stuck with me. What stuck were stories — business biographies, autobiographies, the decisions people made and why they made them. The principle only clicks once you know the story behind it.

So I built the thing I wanted to listen to. Every week I have two conversations with people who build in technology and product. Then I write the essay in my premium newsletter (Taste Maker) to distill the principles and reflect on the narrative — one that puts you inside the conversation, through my eyes. What caught me off guard. What I kept thinking about after we hung up. Where the principle actually lives once you strip away the jargon.

I make this for myself first. If you read the way I do, you’ll want it too.

PS — If you want to pitch coming on the show, or you know someone I should talk to, shoot me an email at caden@hey.com with "January752" in the subject line so it gets past my filters. I'm not optimizing for famous guests. I'm optimizing for interesting conversations, even from people who aren't LinkedIn influencers.

Listen to this episode on Spotify or Apple Podcasts

Ashley Jablow spent a year inside the EPA’s Office of Pesticide Programs as a Presidential Innovation Fellow, watching paper files travel by hand and by email between people who couldn’t share a building. The innovation she remembers most clearly wasn’t a system overhaul or a policy rewrite. It was a woman at a desk who figured out she could sign a PDF and stop printing it.

Ashley Jablow is somewhere inside the Environmental Protection Agency, in the Office of Pesticide Programs, doing the unglamorous version of her job. She is running research interviews. She is asking the people who actually review the safety and efficacy of the pesticides that get used on the country’s food supply how their work moves from one person to the next. The answer, she finds, is paper. Hundreds of pages of paper. A reviewer signs a file, scans it, emails it, and the next person prints it, signs it, scans it, and sends it on. The buildings are spread out. The people inside them are dedicated. The system runs on toner.

One afternoon a woman at one of the desks calls Ashley over.

“Ashley, I wanna show you something that I’ve figured out,” the woman says.

“Please, show me what — show me your work,” Ashley says back.

“This is what I’ve figured out,” the woman says. “Instead of printing each file every time I receive it, I have figured out how to put my digital signature, my electronic signature, on this PDF, so that I don’t have to print out hundreds of pages.”

Ashley admits, when she tells me this, that her first reaction was not the right one.

“I was like, yeah, like, what’s so exciting about that?” she says. “Doesn’t everybody know how to annotate a PDF?”

I want to sit with her admission for a second, because it is the thing the essay is about. Ashley Jablow came to the EPA from IDEO. She had already spent years inside a design and innovation company so famous for its method that the word design lost a syllable when consultants said it. She had then helped run Open IDEO, the open-innovation startup that crowdsourced design challenges for social and environmental impact — a niche inside a niche inside a niche, which she could feel narrowing around her. Six weeks after she got the call accepting her to the Presidential Innovation Fellows program, she had moved her husband and her fifteen-month-old son from San Francisco to the East Coast and reported for a one-year tour of duty inside a federal agency. The fellowship was supposed to broaden her aperture. It did. She has lived in Virginia for over a decade now.

And there she was, standing over the shoulder of a public servant, looking at an annotated PDF, thinking: that’s it?

The honest answer is yes. That’s it.

She tells me what she had to unlearn to see it. At IDEO, the pace was such that she used to fantasize about a single pill that would give her every nutrient she needed at lunchtime so she would not have to stop working. Moving into government, she says, felt like stepping off the moving walkway at the airport — the involuntary lurch forward, the sense that something underneath you had stopped without warning, the long recalibrating look around. How are we ever going to get anything done at this pace? she remembers thinking.

The other thing she had to unlearn was the front page. In the private sector, the front page of the newspaper is the prize — let’s have some wins, let’s share them, let’s blow up our launch metrics in public. Inside the government, the front page is the failure condition. If you are on it, something has gone wrong with public money. She names it without preamble: in the public sector, the goal is to avoid being on the front page, and that is the gravitational field every person around her was working inside. Conservatism is not a personality trait there. It is the structure of the building.

I’m not going to flatten this into a clean Silicon-Valley-bad, government-good fable, because Ashley does not, and the woman at the desk would not. The point of the digital signature is not that government is virtuous. The point is that, inside that incentive structure, the innovation that survived was the one she could prove was harmless. No press release. No keynote. A reviewer figured out that the Sign tool in Acrobat existed, and the cascade of printers downstream went quiet by however much paper one workflow accounted for. The frontier of innovation, for that office, was an annotation menu nobody had bothered to open.

I ask Ashley to tell me what the word innovation even means to her after a year of looking at things like that, and she goes to the Latin.

“The Latin root of the word innovation means change,” she says. “Means to begin again, to renew.”

Then, almost as an afterthought: change is actually everywhere. It’s a constant. The seasons change. Babies learn to walk. We get older. Change is quite neutral when you think about it out in nature. Innovation, on her reading, is a fancy borrowed word for the most ordinary thing in the world. It is not novelty. It is not flash. It is not the front page. It is the act, performed honestly inside a constraint, of beginning again.

This is where I have to disclose something, because the essay would be dishonest without it. I’d spent the first part of our call indulging a long tangent about K-Pop Demon Hunters — the way the animation studio behind Spider-Verse sweated the pre-production until the story landed; the way Sony quietly sold the film to Netflix for a fraction of what it later earned; the way Ted Sarandos called it Netflix’s Frozen. I was using it as a stand-in for stewardship. Care about the narrative, I was saying, and the audience shows up. Skip the narrative, green-light the IP because you bought it, and the audience does not. Ashley listened. She let me finish. And then she did something that was, in retrospect, the entire move of the conversation: she pulled the example back to the EPA woman. The studio in Los Angeles and the reviewer at the EPA were doing the same thing, just on different stages. They were performing the unglamorous work and not skipping it.

It struck me, late, that the reason her example was easier to dismiss than mine was that hers did not flatter the listener. There is no founder myth at the end of a digital signature. There is no Netflix chart. There is only the next file, signed without printing, passed to the next person. The cost compounds invisibly. The savings compounds invisibly. The work is the same.

This is the part where, on most podcast calls, the guest would pivot to a framework. Ashley does not. She tells me, instead, about being an imposter at IDEO. I remember spending my time at IDEO honestly like such an imposter, she says — there was so much to learn, there was a lot of jargon, there was a kind of black box process she was trying to learn on the job. She left, did the EPA year, and only then, metabolizing what she had learned, came to the realization that it was quite simple. There was, she says, an awful lot of peacocking around the word. Shiny and bright and innovation, this hallowed space. The reality was always more ordinary: figure out what people want, what they will use, what they’re struggling with. Imagine some possibilities. Try the smallest, fastest, cheapest thing you can try right now to learn the most.

It is not rocket science. It is not brain surgery.

The way she puts the prototype piece is the line I keep replaying. One of the leaders at IDEO, when she was still there, told her that a prototype is a prop that tells a story. The prop is what you bring to a research session to ask: how do you think you might use this? Where do you see it breaking? Tell me the story of that. The digital signature, in that frame, was already a prototype. The reviewer at the EPA was already a designer. She just had not been peacocked at long enough to know what to call herself.

Late in the call I make the mistake — the useful kind — of asking Ashley how she would coach somebody whose candor cuts the people around them. I am thinking, when I ask, about Steve Jobs in his exile years. I am also thinking, transparently, about myself, because I have been candid to the point of making people feel small, and I have not entirely figured out how to stop. Ashley does not answer the question I asked. She answers a better one.

She turns the lens on the relationship.

Let’s say I have a value of predictability, she says. I like structure, I like order, I like a plan. And let’s say, Caden, you have a value of spontaneity, the creative process, that aha moment.

Neither of those values is right or wrong. Neither is the smart one. We are assigned to work on a project together. We have six weeks. She is going to walk into the first meeting and say: what is our plan, what is our schedule, what are our midpoints? I am going to walk into that meeting and say: I need some openness, some time and space, to let it come to me. We are going to have conflict, she says, not because either of us is unprofessional but because we are approaching the same problem from different values, and we have forgotten to name the values out loud.

I should be clear about what just happened. She was not running an exercise. She was reading me. I do not like giving estimates I have not earned the right to give. I do, in fact, ask for two weeks of exploration before I will commit to a number. I do, in fact, lurch when the calendar is the only thing in the room. She named my actual operating system using the example, and she did it without making me feel small.

This, I realize later, was the actual demonstration of the coaching skill she had just been describing. The hardest part of learning to lead, she quotes the coach Jerry Colonna, is learning to lead yourself. She does not say it about me. She says it about Steve Jobs. But she put it in the air between us, and then she modeled the same thing she was naming. The being and the doing. How you show up next to a person, before you ask the person to do anything.

Soft skills, the cliché says, are the soft stuff. Hard results are the hard stuff. Ashley spent the call quietly inverting that. The reason a P&L lands at the end of a quarter is that, six weeks earlier, two people with different values walked into the same room and agreed on how to work together. The reason a pesticide review actually moves through the building is that a reviewer at a desk decides, on her own, to stop printing. The reason a film is good is that someone sweated the script while the calendar said ship.

The work, in every one of those frames, is the same. It is small. It is specific. It is operational. It is the thing you can do today inside the constraint you are inside. You can call it innovation if you like. The Latin word means to begin again, which is what the woman at the EPA was doing, file by file, while the front page elsewhere belonged to the people who did not have to.

I think about her, after the call. The reviewer Ashley still remembers. Whoever she is, she is presumably still at her desk somewhere, signing pesticide files. She is not on the front page. The work, by definition, has not been on the front page. Pages that did not need to be printed do not show up in any news cycle.

They show up, instead, in the absence of themselves. In a printer that did not run. In a toner cartridge that did not get replaced. In a paragraph at the end of a podcast about a woman whose name nobody learned, whose change everybody benefits from, whose innovation Ashley Jablow can still describe twelve years later as the one that mattered.

That is the front page Ashley spent a year learning to read.

Guest Bio: Ashley Jablow

Ashley Jablow is the Founder and Principal of Wayfinders Collective and creator of Life Design School, a creative studio dedicated to helping leaders and professionals redesign their work and lives with human-centered intention. Rising to prominence in the 2010s through her work at the intersection of design thinking, civic innovation, and leadership development, she became known for translating the methods of the world’s leading design consultancies into practical frameworks for individuals and organizations navigating change. Since founding Wayfinders Collective in 2017, she has accumulated 500-plus hours of coach training through the Coaches Training Institute and built a practice spanning executive coaching, organizational facilitation, and on-demand learning resources.

Previously, as a Presidential Innovation Fellow in the Obama Administration, she embedded with federal agencies to bring human-centered design methods into government — most notably at the Environmental Protection Agency, where she studied workflow bottlenecks in the Office of Pesticide Programs, and at the National Archives, where she led open design of technology for citizen access to historical records. The fellowship, originally a one-year commitment, permanently relocated her family from San Francisco to Virginia. She subsequently served as Vice President of Development & Impact at Vizzuality, a Spanish data visualization and design firm, where she was their first U.S. hire and launched the company’s inaugural American office.

Earlier in her career, she joined IDEO as the first full-time hire on the OpenIDEO platform, a global crowdsourcing initiative running online design challenges for social and environmental impact. She holds a BA in Sociology and Spanish from the University of Michigan and an MBA in Marketing and Corporate Responsibility from Boston University.

As creator of The Clarity Kit, a free 30-minute on-demand workshop available at lifedesignschool.co, she helps participants identify the core problem they need to solve before entering solution mode — applying the same diagnostic rigor she developed across IDEO, government, and consulting to the challenge of personal reinvention.

Hey,

Thanks for reading this. I mean that. There’s a lot of content out there competing for your attention, and you spent some of it here. I hope it was worth it. Even better, I hope it prompted you to think about something differently enough that you’d share it with someone who’d get something out of it too.

I started this podcast because tactics never stuck with me. What stuck were stories — business biographies, autobiographies, the decisions people made and why they made them. The principle only clicks once you know the story behind it.

So I built the thing I wanted to listen to. Every week I have two conversations with people who build in technology and product. Then I write the essay in my premium newsletter (Taste Maker) to distill the principles and reflect on the narrative — one that puts you inside the conversation, through my eyes. What caught me off guard. What I kept thinking about after we hung up. Where the principle actually lives once you strip away the jargon.

I make this for myself first. If you read the way I do, you’ll want it too.

PS — If you want to pitch coming on the show, or you know someone I should talk to, shoot me an email at caden@hey.com with "January752" in the subject line so it gets past my filters. I'm not optimizing for famous guests. I'm optimizing for interesting conversations, even from people who aren't LinkedIn influencers.

Listen to this episode on Spotify or Apple Podcasts

They removed the timer from a recording app. They added balloons, then quadrupled her rate from $400 a month to $1,800. Molly walked — and used the story to explain something I’ve been circling for years: most product roadmaps are written for the board, not the customer.

Molly is twenty minutes into a story about a phone call she had with Riverside, the video-recording software her podcast agency was using to record clients. She is not laughing. She is doing the slightly-controlled-anger voice of someone who has had to say the same obvious thing in three different meetings.

“You are killing my cost, man,” she tells me she told them. “You are killing my cost of goods sold.”

She is in Costa Rica. I am in Utah. There is a kind of dry, transactional warmth in how she lays it out, the way someone who runs an actual business talks about a vendor who doesn’t run one. Molly owns Heartcast Media — twenty-five years in multimedia, the company that produces over a thousand podcast episodes for clients who include the Department of Health, NATO, and a long list of CEOs who hire her specifically so that they don’t have to think about microphones. She knows what an agency needs from a recording tool. She knows what an agency does not need.

What an agency does not need, she tells me, is balloons.

“They added balloons. They added all this crap that no agency is ever going to use, and then they turned around and said, ‘We’re going to change your rate from four hundred a month to eighteen hundred a month because now you have emojis and balloons, and you can make magic clips.’”

The list itself is the joke — emojis, balloons, magic clips, four times the price — and she delivers it flat, the way you read a receipt out loud. She is still annoyed about it years later. You can tell because she still remembers the exact dollar figures.

“They took the timer off for two and a half months a couple years ago,” she says. “I’m like, this is literally the very backbone of a recording is the timer.”

A timer. The one piece of an interface that tells the agency producer how long the conversation has been running, so they can pace it, cut to break, know when to wrap. Riverside removed it. For two and a half months. Then they came back with the new pricing.

“Like, tell me you don’t know anything about recording,” Molly says, “without telling me you don’t know anything about recording.”

I think about this line for the rest of our conversation. It is doing two things at once. It is making fun of a meme-shaped sentence — Molly knows exactly which corner of the internet she is borrowing from — and it is making a precise accusation. The people who built the product had stopped using the product. Or had never used it. Or had used it once, in a demo, and gone back to building features they could put in a Friday email so investors would feel motion.

“I’m an agency,” Molly says she told them. “We use Adobe. I’m never going to use your shitty editor, and I’m never going to give you eighteen hundred a month.”

So she didn’t. She left for a few years. She kept paying Zoom about five hundred a month instead, which she also thought was too much, but at least Zoom was not pretending to be something it wasn’t. Riverside lost her account. They lost six thousand dollars a year off one customer.

“And it’s easy to do that in any business,” she says. “Especially with AI. You’re like, oh, I can do all these things. But if you can’t do it consistently, if you can’t create a system around it, and if it doesn’t have any real value, then you’re just cluttering the inbox and you’re training people, including your clients, to ignore you.”

Training people, including your clients, to ignore you.

The pattern she’s describing isn’t unique to Riverside. I have watched a version of this play out at every venture-backed software company I’ve ever worked near.

There is a roadmap and the roadmap has features on it, and the features have shipping dates, and the shipping dates correspond to board meetings or all-hands or fundraises. The shape of the calendar dictates the shape of the product. Someone, at some point, decided that the answer to “how do we charge more” was “ship more,” and “ship more” became its own moral category. It stopped being a means and became the work itself.

I told Molly I think of myself as the “anti-product-management product manager”. That is the only way I know how to describe what I do. I run a product builder podcast, I have done product management along with design for years, and the thing I keep arguing with my own profession about is exactly this — the gap between making plans for teams and actually delivering value to a person who is going to write a check.

“It was probably some PM,” I say, “that thought, hey, we could justify charging them more if we just add more features, rather than worrying about value, like making a more reliable tool.”

There is a thing that happens inside companies where shipping becomes performance, and the performance is mostly for investors. You need something to tell at the next board meeting. Pointing at revenue is hard because revenue is slow and full of caveats. Pointing at features is easy. The features compound visually on a slide. The features sound like motion.

The customer, in this performance, is a kind of background actor. They appear in the dashboard as a churn number. They do not appear as Molly, on a call, telling you that you have killed her cost of goods sold.

This is the thing I want to fix and don’t know how to.

Molly’s story sits inside a larger argument she has been making for the full episode, which is about positioning. She runs Heartcast Media with what she calls singular clarity — podcast production as a business development tool, podcast booking, podcast growth, period. That is the sentence. It does not change. She has owned a company before, called One Love Massive, that supported community through art, music, and culture. Nineteen employees. A hundred and sixty artists. A three-story building in DC. And every week in the staff meeting she would have everyone do the elevator pitch, and nobody could agree on what they actually sold. She tells that story like a person who has paid the tuition. She’s not running that company anymore.

Heartcast is the second version. Heartcast is the company she built after she learned what it costs to be unclear.

So when she watches Riverside lose her account because they added emojis and balloons, what she is watching is the same lesson she paid for at One Love Massive, except this time it is someone else’s lesson and the someone else is the kind of company that gets covered in tech press. She is in the position of the seasoned business owner watching the unseasoned business owner make the obvious mistake. She is not surprised. She is annoyed.

“I’d say like, you guys gotta put yourself in the seat of the user,” she tells me she told the Riverside executives, after she escalated up the corporate line and got into one of their meetings. “You jumped the shark, man, big time.”

I keep thinking about that meeting. Molly, a paying customer with a six-thousand-dollar-a-year contract on a service that is supposed to be the core infrastructure of her agency, getting into a room with the executives and telling them they jumped the shark. I want to know what the executives were thinking during that meeting. I want to know if the PM was in the room. I want to know which of the people in that meeting was the one who shipped balloons.

I don’t actually know if Riverside is doing well now. Molly mentioned that they reportedly made ten million dollars in a year, plus another ten from an investor — the math of the venture funnel adds up even when the customers are angry. Riverside might be fine. Zoom might be fine. The companies that ship the wrong things often are fine, in the short run, because the financial mechanisms that fund them are not actually tied to whether the customers like the product. They are tied to whether the next round can be raised.

But the customer is keeping a ledger. Molly is the customer. Her ledger has a line on it that says six thousand a year, gone for years, because someone added balloons.

The thing about positioning, the thing Molly keeps trying to teach me across this conversation, is that the customer’s ledger is the only ledger that matters in the long run. You can perform velocity for the board for a few quarters. You can press-release your way through a fundraise. You can put balloons on the recording app and sell that as innovation. But the customers are forming opinions about you, in their own internal accounting, and those opinions calcify into reputation, and reputation is what makes the phone ring.

Or doesn’t.

“And I think that they hurt their reputation a lot,” she says, almost as an afterthought, “because it’s like you’re working for the investors, you’re not working for the people.”

She says it the same way she said the rest of it — without drama, the way you describe the weather. The way someone who has been doing this for twenty-five years describes a pattern she has seen before and will see again.

Six thousand dollars a year. One customer. One feature decision.

That’s the receipt.

Guest Bio: Molly Ruland

Molly Ruland is the CEO and Founder of Heartcast Media, a full-service podcast production studio she established in Washington, D.C. in 2018. Rising to prominence in the late 2010s as the demand for branded B2B podcasting accelerated, she became known for repositioning podcast production as a direct business development tool — not a media vanity project — for brands, NGOs, and founders seeking high-trust relationships with ideal clients. Under her leadership, Heartcast Media has produced more than 1,000 podcast episodes, including 7 programs that rank in the top 10% globally, with clients spanning the U.S. Department of Health, DC Government, NATO, and a range of entrepreneurs.

Previously, Ruland spent approximately 20 years running One Love Massive, a multi-sensory creative platform she built in Washington, D.C. that supported community through art, music, and culture. At its peak the operation employed 19 staff, managed 160 artists, and operated out of a three-story building — an experience that sharpened her understanding of brand clarity and the operational cost of an undefined offer. She credits One Love Massive with the hard lessons behind Heartcast Media’s singular positioning: podcast production as a business development and lead generation engine, period.

In 2026, Ruland co-authored Speak Your Way to Sales alongside nine other women entrepreneurs, a book focused on generating revenue through speaking, podcasting, and guesting. The title debuted at number one in Amazon’s small business category. She also hosts her own content marketing podcast and maintains a separate political interview series as a passion project.

Hey,

Thanks for reading this. I mean that. There’s a lot of content out there competing for your attention, and you spent some of it here. I hope it was worth it. Even better, I hope it prompted you to think about something differently enough that you’d share it with someone who’d get something out of it too.

I started this podcast because tactics never stuck with me. What stuck were stories — business biographies, autobiographies, the decisions people made and why they made them. The principle only clicks once you know the story behind it.

So I built the thing I wanted to listen to. Every week I have two conversations with people who build in technology and product. Then I write the essay in my premium newsletter (Taste Maker) to distill the principles and reflect on the narrative — one that puts you inside the conversation, through my eyes. What caught me off guard. What I kept thinking about after we hung up. Where the principle actually lives once you strip away the jargon.

I make this for myself first. If you read the way I do, you’ll want it too.

PS — If you want to pitch coming on the show, or you know someone I should talk to, shoot me an email at caden@hey.com with "January752" in the subject line so it gets past my filters. I'm not optimizing for famous guests. I'm optimizing for interesting conversations, even from people who aren't LinkedIn influencers.

Listen to this episode on Spotify or Apple Podcasts

In January 2025, Marcelo Calbucci sat down to write a PRFAQ for a new investment vehicle he was thinking of starting. By the end of the document, he had decided not to start it. The author of The PRFAQ Framework — six-time founder, ex-Amazon, ex-Microsoft — walks me through what writing forces you to see that a pitch deck never does.

“Let me say something that might surprise you,” Marcelo Calbucci tells me.

We are an hour into a conversation about a book he spent a year writing, and he says it the way a man lays a card face-up on the table — without flourish, watching to see what I do with it. “Most PRFAQs lead to a no-go decision.”

I should explain what a PRFAQ is, because the name does it no favors. It is the document at the center of Amazon’s Working Backwards process: a press release for a product that does not exist yet, followed by a long list of frequently asked questions about it. You write the thing as if it has already shipped, and then you interrogate it. Marcelo spent two years inside Amazon watching this process run at full weight — months of writing and review for a single bet, financial modeling, user research, the whole apparatus — and then he left and wrote a book adapting it for the people who never get that apparatus: founders, designers, product managers at companies with no research team to lean on.

So when the author of the book tells me that most of the documents the book teaches you to write should end in no, I do the thing I suspect he wants me to do. I push back. That sounds like failure. You do weeks of work, and the deliverable is that you don’t build the thing?

He has heard this before. I can tell because he doesn’t reach for theory. He reaches for himself.

“This is very personal,” he says. Last January, he sat down to write a PRFAQ for something he genuinely wanted: a new investment vehicle for founders. Not a thought experiment. A real next move for a man who has started six companies and raised more than forty million dollars doing it. He knew the shape of the thing. He could have built a pitch deck for it in an afternoon and felt good walking out of the room.

Instead he opened a blank document and started writing the press release for it — the announcement he’d make if the thing already existed and had already worked. Then the questions underneath it, the ones his own framework forces: who is the customer, whether the problem he was so sure existed actually existed or just felt like it did, how the people he wanted to serve were already solving it without him. Each answer he was confident about sent him to go check, and the checking sent him back to the document less confident than he’d started, and somewhere in that loop the thing began doing what he wrote an entire book about. It started talking back.

This is the part outsiders never see about a man with his record — six companies founded, more than forty million dollars raised across them, eighteen years spent deciding what to build and convincing other people to fund it. You would assume that by now the deciding gets easier, that a founder six times over walks into his seventh idea with the confidence of someone who has been right before. What he was describing instead was a person voluntarily sitting down with the one tool guaranteed to make a good idea harder to keep believing in. He did not have to write the document. Nobody was making him. He wrote it because he has learned not to trust an idea he has not yet tried to talk himself out of.

I want to know what it said. I want to know whether a man who has done this six times can really sit in a room with his own idea and let a Word file argue him out of it, or whether that is the kind of thing you say in an interview and not the kind of thing that happens at a kitchen table in January.

He pauses on the word realized, like he is deciding how honest to be about what came next.

What he decided that month — and the reframe he handed me when I called it a waste — is the part of the conversation I have been turning over since we hung up.

What this profile covers

1. What that document did to a founder who has been right six times before — and the reframe he handed me when I called the whole exercise a waste. The shift he names is small, a single change in what you choose to measure, and he uses it to separate the product managers who last from the ones who burn out. Once he said it, I could not unsee how much of product work is built to reward the wrong number.

2. Why the process can’t simply be lifted out of Amazon and dropped into your company — the part of his book that got ahead of every objection I came in with. It starts with a sixty-minute meeting that opens with twenty minutes of total silence, and it ends somewhere uncomfortable for anyone who has ever said “let’s just do it the way Apple does it.”

3. And the line he draws through the middle of 2026’s most tempting shortcut: what you can hand to an AI to write, and what you must refuse to. The example that makes it concrete is the most boring feature request in software — a customer asking for tags — and what Marcelo does with it is the whole argument for why the thinking is still yours.

Read more

Listen to this episode on Spotify or Apple Podcasts

Drew Bridewell spent years at LinkedIn and Facebook with no access to the P&L, then watched AI dissolve both the cost of learning the finances and the cost of the design-system maintenance that used to eat the time he would have needed to learn them. What’s left is the thing only designers can do: visualize what doesn’t yet exist with enough specificity that other people see it, align around it, and believe in it.

About a third of the way into our call, Drew Bridewell catches himself mid-thought and reframes the word he’s been using for his job.

“I’ve really shifted into, like, this operator language,” he says, “because as an operator for any business or any company you, you participate in, you need to understand the finances, you need to understand the economics, you need to understand how the company makes money, how they lose money, then, and then also how much it costs to have a team, how much it costs to have AI as a resource.”

He says it the way someone says a phrase they’ve grown into recently. Operator. Not designer. Not head of product & design, which is what his title at GrowthDay said for five years. Operator, with all the inheritance the word carries — that you spend somebody’s money, or you make it, or you don’t, and the people in the room know which.

The shift, when he describes it, isn’t a re-branding. It’s a diagnosis.

“All the things that I love about the, the, like, the foundations and principles of UX don’t even matter if you don’t understand how the company is supposed to operate,” he tells me. “’Cause then you can’t work backwards, you can’t figure out, like, the root of the problems. You’re just basically taking orders.”

Just basically taking orders. He doesn’t put it sharper than that, and he doesn’t have to. The whole career argument designers spent the last twenty years making — that craft matters, that thinking matters, that we should be in the room where the product decisions get made — collapses in front of that sentence. The room was never refusing the craft. The room was refusing the conversation that happens in the language of dollars, and the craft, on its own, couldn’t get there.

I came up through this argument from the other side. I have a human-computer interaction degree. I was a UX-pilled graduate of my design school in the era when companies hired UI talent, not UX talent — when the market rewarded the people who could ship the prettiest screen, not the people who could explain why the screen should exist. I watched designers fight, decade after decade, for the seat. The fight was real and the seat is real. What I underestimated was how much the seat was always financial.

Drew makes it concrete with where he learned it.

“I learned it more as I got further and further away from big tech,” he says. “Because, you know, at, like, LinkedIn and Facebook, I’m not, I wasn’t, like, getting, um... I, I didn’t have access to the, the P&L of those massive companies, but I definitely, you know, we, we’d see the movement, and we had, we had really strong VPs and, and leadership there, but we weren’t, you know, that wasn’t a discussion that designers got to have, uh, and that was a big problem. And I think we would all have been more successful 10 years ago if literally everybody in the company understood the finances.”

That last clause is the breakthrough sentence of the whole conversation. We would all have been more successful ten years ago. Not the designers — all of us. The thing he’s describing isn’t a missing skill on the design side. It’s a structural choice on the company side, made when finance was an expensive specialty and giving everyone a window into the P&L would have been more risk than reward. So the designers spent the decade making craft arguments to people who were having a different conversation in a different language in another room. And the designers who eventually did get into that other room got there by going someplace small enough that they couldn’t avoid the finances anymore — which is the path Drew describes for himself, getting smaller and smaller until the numbers were on the same table as the work.

For a long time, the cost of learning that other language was high enough that it sorted people. You either spent two years and a hundred thousand dollars on a degree that taught you to speak finance, or you accepted that someone else would always be the one in the room translating between the design and the business. That sort was the gate. It wasn’t subtle, and it wasn’t fair, and the people on the inside of it ran most of the companies the designers were trying to influence.

Two things changed in the last couple of years, and Drew has spent his own money learning both of them.

The first is that the financial half of the literacy stopped being expensive. The frameworks and the vocabulary — what a P&L is, what a balance sheet is, how revenue and cost of revenue and contribution margin actually move — are a short course away now. The math you used to need to do by hand is something a spreadsheet does, and the moments where you’d freeze because you didn’t know the next move are moments where you can ask. You don’t need a degree to price a design decision anymore. You need the patience to learn the words and a tool that handles the arithmetic. Drew is matter-of-fact about it. The barrier wasn’t conceptual; it was access. Access just dropped.

The second is that AI removed the other half of the cost — the half nobody was talking about. For most of Drew’s career as a senior design leader, the unglamorous job underneath the title was maintenance. Maintaining the Figma library. Versioning the components. Mediating the requests for new variants. Shipping the tickets that kept the design system internally consistent so the rest of the team could move. That work was real, and necessary, and it consumed exactly the hours a designer might otherwise have spent learning the business.

About a year before our conversation, Drew started paying out of pocket for the maxed-out versions of Claude Code, Bolt.new, and Codex — a hundred to two hundred dollars a month of his own money. He started testing into onboarding funnels at GrowthDay, building variants in Claude Code or Bolt.new, shipping them, watching them, tearing them down. By his count, hundreds of variations in a year. By the end of the year, the engineering team trusted him to migrate to production.

Then he did the thing that’s hard to describe without making it sound either smaller or more dramatic than it was.

“I ended up reproducing our entire, like, Figma, basically Figma design library inside of Cloud Code,” he tells me. He means Claude Code; the audio system has been hearing the brand name as “Cloud” all conversation and I’ve stopped correcting it in my head. “It allowed my CEO or anybody to go and pull from that Git repo and then just ask for anything that you want, and then it would just produce it.”

What he just described is the dissolution of the design-system-maintenance job. Not its outsourcing. Its encoding. Five years of accumulated taste — every button, every type ramp, every brand decision people argued into existence — translated into a system that could produce in the brand’s voice from natural-language prompts. Anyone on the team, including the CEO, could ask for a funnel page or a post and get something brand-consistent back. The library went from a thing a person had to maintain in tickets to a thing the company carried in code. The job that used to eat the senior designer’s week stopped existing in the form that ate it.

And here is the conjunction the conversation hangs on. The two costs that kept designers out of the operator conversation — the cost of learning the finances and the cost of maintaining the system — both dropped at roughly the same time, on roughly the same curve, for roughly the same reasons. What was a permanent trade-off five years ago became, in the course of a year, a choice.

I ask Drew what a designer does with that, once they see it. He doesn’t pause.

“That’s why I think I’ve really shifted into, like, this operator language,” he says again. The word lands differently the second time. The first time he said it, it sounded like an identity move. The second time, it sounds like an point of view about where the work is now.

This is, I notice, the same Drew who introduced himself at the top of the call by giving me a title I hadn’t heard before.

“My name is Drew Bridwell,” he’d said. “I’m now a chief design operator. I’m primarily focused on helping founders bring their visions to life.”

Chief design operator. The compound is doing real work. The design half is the craft — twenty years of Lynda.com and LinkedIn and Facebook and InVision and GrowthDay. The operator half is what he learned the hard way, going small enough that the P&L finally got close enough to read. Sitting between the two is what AI freed him to actually do — visualize, make the unbuilt thing legible, get the people who have to fund it and ship it and sell it to look at the same picture.

Because that last part — visualization — is the thing that doesn’t get cheaper.

The frameworks you can buy. The maintenance you can encode. What you can’t outsource is the act of seeing what doesn’t yet exist with enough specificity that other people can see it too. That’s still a designer’s job, and it’s still rare, and it’s the thing the operator language was supposed to be in service of all along. When a founder is staring at a blank space and a board is staring at the same blank space and the team is waiting to be told which version of the thing to start building, the person who can put something concrete enough on the table for everyone to react to is the person doing the load-bearing work.

That work creates alignment, in the most literal sense of the word. The picture is on the table. We’re looking at it together. We agree this is the thing.

“He had to learn, and he’s not like any other CEO,” he says of Brendon. “He’s like, like a high-performing CEO, so he’s like learning and doing things as well and learning from us ‘cause, you know, I write about all this stuff in my status update every week, right? So I’m like, I’m, I’m a transparent, I’m a transparent beast. Like I’m gonna share it all.”

Transparent beast. He says it without irony. The transparency is how the visualization earns belief — not as a one-shot demo, but as an ongoing public record of the thing coming together. He wrote the weekly status update the whole way through. By the time the design library was in the repo, nobody had to be sold on what they were looking at. They’d been reading the receipts for months. The picture had been forming in their inboxes one Friday at a time, in his voice, on the record, and the day the keys were available the team had already been living in the thing they were now being handed.

What design at the operator level actually does, then, sits on top of both the craft and the finances rather than choosing between them. The work is making something invisible — a strategy, a brand, a year of decisions — visible enough that a roomful of people can agree it exists. Then writing the receipts every week so the agreement isn’t dependent on you being in the room.

There’s a line at the end of our call I keep replaying. Drew is talking about the next twenty years, about the five to ten founders he’ll work with, about the small businesses about to get well-made software for the first time. He says he projects one to two million dollars a year in this next phase. He says it like arithmetic, not a target. And then he adds, almost as an aside, the line that turns out to be the answer to the whole conversation:

“I’m trying to teach the whole system, not, not just one thing.”

The whole system. Not as the sum of the craft and the finances and the picture, but as the practice of holding all three in the same room at the same time. Designers spent twenty years asking for a seat at the table, and what they were really asking for was the conversation the table was having — the one in dollars, the one in trade-offs, the one about what gets built and what doesn’t. The conversation is open now. The seat costs what it always cost. The price just stopped being out of reach.

Guest Bio: Drew Bridewell

Drew Bridewell is a Chief Design Operator and fractional product design leader, helping founders across industries build custom digital products at a fraction of traditional costs. Rising to prominence in the 2010s as a design educator and systems architect, he became known for bridging the gap between UX craft, business operations, and high-performance team design — a practice built over two decades at companies including LinkedIn, InVision, and GrowthDay. He holds a Certified High Performance Coach (CHPC) credential and is the founder of Next Level UX, an operating system for designers and operators combining 20 years of design practice with research-backed high-performance habits.

Previously, as Head of Product Design at GrowthDay — a personal development platform built around Brendon Burchard’s six high-performance habits framework — Bridewell spent five years leading product experiments, testing hundreds of onboarding funnel variations using Claude Code and Bolt.new, and shipping code directly to production. He rebuilt GrowthDay’s entire Figma design library inside Claude Code, enabling the CEO to self-serve product iteration without a dedicated engineering headcount. Over three years of the engagement, he taught weekly live design and performance frameworks on the platform, reaching the company’s subscriber community of coaches, executives, and high-performance practitioners.

His career highlights include serving on the Design Transformation team at InVision, where he mapped the design systems and organizational maturity of hundreds of enterprise clients. Earlier, at Lynda.com prior to its acquisition by LinkedIn, Bridewell hosted Practical UX Weekly on LinkedIn Learning — a widely-followed series on interaction design principles that introduced a generation of early-career designers to the foundations of UX. He earned his degree from the Savannah College of Art and Design.

As founder of Next Level UX, Bridewell coaches designers, operators, and founders through systems built at the intersection of design thinking and financial literacy — teaching the operator skills that enable practitioners to price design decisions, understand P&L, and deliver at the level of a full product team as a single fractional contributor.

Hey,

Thanks for reading this. I mean that. There’s a lot of content out there competing for your attention, and you spent some of it here. I hope it was worth it. Even better, I hope it prompted you to think about something differently enough that you’d share it with someone who’d get something out of it too.

I started this podcast because tactics never stuck with me. What stuck were stories — business biographies, autobiographies, the decisions people made and why they made them. The principle only clicks once you know the story behind it.

So I built the thing I wanted to listen to. Every week I have two conversations with people who build in technology and product. Then I write the essay in my premium newsletter (Taste Maker) to distill the principles and reflect on the narrative — one that puts you inside the conversation, through my eyes. What caught me off guard. What I kept thinking about after we hung up. Where the principle actually lives once you strip away the jargon.

I make this for myself first. If you read the way I do, you’ll want it too.

PS — If you want to pitch coming on the show, or you know someone I should talk to, shoot me an email at caden@hey.com with "January752" in the subject line so it gets past my filters. I'm not optimizing for famous guests. I'm optimizing for interesting conversations, even from people who aren't LinkedIn influencers.

For years Brian Donohue thought the six-week cycle was the sweet spot — they’d arrived at it independently, the same place Basecamp landed. Then Intercom rebuilt its support product around large language models, and the cycle, the triad, and the stable teams all went out the window.

Listen to this episode on Spotify or Apple Podcasts

Guest Bio: Brian Donohue

Brian Donohue is the VP of Product at Intercom, where he leads product development for Fin, the company’s AI agent for customer support. Rising to prominence through more than a decade at Intercom, he became one of the defining figures behind the company’s transformation from a traditional SaaS helpdesk into an AI-first customer service platform. Under his leadership, Fin grew from a June 2023 launch with a 25% resolution rate to a sustained average of 65% resolution across all paying customers — widely regarded as one of the most measurable success records in enterprise AI product development.

Previously, as Director of Product Management at Intercom, Donohue oversaw multiple product areas during the company’s rapid growth years, building deep expertise in outcomes-driven development, user onboarding, and messenger interface design. Before Intercom, he served as Director of Design at Houghton Mifflin Harcourt, where he accumulated more than twenty years of combined design and product leadership experience across enterprise and consumer contexts.

Donohue has been a vocal advocate for technical rigor in AI product development, having championed the adoption of consumer-grade A/B testing methodologies within Intercom’s R&D organization and the firm’s transition to outcome-based pricing — charging per resolved customer conversation rather than per seat.

Key Conversation Topics

1. Continuous reassessment as strategy — Intercom questioned “are we going bold enough?” every three months rather than making one big bet. Incremental big swings added up to a massive shift.

2. Inherited product blindness — Even though Fin was “built from scratch,” Intercom was still anchored to old UX decisions (button-based resolution confirmation) that took two years to recognize and fix. The fix actually significantly improved resolution rates.

3. Outcome-based pricing aligning incentives — Charging per resolution ($0.99/resolution) aligned what customers want, what the product team optimizes for, and what finance cares about in a way seat-based pricing never could. Resolution rate climbed from ~25% at launch to ~65%.

4. The AI operating model shift — Throwing out the six-week cycle, the triad, and traditional team topology. “Follow the work” rather than organizing around stable teams. Destabilizing but effective for speed.

5. Technical uplift required for AI product managers — Natural language as the programming interface doesn’t lower the bar — it raises it. Engineers think in rule sets and constraints; PMs now need that same rigor.

6. R&D Services as a critical new muscle — Forward-deployed R&D folks (like Palantir’s model) are essential for getting customers to value. AI transformation requires hands-on implementation support. PLG counterintuitively did NOT get amplified by AI.

7. Build to think / prototyping value for PMs — The real opportunity for PMs isn’t doing final design — it’s using AI tools to prototype fast enough to validate ideas before bringing in designers.

Themes

• AI agent product development at scale

• Outcome-based pricing in SaaS

• Organizational transformation under AI pressure

• The paradox of technical uplift under “democratized” technology

• A/B testing rigor borrowed from consumer product applied to AI

Hey,

Thanks for reading this. I mean that. There's a lot of content out there competing for your attention, and you spent some of it here. I hope it was worth it. Even better, I hope it prompted you to think about something differently enough that you'd share it with someone who'd get something out of it too.

I started this podcast because tactics never stuck with me. What stuck were stories — business biographies, autobiographies, the decisions people made and why they made them. The principle only clicks once you know the story behind it.

So I built the thing I wanted to listen to. Every week I have two conversations with people who build in technology and product. Then I write the essay in my premium newsletter (Taste Maker) to distill the principles and reflect on the narrative — one that puts you inside the conversation, through my eyes. What caught me off guard. What I kept thinking about after we hung up. Where the principle actually lives once you strip away the jargon.

I make this for myself first. If you read the way I do, you’ll want it too.

PS — If you want to pitch coming on the show, or you know someone I should talk to, shoot me an email at caden@hey.com with "January752" in the subject line so it gets past my filters. I'm not optimizing for famous guests. I'm optimizing for interesting conversations, even from people who aren't LinkedIn influencers.

Listen to this episode on Spotify or Apple Podcasts

“I’ve got a quick example if I got time for it,” Vance Morris says. “Is that okay?”

It’s his interview. I tell him to go ahead.

So he tells me about an insurance agency. He’d been brought in to fix one specific thing: the way they answered the phone. It sounds small until you realize that answering the phone was the agency’s number one source of new business. Every lead came through that one ringing line, and the people picking it up sounded like everyone else who has ever picked up a phone. “Thank you for calling Dave’s Insurance. How can I help you?” Pleasant. Forgettable. Indistinguishable from the agency across the street and the one across the country.

Then Vance walked into the owner’s office. Gold records on the wall. Autographed guitars. The man was a rock and roll fanatic, and his entire personality was hanging there in frames, and nobody had thought to let it leak into the business. “We should really lean into this personality a bit,” Vance told him. And then comes the part Vance wants me to hear: the fix came from the receptionist. The idea was to answer the phone by channeling Wolfman Jack, the rock-radio howl. From then on, the phone got answered a different way.

“Thank you for calling Dave’s Allstate, the agency that rocks.”

I laugh, because it works, and because it’s the kind of thing that sounds like a gimmick until you sit with it for a second. Vance has clearly sat with it for longer than a second. He breaks it apart for me like he’s done it a hundred times, because he has. What to do: answer the phone. How to do it: the agency that rocks. And then he slows down on the third one, the one he actually cares about.

Why do we do it that way?

“Your marketing is designed to do two things,” he says. “Attract the people you wanna do business with and repel the people you don’t.” Answer the phone like a rock station and you start sorting your callers before they’ve said a word. The people who smile are your people. The people who frown and hang up were never going to be easy clients anyway. And underneath the sorting, there’s a second thing happening, which is that nobody else in the country is answering the phone that way, so the agency has quietly become the only one of its kind. “He owns it,” Vance says.

That’s when he gives me the line I anchor on. The why is what lets your employees “really have something that they can wrap their brains around.”

I want to stay on that, because I think it’s the whole interview hiding inside a phone greeting.

Vance spent about ten years at Walt Disney World. He was on the opening teams for the Yacht and Beach Club, for Pleasure Island, for Animal Kingdom, and his signature build was Chef Mickey’s, the character dining experience at the Contemporary Resort. He is, by his own cheerful admission, a lousy employee. “I just don’t like to be told what to do,” he tells me near the top of our conversation, which puts him “in the unemployable realm of things.” A man like that staying somewhere for a decade is worth paying attention to. He didn’t stay because Disney told him what to do. He stayed because, for nine and a half of those years, Disney was building things, and he got to build them. He was on the opening team. There was creation going on, and systems and processes being invented rather than maintained, and that was the work that held him.

And then it stopped, and that’s the part that should make every executive nervous. Growth slowed. “Processes and systems were just being managed as opposed to being created,” he tells me, and I can hear the moment land in his telling. “That’s where I kind of start to feel, eh, I’m not feeling overly creative anymore. I should look somewhere else.” Nothing went wrong. No one mistreated him. The company simply finished its 20 percent and settled into running the 80, and the man whose whole value was the 20 percent felt himself becoming redundant in a building that no longer needed anyone to invent anything. So he left. The lesson cuts both ways: the 20 percent isn’t only where you differentiate your product. It’s where you keep the people who can build the next one.

But the thing he carried out the door wasn’t the magic. It was the plumbing.

“Disney runs on systems and processes,” he says, and he knows how that lands. He knows the word “process” makes people picture employees behaving like robots, creativity drained out of them by a checklist. He thinks that’s exactly backward. “If you design a great process, an extraordinary process, it’s gonna deliver an extraordinary result.” That’s how a company gets 75,000 employees all singing the same song. There’s a process for waiting on a table. There’s a process for changing a bus tire. There’s a process for nearly everything, and the processes are simple, and that simplicity is the point.

Here’s the mechanism he describes, and it’s the part that reorganized something in my head. When the job becomes muscle memory, what he calls “muscle reflex memory by rote,” you stop spending your attention on the job. “It gives your brain 20 to 25% excess capacity,” he says, “’cause you’re not thinking about your job, you’re just doing it.” The systems aren’t there to make people smaller. They’re there to free up the exact slice of a person that the company actually wants: the part that takes the photo, gives the directions, signs the autograph, notices the kid who dropped his ice cream. The 80 percent runs itself so the 20 percent can show up.

Vance took that home and pointed it at three businesses nobody dreams about as a kid: carpet cleaning, mold remediation, an Oriental rug washing facility. He built a marketing system, a retention system, an operations system. He hired a general manager and gave him a single instruction. “Just manage the systems. Don’t screw with anything, just manage the systems.” They meet for an hour every Friday morning at 7:30 to talk through any improvements, and then the manager marches off and executes. Vance spends the other half hour of his week on the accounting, because he doesn’t let anyone touch the checkbook. Ninety minutes a week, total, on three companies. That’s what a well-designed 80 percent buys you.

I tell him what I think I’m hearing, because by now I can feel a shape forming. You systematize the 80 percent, the table stakes that don’t set you apart, precisely so you can stop sweating it. And the reason you tell employees this isn’t to keep them in their lane. It’s to draw the lane on purpose. This part is table stakes, so don’t waste your creativity reinventing it. This other part, the 20 percent, is where we actually compete, and that’s where we need your brain.

“Yeah,” Vance says, and he starts listing the companies that live this way. The Ritz-Carlton. Harley-Davidson. Apple. Each of them has the systems-and-processes piece locked down, and each of them also has the part that asks, constantly, “How do we make this thing better? Or how do we make it completely new?” They go hand in hand. And then he tells me where most people get it wrong, which is by giving the creative part too much room. “20% is enough,” he says. “’Cause otherwise you’re just going off in a myriad of directions and you kind of just flounder around and get lost.”

This is the trap I’ve watched product teams fall into from the other side. They systematize the wrong fifth. They build rigid process around the very thing that’s supposed to set the company apart, and they leave the table stakes to improvisation, so the differentiator calcifies while the basics stay sloppy. It’s the inversion of everything Vance is describing. The phone greeting gets standardized into beige, and the actual personality — the gold records on the wall — never makes it into the building.

What strikes me, sitting with all of it, is that the three words aren’t really a management framework. They’re a way of treating people like they can hold an idea. Most businesses stop at two because two is enough to get the task done. You can tell someone what to do and how to do it and the phone will get answered. But you’ll have built a person-shaped machine, and machines don’t channel their inner Wolfman Jack. The third word is the one that says: here is the reason this matters, and I trust you to do something with it.

And the proof, in Vance’s story, isn’t him. It’s the insurance company owner that had an affinity for rock and roll.

Vance didn’t hand down a script. He gave the owner a why: lean into who you actually are. And somewhere down the chain, a person who answers the phone for a living heard that why and invented the how. The agency that rocks.

That’s the line still ringing at that office, and no consultant wrote it. Someone who finally understood the “why” did.

Guest Bio: Vance Morris

Vance Morris is the Founder of Deliver Service Now!, a consulting and coaching firm that teaches small and midsize businesses how to implement Disney-caliber customer experience systems combined with direct response marketing. Rising to prominence through a decade of leadership at Walt Disney World, he became the creative lead behind Chef Mickey’s — Disney’s flagship character dining experience at the Contemporary Resort — a concept whose systems have remained largely unchanged for more than 25 years. He also built and systematized three home service businesses in Maryland (a carpet cleaning company, a mold remediation company, and an Oriental rug washing facility) to operate on 90 minutes of his attention per week.

Previously, as a manager and trainer at Walt Disney World through the 1990s expansion era, Morris served on the opening teams of the Yacht & Beach Club Resorts and Animal Kingdom, and acted as All-Island Duty Manager at Pleasure Island. He was recognized for generating $125,000 in business from a single marketing campaign, earning the Marketer of the Year award at a GKIC competition in 2015 and an International Marketing Award in a Dan Kennedy competition.

His consulting client roster has included NASA, the Smithsonian, the Kennedy Center for the Performing Arts, Legal Seafoods, Tyson, Rainforest Café, and Compass Group. He has shared stages with Daymond John, Dan Kennedy, Joe Polish, and Jack Canfield across more than 40 years of speaking experience.

Morris is also the creator of 52 Ways to WOW Your Customer, a free resource delivering one customer experience tactic per week of the year.

Hey,

Thanks for reading this. I mean that. There's a lot of content out there competing for your attention, and you spent some of it here. I hope it was worth it. Even better, I hope it prompted you to think about something differently enough that you'd share it with someone who'd get something out of it too.

I started this podcast because tactics never stuck with me. What stuck were stories — business biographies, autobiographies, the decisions people made and why they made them. The principle only clicks once you know the story behind it.

So I built the thing I wanted to read. Every week I have two conversations with people who build in technology and product. Then I write the essay I wish I could find — one that puts you inside the conversation, through my eyes. What caught me off guard. What I kept thinking about after we hung up. Where the principle actually lives once you strip away the jargon.

I make this for myself first. If you read the way I do, you’ll want it too.

PS — If you want to pitch coming on the show, or you know someone I should talk to, shoot me an email at caden@hey.com with "January752" in the subject line so it gets past my filters. I'm not optimizing for famous guests. I'm optimizing for interesting conversations, even from people who aren't LinkedIn influencers.

Listen to this episode on Spotify or Apple Podcasts

Partway through our conversation, I admit something to Khurram Mir that I’m not proud of.

“Whenever I have friction with a QA partner,” I tell him, “it’s because I feel like they’re being nitpicky about something.” They block the launch. They say no, this doesn’t work about something that, to me, looks finished enough to ship. I’ve been guilty of this recently — the quiet resentment that builds when the person whose entire job is to find problems keeps finding them at the exact moment you want to be done.

I expect Khurram to take my side. He has, after all, spent his career on the testing side of the table. He started in software testing in 2001, drawn to it because it asked him to think like a user instead of an engineer. He built Qualitum into a consulting firm with offices in five countries and more than fifteen years behind it. If anyone is going to defend the QA person against the impatient product manager, it should be him.

He doesn’t defend the QA person. He doesn’t defend me either. He does something more useful — he tells me the friction is a symptom, and then he tells me what it’s a symptom of.

“If you bring in QA early,” he says, “this is the best thing you could do for your own product.”

Then he stops, and takes a step back, the way you do when you realize the listener is holding the wrong frame entirely.

“Let’s not think QA as technical software engineers,” he says. “Let’s think of this person as somebody who is going to look at your application like an end user.”

I tell him I think I see where this is going, and he keeps pulling the thread. The QA person, he says, can be your beta user. Your friend who’s going to use the app. And then he says the line that reorganizes the whole problem for me.

“Let’s not even use the word test here. This person is going to use your application.”

There’s a weight on the word use when he says it — not a correction so much as a reveal, like he’s been waiting the whole conversation to put it that plainly. Because the consequence is immediate and it lands on me, not on the tester. “If you don’t bring this guy up to the speed on what the product is supposed to do,” he says, “and you don’t give them enough time and enough understanding of how the product is supposed to work as a user, they cannot really look into this application and give you any valuable feedback.”

I want to argue. I don’t, because I already know he’s right, and I know it because of a complaint I make about my own QA partners constantly. They tell me the form isn’t working. The submit button isn’t working. The field doesn’t validate. Khurram names this before I can.

“They may be able to tell you, this form is not working, this field is not working, my submit button is not working,“ he says, “but that even a CTO can figure out.”

That stings in the specific way that true things sting. The feedback I’ve been dismissing as nitpicky is exactly the feedback a context-starved tester is able to give. It’s the floor. It’s what’s left when you hand someone a finished build and no reason to care about it.

Earlier in our conversation I’d reached for a metaphor without realizing it was about to indict me. I’d been talking about video game testers — the ones you see in shows like Mythic Quest, paid to sit and play a game all day and log what breaks.

The reframe I loved was that they’re not outside the game. They’re playing it. They’re immersed, in character, trying to be the god of war in the game about being the god of war. And then I’d said the part I should have heard more carefully the first time: if all you do is hand someone a game with no context and tell them to play it, what can they possibly give you back?

“You just point out all the — everything that’s wrong with it,” I’d said. “Well, yeah, this button doesn’t work. Oh, the border radius is off by this many pixels.“ Because, I’d told him, “I need to justify my position, and you’re not giving me a lot to work with.”

The border radius. That’s the picture I can’t shake now. A person who was hired to protect the quality of your product, reduced to counting pixels, because counting pixels is the only thing left to do when nobody told them what the product was for. The nitpicking isn’t pettiness. It’s a person doing the only job you actually gave them.

Khurram takes the idea somewhere I hadn’t. The difference between a developer and a tester, he tells me, isn’t seniority or skill. It’s what they do with a user story.

“If you share a user story,” he says, “the developer will think, Oh, I need to implement this user story, and I have to write the code this way. But a tester needs to think of everything around that user story.”

He lets that sit, and then sharpens it.

“What is not written in that user story is what a tester has to think about.”

This is the whole craft compressed into a sentence. The developer builds what the story says. The tester is responsible for the negative space — every way a real person will use the thing that nobody bothered to write down, because the feature you shipped to be used one way will reach a customer who uses it some other way entirely. And a person can only see the negative space if you’ve shown them the whole picture first. You cannot ask someone to imagine what’s missing from a document they were never given.

Which is when Khurram describes the trap his testers live inside, and I recognize it as the exact trap I’ve been blaming them for.

“QA guys have this problem,” he says. “If they don’t report everything, then the team says, Oh, you didn’t report this. And if they over-report, then people say, Oh, you are wasting your time, because we have to filter out all the unnecessary stuff.“

So the tester logs everything, including the border radius, because the one time they don’t log something it becomes the thing that shipped, and then it’s their fault. Over-report and you’re nitpicky. Under-report and you’re negligent. There is no safe move available to a person who doesn’t know what matters. The double-bind isn’t a personality flaw in the QA team. It’s the predictable output of a system where nobody told them what to care about.

I say it out loud, because by now it’s the only honest thing left to say. If QA is being nitpicky, it’s my fault — because they don’t know what to look at. They don’t know what to evaluate.

Khurram answers with a question I’ve been circling the entire conversation without landing on.

“What is the priority?”

He says it like the question contains its own answer, and it does. “As a product manager,” he says, “you must prioritize it for them. You must tell them, Look, in terms of priority, these are the features that we need to look at.“ Not because the tester is incapable of judgment — the opposite. He’s clear that QA needs to come back with their own opinion, their own suggestions, their own sense of where the product could be better. But the priority, the frame, the this is what good looks like for this release — that has to come from the person holding the vision. That’s not testing work. That’s product work. I’d been outsourcing my own job and then resenting the people I outsourced it to for doing it badly.

There’s a number Khurram offers that makes the cost of getting this wrong concrete. He tells me you are far better off having a QA person hand you two extra bugs than having a customer send you a single one. The math isn’t close. A bug a customer finds engages your support team, your developers, your reputation, and your own attention, all at once, at the worst possible time. A bug your tester finds costs you a conversation. The nitpicky QA person you’ve been quietly resenting is the cheapest insurance you will ever buy, and the resentment is just the sound of you misreading the invoice.

Near the end, Khurram makes the shift explicit, and it reframes the whole category for me. Imagine, he says, the tester comes back not with a list of broken buttons but with something else: I used this. Here’s how you could make it better.

“QA shifts, in my opinion, from a cost center to a value center,” he says, “the moment you start thinking of QA as not just somebody finding me issues.”

I’ve spent years treating the QA function as a tollbooth between me and shipping.
A job family that exists to slow me down — and occasionally to embarrass me.

Khurram has spent his career on the other side of that glass, watching product managers like me hand a finished build to a stranger, withhold every reason to care about it, and then take the resulting pixel-counting as proof that testing is a tax.

The border radius was never the problem. The border radius was the answer to the only question I’d actually asked.

Guest Bio: Khurram Mir

Khurram’s Substack

Contrarian takes on software quality and engineering leadership.

By Khurram Javed Mir

https://www.linkedin.com/in/khurrammir/

https://www.youtube.com/@khurramjmir

Khurram Mir is the Co-Founder and Chief Marketing Officer of Kualitatem, a specialized software quality engineering and information systems auditing firm operating across the United States, UAE, Saudi Arabia, Qatar, the United Kingdom, the Nordics, and Asia, and the Co-Founder of Kualitee, an AI-powered test management platform that grew out of Kualitatem’s internal tooling. Rising to prominence after beginning his career in software testing in 2001, Mir has spent more than two decades building the methodology and infrastructure that define enterprise QA at scale, accumulating over 500,000 hours of testing delivery and working with more than 200 client organizations across more than 350 applications.

Mir co-founded Kualitatem in 2009 on the conviction that independent quality assurance should be a non-negotiable phase of every software development lifecycle, not an afterthought appended at the end of a release cycle. The firm achieved TMMi Level 5 certification — the highest maturity designation in the Testing Maturity Model integration framework — and has maintained ISO 27001 and ISO 9001 certification for six consecutive years. Kualitatem also developed an internal training institute to build consistent QA discipline across its geographically distributed team. A banking engagement that became a defining case study demonstrated that involving QA teams at the requirements stage — a shift-left approach — eliminated 33 percent of defects before formal testing even began.

In 2016, Kualitatem productized the internal consistency tooling it had built to maintain uniform service quality across multiple countries, launching Kualitee as a standalone test management platform. The platform’s generative AI engine produces test cases directly from user stories and test scenarios, with Kualitatem’s own teams reporting a 23 to 27 percent reduction in testing time as a result. Kualitee now serves more than 2,000 engineering teams worldwide, including clients such as Emirates, T-Mobile, and Cox Enterprises, and has been recognized by G2 as a leading test management solution across multiple regional and segment reports. Mir serves as product manager for Kualitee in addition to his operational role at Kualitatem — a dual function that reflects the firm’s broader thesis: that the services mindset and the product mindset must be learned separately, even when one organization spawns the other.

Hey,

Thanks for reading this. I mean that. There's a lot of content out there competing for your attention, and you spent some of it here. I hope it was worth it. Even better, I hope it prompted you to think about something differently enough that you'd share it with someone who'd get something out of it too.

I started this podcast because tactics never stuck with me. What stuck were stories — business biographies, autobiographies, the decisions people made and why they made them. The principle only clicks once you know the story behind it.

So I built the thing I wanted to read. Every week I have two conversations with people who build in technology and product. Then I write the essay I wish I could find — one that puts you inside the conversation, through my eyes. What caught me off guard. What I kept thinking about after we hung up. Where the principle actually lives once you strip away the jargon.

I make this for myself first. If you read the way I do, you’ll want it too.

PS — If you want to pitch coming on the show, or you know someone I should talk to, shoot me an email at caden@hey.com with "January752" in the subject line so it gets past my filters. I'm not optimizing for famous guests. I'm optimizing for interesting conversations, even from people who aren't LinkedIn influencers.

Listen to this episode on Spotify or Apple Podcasts

John Long has spent 15 years selling technology — and the clearest pattern he’s noticed is that when product and sales stop trusting each other, the company doesn’t just slow down, it inverts.

“Developing product is a little bit like playing Battleship,” John Long tells me. “We do our best to get close. But we’re lobbing things over and hoping that we hit something.”

He says it without drama, the way you describe a thing you’ve made peace with. And it would be a perfectly ordinary metaphor — every product person has felt the fog of guessing what a customer actually wants — except that Long doesn’t stop at the guessing. He stops at what happens after the miss. Because the miss, in his telling, is where the trust starts to die.

Long has spent 15 years selling technology, and he’s a particular kind of seller. The kind who digs into the product until he barely needs a sales engineer, who can demo the thing himself because he’s bothered to learn how it actually works. That’s rarer than it sounds. “Some organizations don’t even allow that,” he says — they keep sellers out of the product entirely. He’s spent his career on the other side of that wall, close enough to product to watch the relationship between the two functions either compound or collapse. Now he’s the CEO of Thynk AI, a company building AI agents that handle the parts of selling no one enjoys. But the thing he keeps returning to isn’t the technology. It’s the human seam between the people who build and the people who sell, and how easily it tears.

Start with what it looks like when the seam holds, because Long has lived that too. He describes it almost wistfully. “If you have sales in one silo and product in another silo and the two never meet, product market fit is going to be a disaster.” The inverse — sales and product cross-pollinating — is the only way he’s seen a company nail it. He puts it bluntly: “If the guys developing don’t know what the guys using are actually doing with the tools, it’s not gonna work.” When that gap stays open, the seller is left doing something absurd. “You’re trying to sell ice cubes to Eskimos.” The product does A, B, and C. The customer needs X, Y, and Z. And so, Long says, “I spend 90% of the sales process trying to convince them that A, B and C is actually what they want to buy.” His favorite saying cuts the other way, toward the thing the silos make impossible: “Sell the customer what they want to buy.”

But the slow rot doesn’t announce itself as a strategy failure. It announces itself as friction, and the friction has a sound. Long can reproduce it from memory. The sales leadership preaching down at the reps: “Sell what’s on the truck. Don’t make up things. Don’t sell vaporware. Don’t sell things that don’t exist.” The sales leader carrying complaints up to the product leader: we need the product to do these things, and it’s not doing them. And the product leader, if he’s lost touch with what the customer actually needs, firing back the line that tells you the trust is already gone. “Hey, no, we gave you the perfect product. Quit complaining and go and sell what we’ve built.”

I ask him what the early symptoms are, the things you’d notice before anyone names the problem. He doesn’t reach for a framework. He reaches for the implementation team — the people downstream of every overpromise, the ones who inherit the gap between what was sold and what exists. He voices them, and you can hear that he’s heard this exact lament more than once. “Ah, I wish the sales reps would actually represent the product accurately. I’m having to fix all of their problems. I’ve got customers that are frustrated from day one.” Overpromising, churn, a backlog of broken implementations — these are the visible signs. Underneath them is the invisible one: “this spiral downward of friction, frustration.”

Then we get to Battleship, and the metaphor turns out to be sharper than it first appeared. Because the problem isn’t that people miss. Everyone misses. The problem is what each side is allowed to conclude from a miss.

Watch what happens, Long says, when a sales rep brings real intelligence back from the field — the customer needs it to do these things — and the product team builds toward it and lands close but wrong. “We splashed the ship, but we didn’t hit the ship.” A reasonable outcome. A near miss in a game that is mostly near misses. But the conclusion the product team draws is not reasonable. “The product team inherently says, ‘Oh, the sales rep doesn’t know what he’s talking about. He doesn’t know how to gather requirements. I don’t trust him. I’m not gonna listen to him anymore. I’m doing this on my own.’”

One miss, and the channel closes.

Now run the same miss the other direction. The product team, working from its own instincts, builds something and it doesn’t land. Same result, same splash, same near miss. But the verdict flips entirely. “If the product team develops something and they miss the ship, then they’re like, ‘Well, it’s okay. We got closer.’” The miss becomes a milestone. Foundational. A step in the right direction. “Suddenly it’s okay.”

That asymmetry is the whole thing. The sales rep’s miss is evidence he can’t be trusted. The product team’s miss is evidence they’re learning. Same game, same odds, two completely different scorecards — and the scorecard is what determines whether anyone keeps listening to anyone. Long isn’t bitter about it; if anything, he’s generous to both sides. “We all miss,” he says, twice, like he wants to make sure it lands for each camp. And then the line that defuses the blame entirely: “I genuinely don’t think anyone ever sets out to be like, ‘I’m gonna build a product that really doesn’t do anything.’”

He’s quick to point out the miss isn’t even fully anyone’s fault, because the target keeps moving. “There’s generally a lot of cooks in the kitchen on the customer side.” He acts out the contradiction the product team is asked to satisfy: one customer insists the button belongs in the upper left corner, because that’s where everybody looks. The next person in the same company is just as certain it belongs in the bottom left, for the same reason. “You’re never gonna get it exactly right.” The honest goal isn’t precision. It’s persistence. “Hopefully we’re hitting boats every once in a while. And then we’ve got something solid and we can start to kinda hit around that.” Like Battleship, he says, you eventually sink the ship — but only if both players are still willing to call out coordinates.

Which is why the cure he describes isn’t a process. It’s a relationship. And he has a specific one in mind.

“Inherent in that type of relationship is a foundation of trust,” he says, and then he gets concrete in a way that turns the abstraction into a person. His business partner today — at the AI company he’s building right now — is the same man who ran product at a company where Long was selling 15 years ago. The product guy. The one developing while Long was out selling what got developed. I ask, and the number he gives me lands hard enough that I say “wow” out loud. The two of them have traveled together, he estimates, “well over 100 times.”

Not for offsites. For customers. “We were constantly connected at the hip. I was selling, he was developing, and we had this deep level of trust with each other.” For seven or eight years, multiple times a month, they got on planes together — the seller and the builder, going to see the same customers with the same eyes. “We were cross-pollinating our two worlds on a regular basis every single week. Either I was in with the product team or he was with me on sales calls, one or the other.”

That’s the antidote to the Battleship asymmetry, and notice what it actually requires. It’s not better requirements documents. It’s proximity sustained long enough that neither side can hide behind the wall. When the product guy is sitting in the customer meeting, he doesn’t get to dismiss the sales rep’s intelligence as secondhand — he heard it himself. When the seller is sitting in the product room, he doesn’t get to treat a miss as betrayal — he watched how the sausage got made. The trust Long describes isn’t a feeling they decided to have. It’s a residue, the thing left behind by a hundred shared flights.

What strikes me, listening to him, is that the trust came first and the results followed, not the other way around. Long has had the dialed-in experiences every seller dreams about — the products so well-fit that customers wanted a quote before he finished the pitch, the runs of growth where the scaling never scaled complexity. But when he traces those back, they don’t start with a great product. They start with a seller and a builder who refused to operate in separate rooms.

The spiral he describes — the one that starts with a single near miss and ends with two functions that have stopped speaking — is the default. It’s what happens when you let the wall stand and let each side keep its own scorecard. The companies that escape it don’t escape because they miss less. They escape because someone decided that a miss was a coordinate, not a verdict, and kept playing.

Near the end, Long is describing the AI company he’s building, and he mentions, almost in passing, that his co-founder is that same product guy. The one from the first story. The one he’s flown with more than a hundred times. They scrapped one plan, elevated another, and ended up here — still the seller and the builder, still connected at the hip, fifteen years and one industry later.

He doesn’t frame it as proof of anything. But it is. The whole conversation has been about what happens when sales stops trusting product, and the answer has been sitting in front of me the entire time, in the shape of a man who never let it happen.

Guest Bio: John Long

John Long is the CEO and Co-Founder of Thynk AI, a Utah-based company building AI communication agents that handle the full pre-sales motion — cold outreach, lead qualification, scheduling, and beyond — without a human ever touching the conversation. Rising to prominence in enterprise technology sales over a 15-year career, Long built his reputation not as a manager of sales teams but as the kind of operator who embeds so deeply with product that the line between salesperson and builder disappears entirely. He was once the lone sales representative tasked with opening a brand-new market segment, and over the course of more than 100 trips with his product team, he helped construct what became a multimillion-dollar recurring revenue line from scratch. The product partner he worked alongside on that run is now his co-founder at Thynk AI.

Founded in mid-2024, Thynk AI entered the market with a thesis that most AI SDR tools are window dressing — capable of sending a templated email but unable to hold a real conversation, respond to replies, or carry a prospect from cold contact through to a qualified meeting without human intervention. Long and his co-founder built Eric, Thynk AI’s AI sales agent, to close that gap end-to-end. Eric makes and receives calls, sends texts and emails, conducts live phone meetings, qualifies and disqualifies prospects, and books follow-ups autonomously. The company’s own website reflects the conviction: there is no human contact available until Eric has qualified you. In its first 90 days of operation, the platform generated $13,440,000 in pipeline for its users with no human SDRs and no ad spend.

Long sees AI communication agents as a platform, not a point solution. Thynk AI has already extended Eric beyond outbound sales into customer service, HR, and accounting functions — any workflow where a business currently deploys a human to conduct a structured, repeatable conversation. The company operates from Lehi, Utah, and Long continues to serve as an advisor and speaker on practical AI deployment for growth-stage companies.

Hey,

Thanks for reading this. I mean that. There's a lot of content out there competing for your attention, and you spent some of it here. I hope it was worth it. Even better, I hope it prompted you to think about something differently enough that you'd share it with someone who'd get something out of it too.

I started this podcast because tactics never stuck with me. What stuck were stories — business biographies, autobiographies, the decisions people made and why they made them. The principle only clicks once you know the story behind it.

So I built the thing I wanted to read. Every week I have two conversations with people who build in technology and product. Then I write the essay I wish I could find — one that puts you inside the conversation, through my eyes. What caught me off guard. What I kept thinking about after we hung up. Where the principle actually lives once you strip away the jargon.

I make this for myself first. If you read the way I do, you’ll want it too.

PS — If you want to pitch coming on the show, or you know someone I should talk to, shoot me an email at caden@hey.com with "January752" in the subject line so it gets past my filters. I'm not optimizing for famous guests. I'm optimizing for interesting conversations, even from people who aren't LinkedIn influencers.

Listen to this episode on Spotify or Apple Podcasts

There was a time, Michael Ferranti reminds me, when people who loved Sonos would not shut up about it.

He says it almost fondly, the way you’d describe a friend’s old enthusiasm. The rabid fan base. The audiophiles who treated their speakers as a personality trait. Sonos wasn’t just good equipment — it was a great experience, he says, the kind where everything in the house seemed to talk to everything else without you having to think about it. Everything just worked together. People evangelized it.

“At least until a couple of years ago.”

That clause is the whole story, and Michael lets it sit there for a second before picking it back up. He’s the VP of marketing at Unleash now, an open-source feature management company based out of Oslo, and he’s spent well over a decade in and around dev tools and infrastructure — the kind of person who reads other companies’ engineering blogs for fun and remembers what they said. Which is why the Sonos story bothers him the way it does. Because Sonos, by his account, knew better. They had written down exactly how to avoid what they were about to do to themselves.

“From a DevOps perspective,” he says, “they had an internal engineering blog where they were always talking about, hey, we’re on Kubernetes now, we’re using containers, we’re doing CI/CD, we’re doing all these things, we’re monitoring with Datadog.” He runs through the list like a man reading a résumé that should have prevented a tragedy. By every technical measure, this was a company that understood how to ship software safely — incrementally, in small controlled batches, watching the metrics, ready to roll back.

And then, Michael says — and here his voice picks up a particular relish — “probably because of the pointy-headed business people.”

He catches himself. “No offense.” A beat. “People have accused me of being a pointy-headed business person myself, so I say that with love.” It’s a good line, and he knows it, and it does a real piece of work in the story: he is not an engineer taking a shot at the suits. He is one of the suits, indicting his own kind.

What the business people wanted was a moment. A new set of headphones, unveiled to the market all at once. Not just the headphones — a new version of the hardware, a new mobile app, the whole constellation lighting up on the same day so that anyone who owned all of it would have a single, coordinated, mind-blowing experience. To pull that off, they did the one thing the engineering blog warned against. “They held a bunch of changes that they wanted to make,” Michael says, “until this big bang release.”

He pauses, because we both know where this goes.

“Not surprisingly, since I’m talking about it on this podcast” — a small grin in the voice — “the outcome wasn’t everybody loved it and applauded.” He lets the real sentence land flat and hard. “The outcome was it broke everything.”

It took them months to unwind. And the part Michael keeps returning to isn’t the engineering damage, it’s what the engineering damage cost. The thing Sonos had spent years building — that rabid, won’t-shut-up loyalty — “they took this brand loyalty that they had accumulated through blood, sweat, and tears over the last couple of years, and just flushed it down the toilet.” He wants me to know he isn’t reaching for drama. “I’m really not exaggerating. Their market cap tanked.” Over $100 million in lost direct revenue, by his count — and that figure doesn’t even include the market capitalization or the brand equity, the harder-to-tally erosion of all those people who used to evangelize and now just felt burned.

The diagnosis is brutal in its simplicity. They didn’t follow their own blog.

I ask him how that happens. How a company writes the correct playbook, publishes it, brags about it, and then does the opposite. Michael doesn’t pretend it’s mysterious. “When the CEO says jump,” he says, “you say how high.” The blog was true. The incentives were truer. Somewhere above the engineers who knew how to release software incrementally was a person who wanted the splash, the unveil, the keynote moment where everything works at once — and the closer you sit to that person, the harder it is to be the one who says we should do this slowly, in pieces, where it’s less impressive and far less likely to detonate.

This is the failure mode Michael has built his argument around, and the Sonos story is its cleanest illustration. The instinct toward the big bang isn’t stupidity. It’s seductive. It promises that if you can just get the latest hardware and the latest app and the new product to land together, you’ll deliver something nobody could feel any other way. The trouble is what it requires you to ignore. To make the coordinated experience perfect, Sonos effectively told most of its existing customers — the ones a few generations back on hardware — that they weren’t sure how it would work for them yet. “For everybody else,” Michael says, channeling the bet they made, “people that are on four generations ago, we’re not sure how it’s gonna work yet. So we’re not gonna try to do that now.”

You’re either in the mind-blowing experience or you’re a casualty of it. There is no middle setting on a big bang.

What he wishes they’d done instead is the thing his whole company exists to make easy. “What’s the experience that we’re trying to create,” he says, “and how do we know categorically that we’re creating that experience?” You measure the user experience as you roll the products out. You do it in small batches over time. You build a feature, expose it to a few, watch what actually happens, and keep your finger near the switch. Underneath that is the mechanism — feature flags, the ability to turn functionality on and off in production safely, in a controlled way, without a deployment. And the piece he keeps coming back to, the one that would have saved Sonos, he calls surgical rollback. “If ever there’s an issue, you can roll it back very, very surgically.” Not a months-long unwind. A scalpel, applied to the one thing that broke, while everything else keeps running.

Picture the same launch run the way he describes it. The new app goes to internal users first, then to a small group of customers who like being on the latest and greatest, then to one region, then everywhere — each step measured, each step reversible. The hardware reaches the people on current-generation gear first, where the team is confident, before anyone promises a mind-blowing experience to a customer four generations back. Nothing gets held in a vault for a single coordinated detonation. The release stops being one enormous unobserved bet and becomes a series of small observed ones. And underneath it is the way Michael thinks about a feature across its whole life — he watches it travel from an idea to code to the thing a customer can actually touch, and then he decides what happens to it. “Sometimes I kill the feature because it doesn’t work,” he says. “Sometimes I roll it out globally.” A big bang offers exactly one of those endings and quietly removes your ability to choose between them. By the time you learn which one you got, it’s already everywhere, and the only tool left is the months-long unwind.

The deeper point, and the one that makes the Sonos story more than a cautionary anecdote, is about who holds the knowledge versus who holds the decision. The engineers knew. The blog proved they knew. But the call belonged to people optimizing for a different kind of metric — the launch, the narrative, the moment — and the org chart made sure the people with the safest path had the smallest voice. Michael’s case for feature ops is, underneath the tooling, a case for changing that. For giving the people who understand how software actually behaves a real seat when the irreversible decisions get made. “A developer could be like shrug emoji” if you ask them whether to ship to everyone, he tells me elsewhere — not because they can’t answer, but because the question was never fully theirs to answer alone. Sonos is what happens when nobody with the scalpel is in the room when the CEO says jump.

I find myself thinking about the fans. The ones who used to evangelize, who treated the brand as a piece of their identity, who would not shut up about how well it all worked together. A big bang is supposed to be for them — the grand coordinated experience, the payoff for their loyalty. Instead it was aimed straight at the thing they loved most.

Sonos got their market cap back, eventually. The headphones shipped. The systems got unwound. But Michael’s phrasing stays with me, because it names the part that doesn’t show up on a balance sheet. The loyalty, accumulated through blood, sweat, and tears, flushed in a single release.

You can recover revenue. The people who used to not shut up about you are quieter now.

Guest Bio: Michael Ferranti

Michael Ferranti is the VP of Marketing at Unleash, the world’s largest open-source feature management platform, where he leads go-to-market strategy for a company that has more than 500 enterprise customers, 13,500+ GitHub stars, and 35 million downloads. Rising to prominence in the 2010s through a series of infrastructure and developer-tools companies, Ferranti built a reputation as a marketer who can translate technically dense products — container storage, zero-trust access, feature flags — into category-defining narratives for engineering and platform buyers.

Previously, as Chief Marketing Officer at Teleport, the open-source infrastructure access platform, Ferranti joined in late 2021 and led the company’s marketing organization through a period of rapid enterprise expansion. Before Teleport, he spent nearly four years at Portworx as VP of Product Marketing and Corporate Marketing, where he helped build the category around Kubernetes-native persistent storage before Portworx was acquired by Pure Storage in 2020 in a deal valued at $370 million.

Earlier in his career, Ferranti held marketing and product roles at ClusterHQ and at Rackspace, where he worked in the early days of OpenStack and most recently served as head of marketing for Mailgun by Rackspace, the developer email API. A Virginia Commonwealth University undergraduate, he relocated from Richmond, Virginia to the Paris metropolitan area in 2023. At Unleash, he has been part of the team that tripled ARR over three consecutive years, closed the $35 million Series B in March 2026 led by One Peak with participation from Spark Capital, Frontline Ventures, and Firstminute Capital, and expanded the customer roster to include Lloyds Banking Group, Wayfair, Prudential, and Lenovo.

Hey,

Thanks for reading this. I mean that. There's a lot of content out there competing for your attention, and you spent some of it here. I hope it was worth it. Even better, I hope it prompted you to think about something differently enough that you'd share it with someone who'd get something out of it too.

I started this podcast because tactics never stuck with me. What stuck were stories — business biographies, autobiographies, the decisions people made and why they made them. The principle only clicks once you know the story behind it.

So I built the thing I wanted to read. Every week I have two conversations with people who build in technology and product. Then I write the essay I wish I could find — one that puts you inside the conversation, through my eyes. What caught me off guard. What I kept thinking about after we hung up. Where the principle actually lives once you strip away the jargon.

I make this for myself first. If you read the way I do, you’ll want it too.

PS — If you want to pitch coming on the show, or you know someone I should talk to, shoot me an email at caden@hey.com with "January752" in the subject line so it gets past my filters. I'm not optimizing for famous guests. I'm optimizing for interesting conversations, even from people who aren't LinkedIn influencers.

Under every answer Fin gave, for two years, sat two buttons.

The AI would resolve a customer’s question, list its sources, and then ask: Did this answer your question? Below it, the only two ways to respond. Yes. Or: Talk to the team.

“It was, like, crazy bad UX,” Brian Donohue tells me, walking through it the way you walk through a photo of yourself from 15 years ago. “It was, like, the wrong question to ask at the wrong time.” Listen to the shape of the thing. Did this answer your question? Yes. Or: talk to the team. “You couldn’t say no and continue it,” he says. The interface presumed the conversation was over at the exact instant the whole point was to keep it going. “It was, like, a way no one would ever ask this.”

Brian is the VP of Product for Fin, Intercom’s AI agent for customer support — the thing he’s spent the last two and a half years going, in his own words, “progressively, progressively, progressively, more and more and more” all in on. He’s been at Intercom for 11 years. He’s watched the company carry its support product from the old rule-based bots, “where there’s a little bit of ml” and “mostly deterministic stuff going on,” all the way to a system rebuilt from the ground up around large language models. He’s proud of it. You can hear the pride in the way he narrates the early days — the summer of 2022, before ChatGPT, when one of his ML engineers stood up at a show-and-tell to demo summarizing a support conversation and the verdict was “it just still doesn’t work that well.” And then, a few months later, it did. “It immediately was good enough there,” he says. “That opened the door.”

So when he says the company built Fin from scratch, he means it. They threw away the old bots. They restarted on the new system. “That was ground up, from rebuilding.”

Which is what makes the buttons such a strange thing to find still standing.

They weren’t a corner of the product nobody looked at. “This is anchored into our whole system,” he says. “This is how we calculate resolutions. This is how we charge. It’s a fundamental UX part of the system.” The buttons weren’t a cosmetic afterthought. They were load-bearing. The company’s revenue ran through them.

And the team that built Fin from scratch — the team that prides itself on having thrown the old world away — did not see them. For two years.

“We were blind,” he says. “It was inherited product we were blind to.” He keeps circling the same disbelief, the way you do when you’re still metabolizing it in real time. “Oh, we built Fin from scratch.” A beat. “But no, we didn’t.” His voice catches the way it does when a person hears himself mid-sentence. “We still had parts of the system we were anchoring on, and two years later — oh my God, I can’t believe we still inherited that design and hadn’t challenged it.”

I tell him this is exactly the conversation I wanted. Earlier I’d said something I meant as a compliment and a confession of my own: I’m glad I’m talking to him and not to the CPO. The CPO is a fantastic storyteller, buttoned up and polished, and for good reason. “I want the documentary,” I tell Brian. “I don’t want the blockbuster.”

This is the documentary. A team rebuilds its entire product around the most disruptive technology of the decade, and the thing holding it back turns out to be a design decision they’d already declared finished. Not a hard technical problem. A button. A question phrased wrong, shipped fast, and never looked at again — because, as Brian puts it, “it’s slow, it’s deep in the process system, and so everyone’s reluctant to change it.”

What he says next is the first of three moments in this conversation where Brian admits that the thing he was most certain of was exactly the thing he had to unlearn. The button. Then a process he was sure would never die. Then the way he charged for the whole thing.

What this profile covers

The buttons are the first of three certainties Brian had to unlearn at Intercom. What it took for a team that prides itself on having rebuilt Fin from scratch to finally see the two-year-old design they’d been carrying — and what showed up on the dashboard the day they finally moved it.

The second is the operating model he and Basecamp once independently arrived at: the six-week cycle Basecamp made famous in Shape Up, the sweet spot Brian was sure would never die. He threw it out anyway, along with the triad and stable teams, in favor of a one-line mantra — follow the work — and a cost he names without flinching.

The third is how Intercom charges for Fin. Ninety-nine cents a resolution, billed only when the bot actually answers a customer’s question without escalating to a human. A pricing bet from a company with what Brian calls “a pretty bumpy history with pricing,” and what it collapsed about an entire category of product work he used to do.

Through-line: three things an 11-year intercom veteran was surest of, each one quietly the inherited debt. What he’s learned to distrust about the feeling of certainty itself.

Read more

Listen to this episode on Spotify or Apple Podcasts

Before Issac Hicks built a company that erases tedious work, he spent years watching people fight to keep it.

He tells me about the consulting days. He was at one of the Big Four, parachuting into companies in the middle of acquisitions — his job, specifically, to manage the software migrations and technology transitions that follow when one company swallows another. And the thing he kept seeing, no matter what the project was, no matter what he’d been staffed to, was a particular kind of resistance. A company gets bought. Somewhere four levels up, somebody made a lot of money. And the people on the ground, the ones who actually run the workflows, look at the new systems they’re being asked to learn and dig in their heels.

“They had such, so much pain in what they were doing,” he says, “but at least it was a pain they knew.”

That line stops me. Because it explains something I’d never been able to name. The resistance was never really about the new system being worse. It was about the old pain being familiar. He acts out the internal monologue of the bitter employee: “Oh, so I have to learn a whole new bag of crap that I have to do now? Are you serious?” The crap they already had was at least theirs. They’d built a kind of grim competence around it.

Hicks is an aerospace engineer by training who decided, somewhere along the way, that he didn’t want to pursue that career further. Consulting came next, then a turn that now looks prescient: he started building custom AI solutions before most people knew what that meant. This was the era when you had to design the neural nets yourself — perceptrons, regression analysis, basic sentiment analysis stitched together from a limited vocabulary, all of it before the transformer paper made the whole thing legible to the rest of us. He filed the paperwork for Autonomi in February of 2021. It didn’t take off until years two and three, which is to say, until the rest of the world caught up to where he already was.

So when I bring up the fear — the disruption everyone’s bracing for, the careers built entirely on being willing to do the schlep work nobody else wanted — I expect him to hedge. To do the responsible thing and acknowledge the human cost.

He doesn’t hedge. He reframes.

“I’m really an optimist about the whole AI thing,” he says, “because there’s kind of two ways you can look at it.” The first way is the one we all already know. AI comes, displaces a bunch of jobs, and what are these people going to do? Unemployment skyrockets. What about the working man. He’s not dismissive of it — he just thinks it’s overweighted. “It gets a lot of traction. I think it has a lot more traction than it deserves, and the reason I think it has more traction than it deserves is because it’s fear, uncertainty, doubt. It works well in news cycles. It’s gonna get the views, it’s gonna get the clicks.”

Then the other way. The way he actually lives in.

“If those are already profitable workers,” he says, “how much more profitable could they be if they were doing more meaningful work?” He keeps going, and the questions stack on each other like he’s been waiting to ask them. How much more could you accomplish? How much more market share could you have? How much more productivity could you get as a business owner?

The logic underneath it is almost boring in its sturdiness. A worker you employ is, by definition, someone you make money on — that’s what employment is. So the displacement instinct, the cut-the-headcount reflex, is throwing away an asset you’ve already paid to acquire. “It is more efficient to repurpose labor that is already a culture fit, that is already aligned, that you can already trust,” he says, “than it is to try to just get rid of people and then bring on systems that aren’t proven, that you have to figure out yourself or hire somebody to implement.” The person already inside your company is the cheapest, most trustworthy resource you have. The fear narrative treats them as the cost. He treats them as the gain.

I want to know what the tedious work actually is, the stuff he’s automating away. He doesn’t reach for an abstraction. He reaches for a spreadsheet.

“It just makes life so much better when you don’t have to spend hours doing that mind-numbing, soul-crushing” — he searches for the example and lands on the most ordinary one imaginable — “it’s like, ‘Oh, I’m gonna design a spreadsheet for six hours.’”

He almost laughs at it. “Who wants to do that? Nobody wants to design a spreadsheet. Are you kidding me?”

This is the part of his thinking that I find most persuasive, and it’s the part that has nothing to do with technology. Earlier in our conversation he’d described the math of it — a worker spending two-plus hours a day filling out forms, sending routine emails, checking records to make sure things are validated. Multiply that across dozens or hundreds or thousands of people and you’re talking about tens of thousands of work hours. He frames it as a cost problem, which it is. But then he says the thing that I think actually drives him: “That’s also just a morale problem. Somebody who’s spending two-plus hours a day doing that kind of thing — do you think they like that? Are they likely to stick around? What’s your employee attrition look like?”

And then he does something I didn’t expect. He gets meta with it.

“If that’s how they feel during the day,” he asks, “what are they doing outside of work? What’s their family life like? How are they interacting with strangers?” His voice slows here, the salesman tone gone entirely. “What is that doing for society at large whenever you have a bunch of people who are going through their lives just frustrated with the crap that they have to do day in and day out?”

That’s the moment the conversation stops being about automation and starts being about something older. The tedium isn’t just expensive. It’s corrosive. It follows people home. Hicks didn’t start Autonomi because he loves operational workflows — he started it, he tells me, because “I kind of saw an opportunity to both fill a market need and just kind of remove all the crap that was in people’s lives.” The market need was the business case. Removing the crap was the actual point. “I thought it would be a good thing to do to just help people stop doing stuff like that.”

I recognize the impulse — I was the guy who built the spreadsheet, every time, because someone had to. What Hicks names so cleanly is the trap inside that role: the work was always a tax, never the job.

There’s a popular essay among engineers called “Glue Work” — about the unglamorous coordination labor that holds teams together. Its hardest truth is that the risk of doing glue work is that you were never hired to do it in the first place. You do the necessary, invisible thing, and the org promotes the person who shipped the feature instead. Tedium has always operated this way. It’s necessary, nobody wants it, and the people who absorb it rarely get rewarded for absorbing it.

So here is what Hicks is really saying, underneath the optimism, and it’s the thing the displacement story gets backwards. The jobs AI takes are not the jobs people wanted. They’re the jobs people endured. As Hicks puts it, the core ethos is “just being able to get rid of those really tedious things that nobody really wants to do in the first place, but you have to — and now you can automate those.” Nobody’s calling at career built on dread. They’re calling it a career because there was no alternative, and the dread came bundled with the paycheck. Remove the dread and you haven’t removed the person. You’ve removed the tax they were paying to keep the job.

The fear assumes the tedium was the value. Hicks has watched enough acquisitions and built enough systems to know it was the opposite — the tedium was what stood between people and the value they could actually create. He’s not naive about the transition; he knows real disruption is coming, that some people whose entire identity is wrapped around the drudgery will refuse to relearn and will lose out. But the worker who’s willing to move is worth more on the other side, not less.

Which leaves the question he keeps circling back to, the one that lingered after we hung up. When the crap is gone, what fills the space?

“What else could they have been doing?” he asks. “What’s that backlog of work?” Every company he’s ever walked into has one — the pile of things everyone knew mattered and no one ever had the hours for. The strategy that never got written. The customer problem that never got solved. The thing you kept saying you’d get to.

“What would have taken you a year,” he says, “that you can now do in two or three months?”

The backlog was always there. It was just buried under six hours of building a spreadsheet nobody wanted to build.

Guest Bio: Issac Hicks

Issac Hicks is the Founder and CEO at Autonomi, an AI and automation consulting firm that helps mid-market and enterprise companies make critical work reliably repeatable. Rising to prominence in the applied AI space in the early 2020s, Hicks built Autonomi into a recognized force in business process automation — earning a seat on the Forbes Technology Council — by focusing on a thesis most consulting firms won’t touch: that the biggest source of wasted enterprise spend isn’t bad strategy, it’s the avalanche of tedious, repetitive operational work that consumes employees’ days. His firm has driven over $50 million in wasted spend back to the bottom line across deployments spanning custom applications, AI-enabled workflows, and end-to-end process automation.

Hicks arrived at entrepreneurship through an unlikely path. He earned a Bachelor’s Degree in Aerospace, Aeronautical and Astronautical Engineering from Missouri University of Science and Technology (class of 2016), then spent roughly a year working as an aerospace engineer for the government before pivoting into Big Four business consulting. In that role he specialized in technology implementation for companies undergoing software migrations and acquisitions — work that put him inside some of the most operationally chaotic moments a company can experience. He watched acquired employees dread every transition, buried under work that existed solely because no one had built a system to handle it. In February 2021, he left consulting to found Autonomi with the conviction that the gap between a business problem and a scalable AI solution was bridgeable — and that bridging it was more valuable than any single consulting engagement.

Autonomi operates across the full spectrum of automation maturity: from $5,000 pilot deployments to full-scale engagements starting at $25,000, with a primary focus on companies generating $2 million or more in annual revenue. The firm’s product portfolio includes Autonomy Books, an automated bookkeeping solution built specifically for CPA firms — a vertical where reconciliation and data entry remain stubbornly manual despite being near-perfectly suited to automation. Rather than pursue venture capital and the growth-at-any-cost model that comes with it, Hicks chose to build Autonomi as a profitable, self-sustaining business, retaining the operational control he now helps his clients achieve.

Hey,

Thanks for reading this. I mean that. There's a lot of content out there competing for your attention, and you spent some of it here. I hope it was worth it. Even better, I hope it prompted you to think about something differently enough that you'd share it with someone who'd get something out of it too.

I started this podcast because tactics never stuck with me. What stuck were stories — business biographies, autobiographies, the decisions people made and why they made them. The principle only clicks once you know the story behind it.

So I built the thing I wanted to read. Every week I have two conversations with people who build in technology and product. Then I write the essay I wish I could find — one that puts you inside the conversation, through my eyes. What caught me off guard. What I kept thinking about after we hung up. Where the principle actually lives once you strip away the jargon.

I make this for myself first. If you read the way I do, you’ll want it too.

PS — If you want to pitch coming on the show, or you know someone I should talk to, shoot me an email at caden@hey.com with "January752" in the subject line so it gets past my filters. I'm not optimizing for famous guests. I'm optimizing for interesting conversations, even from people who aren't LinkedIn influencers.

Listen to this episode on Spotify or Apple Podcasts

Paul Glover spent 30 years as “Mad Dog” — a Chicago trial attorney who would do whatever it took to win. That instinct carried him into 33 white-collar felonies and five and a half years in federal prison. He got out in his 50s with no law license and no network. Today his largest coaching client is a billion-dollar distribution company.

“I’m also a recovering lawyer,” Paul says, maybe thirty seconds into the call.

He lists it the way you’d mention a hobby. “I practiced labor law in the city of Chicago for 30 years. I’m also an ex-felon. I went to prison for five and a half years for committing white-collar crimes.” Then he keeps moving, smooth, like the prison sentence was one bullet on a résumé he’s read aloud a hundred times. “Got out in 2001 and decided, since I could no longer practice law, to start a coaching business.”

“Wow,” I say. And then again, because the first one didn’t cover it. “Wow.”

I’d come in with the question I usually save for people who’ve made a hard pivot — the one about limiting beliefs, about what they had to unlearn. I start to ask it. Paul cuts the frame out from under me before I finish.

“When you talk about limiting beliefs, I have a different term for it,” he says. “I call it blind spots.”

The distinction matters more than it sounds. A limiting belief is something you hold. A blind spot is something that holds you, and you can’t see it doing the holding.

“Everybody has blind spots,” Paul says. “They’re called blind spots because we don’t see them, but everybody else does. And every blind spot has a trigger attached to it, and if you don’t know what your trigger is and you don’t know what your blind spots are, you are primed to be manipulated by the world. You will not be able to choose your own course because somebody else will choose it for you.”

His own blind spot was the size of a courtroom. “I had an extraordinarily large ego. I truly believed I was the smartest guy in every room.” He’s not bragging when he says it — he’s diagnosing. The ego came from winning, and the winning came easy, and that was the trap. “Once you become successful, you start to live in your own echo chamber, and people will surround you in that echo chamber doing exactly that, continuing to tell you how good you are. At some point, you’ll believe it. Once you believe it, then you start to fail.”

At trial, they called him Mad Dog. “I would do whatever was necessary to win,” he says. “Unethical behavior was fine with me. I just looked at it differently.” He was good. He was also bored. A trial lawyer, he tells me, is an adrenaline junkie — a performer in a room with a referee and an opponent, and he loved the performance. The problem was everything between performances. “When you’re not at trial, when you’re doing preparation, that’s not adrenaline, that’s drudge, and I hated it. So I started to seek adrenaline, and I got it from my clients, who were not nice people, to be kind.”

They were criminals. Good ones. “Good grifters, they find your blind spots and your triggers immediately, and they pressed mine right away.” What they found was a man from a broken home who wanted to belong. They gave him a group. “But the initiation fee,” Paul says, “was committing crimes.”

He paid it 33 times.

There’s a scene he tells next that I keep turning over after the call ends.

Two trials. The first ended in a hung jury. The second convicted him. He’s standing in front of the sentencing judge, looking at seven years, and the judge offers him a deal — a way to cut the sentence by twenty percent. A year and a half, maybe two years, back. All he has to do is two things. Admit he committed the crimes. And help the prosecutor go after the men who committed them with him.

“And my answer to both of those was no,” Paul says.

He’s already convicted. He’s already going to prison. The math is not subtle — two years of his life, free for the taking. He turns it down anyway, and he tells me exactly why, and the why is the whole man in two sentences. “First, I could not admit I was wrong and got caught. Second, I could not give up the people who were in my group.”

The ego that made him a felon followed him all the way to the chair in front of the judge. The blind spot doesn’t care that you’ve already lost. It just wants to keep you from saying the words.

What broke it wasn’t the sentence. It was the traffic.

For the first two and a half years inside, Paul ran revenge fantasies. He was going to get even with everyone who put him there. He’d accepted no responsibility for any of it. And then he started noticing the men who’d already served their time and walked out — coming back. Returning. To prison.

“That shocked me,” he says, “because why would anybody wanna come back to prison? It’s a terrible place.” He’d watched freedom get taken from him without understanding what it weighed until he saw other men volunteer to lose it again. “When they started coming back, I realized that if I did not change, I was going to become a career criminal, because I would return to exactly the same situation I had left.”

He has a theory about this now, built from the inside. “If you have blind spots and triggers, something has to break the pattern, because otherwise there’s no reason for you to change.” For most people the something never arrives, and they stay the same until they die. For Paul it arrived as a turnstile of returning men, and it was enough.

Here is the part that should not work and somehow does.

A 50-year-old ex-felon walks out of federal prison with his law license revoked — thirteen years before he can even apply to get it back. He has, by his own accounting, narrow options and a personality that has never played well with others. So he reaches for the only tools he kept: he can tell a story, and he has failed at the highest possible level and survived it.

He decides to coach. But coaching, as it’s usually sold, makes him wince. “The concept of coaching, to me, always felt too soft,” he says. “And that’s not who I am, and therefore, that’s not how I could coach.”

What he reached for instead, he found in a book he read in prison. In medieval courts, the king was anointed by divine power, which meant challenging the king was heresy, which meant death. “The one exception to that was the fool,” Paul says. The jester in the gaudy outfit, jumping and dancing at the foot of the throne — we remember him as entertainment. He was something else. “Because they were seen as being crazy, they had an exception to the rule of being able to tell the king the truth. So that psychological safety allowed them to tell the king when they were behaving badly or making a bad decision.”

That, Paul decided, was the job. “I’m going to present myself as that person that cares enough about you to give you the gift of truth.” The branding wrote itself. The No BS Executive Coach isn’t a slogan about being blunt. It’s a man who spent 30 years living inside an echo chamber appointing himself the one voice in the room allowed to puncture someone else’s.

His first proof that it might work came as a reference, or rather two of them. Within two years of getting out, Paul asked a client to vouch for him. The client offered a choice. “He said, ‘The first one is, Paul’s an acquired taste, like cyanide.’” Paul laughs telling me this. “I said, ‘I don’t think I’m gonna use that one. Give me the second one.’”

The second one became his entire philosophy. “Paul is a Sherpa. He will get you to the mountaintop, but he will not carry your pack.”

He means it structurally, not just spiritually. Paul puts half his fee on the outcome. A one-year contract, goals set together, and if the year ends without those goals met, he collects only half his compensation. “I believe I have to have skin in the game,” he says. “If I don’t have skin in the game, then I’ll let you off the hook. If my money’s at stake, I’m gonna put my boot up your tail if you’re not doing what you’ve agreed to do.”

I tell him this is, whatever else it is, excellent positioning — clear about who he’s for and unbothered by everyone else. He agrees without flinching. “If you don’t like the taste, I’m okay with that. It’s not gonna work, I don’t wanna take your money, and I don’t wanna waste my time.”

He is not a life coach. He says this twice, in case I miss it. “I’m a performance coach. I get hired to improve performance, and I will push you to the edge. I will not accept mediocrity.” His clients are already successful — that’s the point, he says, that’s how they can afford him. The work isn’t getting them from struggling to fine. “Everybody can be high-performing,” he says. “That’s no longer the goal. The goal is you wanna be world-class. World-class requires a much different set of requirements and effort.” Most people stop short, comfortable, well-paid, respected. He calls that the comfort zone and tells them, gently, that they’ll never get better inside it.

I ask him what he actually sees when a new executive walks in the door. The answer comes fast, like he’s been waiting for the question.

“They are trying to do too much too soon to make that impression that they believe is necessary to convince the person who put them in the position it was the right choice,” he says. They don’t breathe. They don’t listen. They invent problems so they can solve them. Paul has a 90-day program he runs new executives through, and the first instruction is always the same: slow down.

“Start to talk to the people,” he says. Mine what’s already there before you decide what to build on top of it. Most new leaders got promoted for being doers, and now they’re suddenly supposed to lead — a different skill set entirely. The instinct to do more, faster, is the very instinct that will bury them.

Then he gets to the part I don’t expect. He talks about sleep. About exercise. About family time. “If you’re not gonna take care of yourself physically and mentally, I don’t want you in my program,” he says. He runs a monthly audit — a full 24-hour walkthrough of how his clients spend their time and energy. He wants to know where the hours go. Travel, he tells me, is the worst productivity suck in corporate life. And family gets sacrificed first, always. “People who are promoted sacrifice family first, and that is a short-term — just a — it’s an ignorant way to look at it,” he says. “Your family is your support base outside of work. They are the ones that you should care about more than the job, so don’t shortcut them.”

He advocates for two phones — work and personal — and for turning the work phone off. “That freaks people out,” he says, and something in his voice suggests he enjoys the freaking out. “There’s this thing called voicemail. You’d be shocked how it works.”

The mechanism underneath all of it is the same one that saved him in prison. Something has to matter more than your ego. Something has to break the pattern. “If you’re still self-centered, there’s no reason to change,” he tells me. “It’s when you suddenly realize the impact you’re having on others that gives you the necessary strength to break the pattern.” For his clients, that something is usually their family. For Paul, it was the men coming back through the gates.

I ask him why the people at the very top — the ones who answer to no one but a board — are the ones who hire coaches. He gives me the line that reframes the whole conversation.

“The more successful you are, the more you need a coach.”

Then he reaches back across two thousand years for the picture. A conquering general gets his parade through Rome, the loot and the prisoners marched in front of him, the general himself in a gold chariot behind six white stallions. And riding in the chariot with him, the entire length of the procession, a slave. The slave has one job. “To continually whisper in the general’s ear,” Paul says, “’You are but a man.’ Because that type of success will overwhelm you and start to convince you that you are more than a man, and that means you think you’re infallible.”

That’s the chariot Paul rode for 30 years with no one whispering anything. The echo chamber had no slave in it. Everyone in there told him he was the smartest man in the room, and eventually he believed them, and then he committed 33 crimes and told a judge he’d done nothing wrong.

So he built the thing he never had and rents it out by the year. The man who could not say I was wrong to save two years of his own freedom now makes his living saying it for other people, before the parade, while there’s still time to climb down from the chariot.

It’s an acquired taste. He’s the first to tell you. He’s also, somehow, the only one in the room allowed to.

Guest Bio: Paul Glover

Paul Glover is the No BS Executive Workplace Coach at Paul Glover Coaching, where he works with C-suite leaders and high-performing executives across the United States on performance, accountability, and organizational resilience. Rising to prominence over more than two decades of coaching work following a complete professional reinvention, he became known for a performance coaching model built around blind spots, outcome-contingent fees, and a refusal to allow clients the comfort of self-deception. His largest active client is a billion-dollar distribution organization.

Previously, Glover spent 30 years as a labor employment trial attorney in Chicago, earning a reputation as an aggressive courtroom litigator. His legal career ended in 1995 when he was indicted on 33 counts of white-collar crimes — including kickbacks, bribery, and tampering with government witnesses — and subsequently sentenced to federal prison. He refused to cooperate with prosecutors to reduce his sentence, and served approximately five years before beginning what would become a second career launched from scratch in his fifties.

Released in 2001 with his law license revoked and ineligible for reinstatement for 13 years, Glover rebuilt entirely as a coach, eventually building a national practice. He structures his engagements as one-year contracts with 50 percent of his fee contingent on clients achieving mutually defined goals — a model designed to give him skin in the game and eliminate the incentive to let clients off the hook. His coaching approach draws directly from his own reckoning with ego, echo chambers, and the moment accountability finally broke through.

Glover is the author of WorkQuake™, a book on surviving and thriving in the Knowledge Economy, praised by executive coach Marshall Goldsmith as agitating “the business status quo.”

Hey,

Thanks for reading this. I mean that. There's a lot of content out there competing for your attention, and you spent some of it here. I hope it was worth it. Even better, I hope it prompted you to think about something differently enough that you'd share it with someone who'd get something out of it too.

I started this podcast because tactics never stuck with me. What stuck were stories — business biographies, autobiographies, the decisions people made and why they made them. The principle only clicks once you know the story behind it.

So I built the thing I wanted to read. Every week I have two conversations with people who build in technology and product. Then I write the essay I wish I could find — one that puts you inside the conversation, through my eyes. What caught me off guard. What I kept thinking about after we hung up. Where the principle actually lives once you strip away the jargon.

I make this for myself first. If you read the way I do, you’ll want it too.

PS — If you want to pitch coming on the show, or you know someone I should talk to, shoot me an email at caden@hey.com with "January752" in the subject line so it gets past my filters. I'm not optimizing for famous guests. I'm optimizing for interesting conversations, even from people who aren't LinkedIn influencers.