AI for Founders with Ryan Estes

In the beginning, the seeds are everywhere and nothing is talking to each other.That is the exact feeling Jason Katz describes at the top of this What It Do check-in, and if you have ever built anything from zero, your stomach just dropped a little. You are running six initiatives. None of them touch. You are shifting attention left and right and none of it compounds. It is disorienting. And then, if you hold the vision long enough and cultivate the right things, the seeds start to grow like vines, they connect, and suddenly you are not running six disparate projects anymore. You are running one organism. Jason calls the moment it clicks a symphony, and he is not being modest about it.This one is different from a standard What It Do. Ryan and Jason both showed up on the same wave: two purple belts in their forties, both coming off a break, both watching years of quiet groundwork finally pay out at the same time. Ryan floats renaming the show "Stoic Jiu-Jitsu Guys in Their 40s Celebrating Their Wins," and honestly, that is the episode.The tension underneath the celebration is the good part. Jason spends the first half telling younger founders not to try to prove themselves, and then spends the second half admitting that his entire career was built on doing exactly that. He raised his hand for roles he had no business taking. He put himself in pressure cookers where the only exit was to shine. It worked, he is batting 1000 on do or die, and he has been in what he calls PhD education mode for fifteen straight years. He also says plainly that there is a healthier way to do it, and he did not take it.What emerges instead is a calibration: not zero pressure, not crushing pressure, but permanent low-grade discomfort. Always carry something a little heavy. Live in the gray. That is the version he would sell to a 25-year-old.Then there is the relationship math. Jason is currently in conversations about strategic partnerships that trace directly back to people he met a decade ago. Not networking. Not a CRM sequence. Just being a decent, disciplined, curious person for ten years and then picking up the phone. Ryan brings in a gem from Jeremy Wrathall, founder of Cornish Lithium: be interested, and be interesting. Interested carries the relationship. Interesting earns you the right to be interesting to somebody else. Grinding alone does neither.The travel stretch in the middle earns its keep. Ryan went to the Yucatán, climbed Ek Balam, swam cenotes, and came back with a founder observation dressed up as an anthropology lesson: the ancient Maya city has a temple, a state building, side houses, and a ball court. Drive fifteen minutes to the modern village and you find a chapel, a state building, side houses, and a soccer court. Twelve hundred years later, humans are still laying out the same city. Jason counters with a cave dive story that is either a spiritual experience or an OSHA violation depending on your risk tolerance.Ryan closes with a launch. Howdi went live this week at gethowdi.com, built on the back of Wildcast, his host-read advertising platform. The pitch: an autonomous AI sponsorship agent named Casey Taylor that sources real partnership opportunities for independent creators, starting with podcasters. Alpha is open.--kindlingsolutions.comhttps://www.linkedin.com/in/jasonkatz99/https://www.linkedin.com/in/estesryan/#1 AI Founder Newsletter!https://aiforfounders.coBuild your audience for life!https://inboxalchemy.co/If you're not AI native; you're not getting the job!https://ainativestudent.com/Get 35% off any supplement subscription with Momentous!https://crrnt.app/MOME/8RDrnXDdUse code RYAN30 to save $30 on your AI men's fashion stylist!https://taelor.style/Your podcast's autonomous AI sponsorship agent!https://gethowdi.com/

Brett Hurt has sold companies to IBM, taken one public on NASDAQ, and watched ServiceNow absorb his last one. He is telling you, on the record, that none of it made him happy.That is not a humble brag. It is a warning shot, and it lands differently coming from a man who has spent forty seven years writing code, six times as a founder, and who now backs more than 150 startups alongside his wife Debra.The conversation starts where every founder conversation is starting in 2026: Elon Musk told The Economist in July that money won't matter by 2036. Ryan asks Brett to place himself on the doom to utopia scale. Brett does not hedge. He puts himself at ninety five percent confident that humanity reaches what he calls the Age of Abundance for All, and then spends the next hour explaining why that confidence is the opposite of complacency.The risk, in his framing, is not the Terminator. It is the amygdala. Homo sapiens spent 99.9% of our time on this planet without electricity, and the scarcity software is still running. The laziest way to make money, Brett argues, is to hijack human biology: the mind, the body, the wallet. Social algorithms tuned for fear. Media tuned for dystopia. Profit routed over people. He is blunt about the fact that he has been a beneficiary of the system he is critiquing, which is exactly what gives the critique teeth.Then it gets personal. Ryan brings the Bodhisattva vow. Brett brings Bhutan, Buddhism, Judaism, Christianity, and Stoicism, and argues they all sink into the same root: the kingdom is found within. He talks about the Lamborghini on his childhood wall, the Lamborghini he eventually owned for ten years, and the exact amount of lasting happiness it produced. Zero. Not any of it.What did work, according to Brett: being on a mission that is genuinely yours, breaking out of the comparison machine, and doing the internal work to identify the programs running in your head before they run your company.The practical spine of the episode is a set of tools. Reading Doty. Building a plank from two minutes to twenty four minutes over seven years, one increment at a time, because patience is a trainable muscle and almost no American trains it. Buddying up with someone who will ask you what you're reading and how you're actually doing. Meditation as a 300 baud modem to the divine, psychedelics as broadband, and integration as the part that actually matters. And AI as the greatest tool ever built for the eternally curious, if you point it at the right questions.Ryan brings his own anger, his own grappling, his own dinner table in Denver with a daughter home from college and a son back from football practice, and names it: this is heaven. That is the whole thesis in one sentence.If you are scaling past a million and quietly wondering whether the finish line moves every time you get close, this one is for you.Books referenced: Love Conquers Fear by Brett Alexander Hurt, Into the Magic Shop and Mind Magic by James Doty, Why Buddhism Is True by Robert Wright, The Gospel According to Jesus by Stephen Mitchell, Tao Te Ching, Bhagavad Gita, How to Change Your Mind by Michael Pollan.Brett's book : https://www.loveconquersfear.orgBrett on LinkedIn: https://www.linkedin.com/in/bretthurt/--https://www.linkedin.com/in/estesryan/#1 AI Founder Newsletter!https://aiforfounders.coBuild your audience for life!https://inboxalchemy.co/If you're not AI native; you're not getting the job!https://ainativestudent.com/Get 35% off any supplement subscription with Momentous!https://crrnt.app/MOME/8RDrnXDdUse code RYAN30 to save $30 on your AI men's fashion stylist!https://taelor.style/Your podcast's autonomous AI sponsorship agent!https://gethowdi.com/

Your best people just got twice as fast. Congratulations. You have a problem.Ross Barnes has seen this movie from the projection booth. Twenty-five years in tech and advertising, ending as Global CTO of a WPP agency he helped scale from 15 people to more than 1,500 and from $80M to over $1B in revenue. Toyota. Lexus. EA Sports. British Airways. He sat on a global board and drove agile transformation across every function of a company growing faster than its own org chart could redraw itself.Then he left to build Galahad, and the tagline he chose tells you exactly what he learned on the way out: build the machine, protect the human.Here is the trap he watches companies walk into. A gaming client's engineering team was flying. Claude Enterprise across the org, shipping 10X features every week, genuinely at the frontier. And every one of those features needed legal sign-off, because gaming is a regulated business. Legal was not using AI. So the engineering team was not shipping faster. It was building a snowball and rolling it downhill into a team that had no way to catch it.That is the insight Ross has built a consultancy around. AI adoption is not man versus machine. It is your fastest team versus your slowest team. And if you only fund the fast ones, you have not created leverage. You have relocated your bottleneck to someone who never asked for it.His answer is almost aggressively unfashionable: raise the floor, not the roof. Get everyone to a baseline of capability before you go build a superhuman pocket of one department. The org that wins is not the one with the best AI users. It is the one with the fewest people who cannot keep up.Which is why his enablement sessions do not touch a tool for the first two sessions. In any leadership cohort, someone has been living in Claude for two years and someone has never opened it, and you cannot predict which is which from a job title. So you level set. Then, and only then, you ask the question almost nobody asks first: what do you actually want this to accomplish? Handing a team a seat and saying "crack on" does not produce adoption. It produces a room full of people quietly wondering whether they are training their own replacement.The conversation gets genuinely contentious in one place, and it is the best part of the episode. Ryan builds agents with personalities, accents, backstories, the full treatment, partly because a charming agent converts better. Ross builds agents with tone too, but draws a hard line at personification, and his reason is not squeamishness. It is accountability. The moment an agent feels human, you start grading it like a colleague, extending it the benefit of the doubt you would extend a person, and quietly outsourcing your own judgment to something that has none. It is a machine. Treat the inputs and outputs exactly like that. You are accountable for what you ask it and you are accountable for checking what comes back.Ryan pushes on the word "coercive." Ross pushes back, and the exchange surfaces the real question underneath consumer AI: where is the line between charming and manipulative, and who is responsible for drawing it? Ross's position is that the guardrails are the job. No overclaim. No false validation. Build them in before the agent meets a customer, not after.Galahad Group: https://galahadgroup.co.ukRoss Barnes on LinkedIn: https://www.linkedin.com/in/rossbarnesImNotOK: https://www.imnotok.ukHost and Showhttps://www.linkedin.com/in/estesryan/#1 AI Founder Newsletter! -https://aiforfounders.coBuild your audience for life! -https://inboxalchemy.co/If you're not AI native; you're not getting the job! -https://ainativestudent.com/Get 35% off any supplement subscription with Momentous! -https://crrnt.app/MOME/8RDrnXDdUse code RYAN30 to save $30 on your AI men's fashion stylist!https://taelor.style/Your podcast's autonomous AI sponsorship agent! - https://gethowdi.com/

Necessity Built the Company. Gratitude Kept It Alive.Brad Pitzele was collecting diagnoses faster than he could treat them.Autoimmune arthritis first. Then melanoma, caused by the very drugs prescribed to manage the arthritis. Then late-stage Lyme disease on top of both. He was in his late thirties and, in his words, he felt ninety-five years old. He could barely walk. Everything hurt. And every door in traditional medicine led to a version of the same trade: take the drug that might kill you, or live in the pain.So he went looking for a third road. He tried roughly two hundred things. None of them moved the needle.Then a doctor threw a Hail Mary and told him to look at oxygen. Hyperbaric was going to run $50,000 to $75,000, plus ninety minutes in a tube, seven days a week, for eight weeks. This was before remote work was normal. He could not afford the money or the hours. The alternative, exercise with oxygen therapy, was sold by a handful of companies at prices he described as high enough that he walked away from that too.Here is the moment the company was born, and it is not the moment you expect. Brad asked himself a single reframing question: "Well, if it didn't cost that much, would you do it?" Fifteen minutes a day he could do. So the recovering engineer, mechanical engineering degree, fifteen years in retail and e-commerce, went and built the thing himself. Sourcing parts at a volume of one is its own nightmare, and he did it anyway.A year later he was better. His doctor noticed, and asked if Brad would build systems for his patients. Brad said no. He was still recovering and did not want to set himself back. Six to nine months after that, he said yes, and One Thousand Roads was born.The name is the whole thesis. Everyone has their own road to walk back to health, and Brad refused to be the guy screaming that his was the only one. The other half of the name is a target: help one thousand people get out of the lonely, scary place he had been in.What follows in this episode is a founder story that is unusually clean of the normal startup noise. No round. No investors. No creditors breathing down his neck. He self-financed in increments so small they are almost funny. Ten masks. Sell the ten. Buy fifteen. Sell the fifteen. Buy twenty. He took nothing out of the business for four to five years. eBay first as a test, because standing up full e-commerce infrastructure before you have proof is how founders die. Then his own site once eBay's cut got annoying. Then SEO. Then paid ads. Then podcasts, YouTube, and a social presence his team had to drag him into.And the physiology underneath the product is genuinely the most interesting science on this show in a while. Your cells make energy two ways. With oxygen, they run the good engine. Without it, they fall back to a generator that produces a fraction of the output. Brad says your ability to use oxygen drops roughly 1% a year after age twenty-five, which means by fifty you have quietly lost about a quarter of your energy-making capacity. That shows up as brain fog, slower healing, more inflammation, and less life.One Thousand Roads: https://www.onethousandroads.comOne Thousand Roads on YouTube: https://www.youtube.com/@OneThousandRoadsHQBrad Pitzele on LinkedIn: https://www.linkedin.com/in/bradpitzele/The Dr Kumar Discovery, hosted by Dr. Ravi Kumar: https://drkumardiscovery.com/https://www.linkedin.com/in/estesryan/#1 AI Founder Newsletter!https://aiforfounders.coBuild your audience for life!https://inboxalchemy.co/If you're not AI native; you're not getting the job!https://ainativestudent.com/Get 35% off any supplement subscription with Momentous!https://crrnt.app/MOME/8RDrnXDdUse code RYAN30 to save $30 on your AI men's fashion stylist!https://taelor.style/Your podcast's autonomous AI sponsorship agent!https://gethowdi.com/

The Other 8,760 HoursYou see the person responsible for your health for somewhere between 10 and 20 minutes, once or twice a year. Netflix gets three hours a day. One of those two relationships has enough data to know you. It is not the one keeping you alive.That asymmetry is the entire business case for Lirio, and Marten den Haring has been building against it since 2019.He is not a healthcare lifer. He is an economist by training, MSc and PhD, who spent 25 years shipping AI products for financial services, law enforcement, and national security. Oracle. OpenText. Chief Product Officer at Digital Reasoning in Nashville. Then SVP Platform at Element AI in Montreal, the lab co-founded by Turing Award winner Yoshua Bengio. Six months into Canada, Nashville called him home, and Lirio was hiring.He joined as Chief Product Officer in May 2019 to turn a Series A business plan into an actual product. The MVP went live around January 15, 2020.Do that math. Six to eight weeks in the wild, and then the world closed.Lirio's product exists to drive people toward care. Care was shut. Then care reopened on 50 different state timetables into backlogs and staffing shortages, and nobody wanted more patient volume. Marten took the CEO chair in May 2021, in the middle of it. He describes 2021 through 2023 as a stretch where the team was openly asking whether product market fit simply was not there.What flipped it was not healthcare. It was everything else. Consumers spent three years learning that they could get anything from their couch, and then brought that expectation to their care. Suddenly a company built to communicate digitally, personally, at scale, was standing in exactly the right place.Today Lirio delivers more than 400 million nudges a year and reports outcomes that are hard to argue with: nudges 4x more effective than standard health messaging, a 60% reactivation rate on patients lost for three or more years, 50% HbA1c improvement in under six months, and $4.4 million in direct margin added through targeted interventions.The word "nudge" is doing a lot of work there, and Marten is careful about it. It has been called precision shoving. It has been called nagging. Ryan suggests it sounds like his wife on his fourth glass of wine. Marten's answer is the best line in the episode: if you want an automated version of your spouse, Lirio cannot help you.What Lirio actually does is treat every variable of a message as a decision. Not the content alone. The channel, the hour, the frequency, the framing, and whether the right recipient is even the patient at all. Sometimes the highest leverage nudge goes to the daughter who manages her father's medications.Liriohttps://lirio.com/Marten den Haring's team page at Liriohttps://lirio.com/our-team/marten-den-haring/Ryan Estes on LinkedInhttps://www.linkedin.com/in/estesryan/#1 AI Founder Newsletter!https://aiforfounders.coBuild your audience for life!https://inboxalchemy.co/If you're not AI native; you're not getting the job!https://ainativestudent.com/Get 35% off any supplement subscription with Momentous!https://crrnt.app/MOME/8RDrnXDdUse code RYAN30 to save $30 on your AI men's fashion stylist!https://taelor.style/Your podcast's autonomous AI sponsorship agent!https://gethowdi.com/

The Smartest Model on the Planet Will Still Build You a House With No FoundationMike Vitez has been shipping software since before the word "agentic" meant anything. Ten years leading projects. A computer science background. Fifty plus products across three continents, by his studio's count. And a few months ago, he did something most experienced technical leaders refuse to do.He went back to the drawing board. Literally the planning table. He picked the architect's pencil back up."I haven't been coding for a while," he says on this episode. "Like, I wasn't the one who was writing the code, but my people. I needed a mindset change as well and go back to the real architecture part stuff. Not just reviewing it, but planning it."That decision, made in a moment of frustration with routines that had gone stale, is the hinge this entire conversation swings on. Because Mike is now a member of the Claude Partner Network, running an in-house runtime environment where AI agents handle testing, development tasks, and product planning. He has automated quality control on every single commit. He has run forty-plus agents in parallel to build a product landscape in days instead of months. He is, by any reasonable measure, all the way in.And his central warning is this: AI can save you the cost of a low-level code developer. It cannot save you the cost of an architect."You can build a house without a foundation," Mike says, "but it won't be solid."That is not a caution against speed. Mike is aggressively pro-speed. His whole thesis is that MVPs are now trivially fast and you should rush to market, get users, and iterate. The caution is against speed without structure, which is a different animal entirely. It does not prevent collapse. It schedules it.Ryan pushes on the obvious founder question: if you use Claude and I use Claude, what exactly am I paying you for? Mike's answer is one of the cleanest articulations of the AI-era consulting value proposition we have had on the show. Go to Claude and say "build me something," and it will build you something. It might even work. But can you find the bugs? Can you make it scalable? Can you still add the fourteenth feature without the whole thing coming apart in your hands? "Most of the people cannot," he says, "because if you don't plan it out right, that's where the real engineering knowledge comes into the picture."Saturnia Design: https://www.saturniadesign.com/Mike Vitez on LinkedIn: https://www.linkedin.com/in/mikevitez/https://www.linkedin.com/in/estesryan/#1 AI Founder Newsletter!https://aiforfounders.coBuild your audience for life!https://inboxalchemy.co/If you're not AI native; you're not getting the job!https://ainativestudent.com/Get 35% off any supplement subscription with Momentous!https://crrnt.app/MOME/8RDrnXDdUse code RYAN30 to save $30 on your AI men's fashion stylist!https://taelor.style/Your podcast's autonomous AI sponsorship agent!https://gethowdi.com/

Rob Collie spent 30 years inside the machine, and AI still scared himHe was there in 1996, a fresh Vanderbilt grad walking into Microsoft. He led the business intelligence work inside Excel. He was a founding engineer on what became Power BI. He wrote three books about it and, by his own account, sold more than 92,000 copies. If anybody had a right to shrug at the next wave, it was Rob Collie.Then ChatGPT landed, and the guy whose entire career was telling computers what to do realized he ran the exact kind of company AI eats first. A data and BI consultancy. Code, scripts, formulas. Easy mode for a language model.By late 2024 he calls it dread. Not curiosity. Dread. And here is the part that makes this episode worth your commute: he did not fight the fear, he followed it. What he found on the other side was almost insultingly simple. AI success is not an AI problem. It is a data problem and a traditional software problem. The thing you already know how to do.That discovery became Fair Game, his fourth book, out now, and it is aimed squarely at the person who is not getting briefed. Because that is the real divide Rob names on this episode. If you run a Fortune 500, the hyperscalers are in your office with slide decks because they want to keep you. Everyone from mid-market down is left to guess while the labs sprint past them, too busy racing each other to slow down and teach anybody anything.Meanwhile the internet offers you two flavors of fear. The hype side needs you scared so you buy the course. The doom side needs you scared so you click the next video. Rob's read is blunt: both are engagement strategies, and neither one is running a business.What he offers instead is a diagnosis. When you sit down with vanilla Claude or vanilla ChatGPT and try to do real, repeated business work, you hit a wall, and you blame yourself. You should not. That model knows a staggering amount about the Roman Empire and nothing about your company. It is a PhD in everything and a brand new hire at your business. So you spend an hour explaining your world to it, get 80% of the way there, grind on the last 20%, and then the chat ends and all that context evaporates. Rob has a name for the feeling. Bot sitting.The fix is not a better prompt. It is grounding. Rob's own hello-world moment was connecting Claude Desktop through MCP to a Notion knowledge base holding nothing more exotic than his company's brand guidelines. Suddenly the model was not just more accurate. It felt more confident, more willing to take a creative swing. Same model. Different context. He describes it like the LLM got smarter, and functionally, it did.Ryan pushes on the entry point, and Rob's recommendation for anyone still on the sidelines is refreshingly unglamorous: open Claude Cowork, make a folder, and start letting a project accumulate its own memory. Motivation, history, guidelines, goals, all injected on hello. No engineering degree required.https://fairgamebook.ai/https://p3adaptive.com/https://www.linkedin.com/in/robcollie/https://www.linkedin.com/in/estesryan/#1 AI Founder Newsletter!https://aiforfounders.coBuild your audience for life!https://inboxalchemy.co/If you're not AI native; you're not getting the job!https://ainativestudent.com/Get 35% off any supplement subscription with Momentous!https://crrnt.app/MOME/8RDrnXDdUse code RYAN30 to save $30 on your AI men's fashion stylist!https://taelor.style/Your podcast's autonomous AI sponsorship agent!https://gethowdi.com/

Tarun Raisoni built a data center company to roughly $400 million in trailing sales without taking a dollar of outside capital, sold it to a Fortune 500 for $217 million, then walked away from the boat and the fishing rod to start over. His answer for why is four words long: "exits are just a number."What he started instead is Gruve, and what he came on the show to argue is the most uncomfortable idea in enterprise AI right now.Here it is. In the cloud era, your data went somewhere else and stayed exactly what it was. A provider could store it, back it up, and hand it back to you unchanged, because storage does not understand. The AI era broke that. When you push high quality proprietary data into a frontier model, the data can be parameterized, and the intelligence inside it can escape. Tarun's question is not who owns the file. It is who owns the understanding.He calls it the intelligence boundary, and nobody has drawn it yet.Ryan pushed on the obvious nightmare version. You install Claude Code across your team, they ship ten times faster, you feed your financials and your roadmap into it, and then Anthropic launches Claude for Teachers into the exact market you were building for. Tarun did not flinch. He reached for Amazon Basics instead, which is the cleanest available precedent: watch what sells on your platform, build your own version, undercut the seller. Except now the platform is not a marketplace. It is the thing your team talks to all day.His prescription is not "go local and hide." It is a hybrid routing model, and he is blunt that where you draw the lines depends entirely on your business. Some workloads belong in a frontier model because the data gravity and the IP density are low. Some workloads you fine-tune inside your own ecosystem on a large open source model. And some workloads you do not let a frontier model see, not the data, not the metadata, not even the shape of the algorithm.Then the economics arrive, and this is where founders should sit up. Tarun's word is tokenomics, and his point is that the bill you are staring at right now is not a real bill. It is a heavily investor-subsidized bill. What you paid for ChatGPT or Claude two years ago versus one year ago versus today reflects a subsidy that is being slowly withdrawn. Ryan told the story of a founder friend who worked himself into a hospital bed in January because he was convinced the tools were about to be yanked. Tarun's answer was calmer and more useful: stop worrying about the rug pull and start measuring whether the spend is actually producing measurable productivity. Software engineering is measurable. Most other things in your company are not yet.The go-to-market story is genuinely unusual. Enterprises are notoriously brutal to sell into, so Gruve bought its way to a standing start, acquiring NetServ, Lumos Cloud, and SecurView to import talent, partnerships, and customers in one motion. Cisco is both a channel partner and an investor. Reception from the inherited accounts, in his telling, was not resistance but relief, because those customers were being offered outcomes instead of headcount and hours.Gruve: https://gruve.aiTarun's Forbes Technology Council article, "The Next Enterprise Won't Just Use AI, It Will Own Its Intelligence": https://www.forbes.com/councils/forbestechcouncil/2026/07/15/the-next-enterprise-wont-just-use-ai-it-will-own-its-intelligence/Iron Lady Foundation: https://ironladyfoundation.orgTarun on LinkedIn: https://www.linkedin.com/in/raisoni/https://www.linkedin.com/in/estesryan/#1 AI Founder Newsletter!https://aiforfounders.coBuild your audience for life!https://inboxalchemy.co/If you're not AI native; you're not getting the job!https://ainativestudent.com/Get 35% off any supplement subscription with Momentous!https://crrnt.app/MOME/8RDrnXDdUse code RYAN30 to save $30 on your AI men's fashion stylist!https://taelor.style/Your podcast's autonomous AI sponsorship agent!https://gethowdi.com/

Every animal on earth runs on four drives. Humans have a fifth. The question is whether AI feeds it or buries it under a pile of chat windows.That is the cold open Ryan Estes is bringing to a Denver AI panel next Wednesday, and it is why this week's What It Do with Jason Katz, co-founder of Kindling Solutions, is bigger than a build in public check in.Ryan walks through his whole panel hosting playbook live, and the metaphor is a DJ booth. Five panelists are five tracks. You mix them, you watch the room. You know when to loop somebody's best point and when to bring the fader down on a rambler. Jason's contribution: a bullhorn. One short honk to underline a great answer, three seconds to shut somebody up.Then Jason pushes back on the hook itself, the most useful sixty seconds in the episode. "Divine" is ambiguous, he says, and worse, it is divisive. Rewrite it as "does AI make us more or less human" and everyone in that room can answer it. Ryan takes the note on the spot.The heart of the episode is Jason's field report from two CEO meetings in one week, both at different places on the AI maturity curve. One has visionary leadership, sharp balance sheet instincts, and almost nothing underneath it operationally. The systems audit came back empty. The other has already built impressive end to end AI systems and has the opposite problem: a pile of tools with no shared brain, and a CEO asking how to fuse them into one operating system.Jason's read is that everyone lands in the same place. Every company will run on a custom operating system with AI inside it, and the spread between companies right now is the widest it will ever be. That spread is the entire market.Then Ryan drops the question he asks every guest: what AI automation would you be lost without? The answer is almost always the morning brief, the thing that reads your Slack, calls, calendar, and inbox and hands you five lines with your coffee. Jason's caveat matters. The brief is a beautiful entry point and also the ceiling for any company that has not fixed its operational leadership first. Without executive buy in, you are delivering a nicer looking version of the same chaos.From there: model routing, tokenomics, compliance, and the quiet fear that frontier labs will eat the tools built on top of them. Ryan uses Claude for Teachers as the case study. Jason's answer is not to defend the model layer. It is to own the layer nobody can copy. Code is democratized. Anyone can build a thing. The value is understanding the engine: workflows, business logic, and how they connect to strategy. That understanding is the moat.The best structural insight of the episode: an IT department is three buckets. Services, meaning hardware, permissions, users, servers. Data, meaning governance, security, and a model anyone can query. And applications, meaning custom software. In 2021, bucket three meant six months from "we need a thing" to a signed proposal, and up to five hundred thousand dollars for an iPhone app. That timeline collapsed to nearly zero. The reason IT owned it did not. As Jason puts it, three years ago your guy running Claude Code would never have been near building your company's software. He is building it now. Governance did not stop mattering because the build got fast.Kindling Solutions - https://kindlingsolutions.comJason Katz on LinkedIn - https://www.linkedin.com/in/jasonkatz99/https://www.linkedin.com/in/estesryan/#1 AI Founder Newsletter! -https://aiforfounders.coBuild your audience for life! -https://inboxalchemy.co/If you're not AI native; you're not getting the job! -https://ainativestudent.com/Get 35% off any supplement subscription with Momentous! -https://crrnt.app/MOME/8RDrnXDdUse code RYAN30 to save $30 on your AI men's fashion stylist!https://taelor.style/Your podcast's autonomous AI sponsorship agent! - https://gethowdi.com/

Your Website Is About to Become a Line ItemMatt Hassett spent seven years making byloftie.com beautiful.Now he is fairly sure that beauty is depreciating.Not because the design is bad. Because the customer is changing shape. Shopify says AI-driven traffic to its stores grew roughly 8x year over year in Q1 2026, with orders from AI search up nearly 13x. Loftie's post-purchase survey went from 1.5 percent AI attribution to 3 percent in six months. That is still small. That is also what small looks like right before it isn't.Here is the part that should scare every DTC founder. Ask an AI for a sleep product and you never land on a homepage. You get a list. Six items. Your brand is one word next to a category tag. Every hour of art direction and every bit of story that justified your premium folds into a row in a table.The row is the problem. Matt puts a number on it: Amazon costs Loftie roughly fifteen points of contribution margin versus direct. If agentic commerce quietly rebuilds Amazon inside every chatbot, that is not a distribution change. That is a repricing of your entire business.So he did something more interesting than panic. He pointed the same technology at his own books.Loftie had a rule buried in its email platform, written years ago by someone being responsible about GDPR, blocking welcome emails to the EU and UK. Sensible then. Loftie did not sell there. Then tariffs reshaped the business and international became roughly half of sales. Nobody updated the rule. Half of new customers were signing up for a welcome sequence they would never receive. No dashboard flagged it. It just sat there costing money until someone thought to look.Another brand poured spend into one narrow audience while Meta now rewards broad targeting. Another ran two creative families where one beat the other 2x, and funded the loser for months. Matt's advice was blunt: stop making those ads, you are losing money.None of it is clever. That is the point. These are not insights, they are inventory. Money already in the building that nobody had time to walk down and find.Which is how Deliberate got built backwards. Matt was not trying to start a software company. He was trying to keep five people employed through a tariff year without hiring a sixth he could not confidently pay. So he handed the rote work to agents, gave each one a name, a lane, and a personality, and let them argue. Zelda runs paid media. Maggie runs finance and pushes back when Zelda wants to spend. Louisa listens to customers. Seven more cover ops, Amazon, wholesale, people, and the site. Ten in all, $7,500 a month.The naming is not only a gimmick. Agent teams behave like human ones: they get better when perspectives differ. One optimist, one pessimist, one who always asks about the money. Make them identical and you have built an expensive echo.Underneath it is the thesis Ryan keeps circling: your taste is not data. You will build the beautiful ad and it will die, and a stick figure with a red X will convert like a slot machine. The businesses winning are not the ones with the best instincts. They are the ones willing to be corrected in public, by a machine, weekly.Both things. At the same time. That tension is the episode.https://byloftie.com/https://deliberatestudio.com/https://www.linkedin.com/in/matthew-hassett/https://www.linkedin.com/in/estesryan/#1 AI Founder Newsletter!https://aiforfounders.coBuild your audience for life!https://inboxalchemy.co/If you're not AI native; you're not getting the job!https://ainativestudent.com/Get 35% off any supplement subscription with Momentous!https://crrnt.app/MOME/8RDrnXDdUse code RYAN30 to save $30 on your AI men's fashion stylist!https://taelor.style/Your podcast's autonomous AI sponsorship agent!https://gethowdi.com/

Fourteen terminal instances. Fifty-two tabs across three browsers. Six customers, a dozen half-finished workflows, and a Friday morning where your brain simply refuses to boot. That's not leverage. That's a slow-motion crash dressed up as productivity.This week, Ryan sits down with Ilan Man, founder and CEO of Paradox Machines, an AI-enabled data services company helping mid-market and private equity-backed businesses finally get real value from their data without the enterprise price tag. Ilan spent nearly 20 years in data before founding anything: statistician, actuary, data scientist back when it was "the sexiest job in America," data engineer, data leader, and consultant at an exited firm. Four months ago he put on the founder hat for the first time, backed by Infinity Constellation, the AI-native holding company founded by CEO Brennan Pothetes and Chairman Francis Pedraza that just raised a $24M Series A.And here's the paradox his company is named for: AI and data are everywhere and nowhere at once. Every conference, every feed, every board meeting is drowning in AI talk. Meanwhile, actual executives will tell you they don't trust their own reports, their pilots died on the vine, and they're on their third AI strategy deck. Ilan built Paradox Machines to close that gap for the companies that can't afford a Palantir, a Snowflake stack, and a full data team, especially portfolio companies that need to be exit-ready in three to five years.But the deeper conversation is about the thing nobody puts in their LinkedIn victory lap: sustainability. Ilan is running a small senior team, reportedly serving half a dozen customers just months in, and he's blunt about the cost. Always-on agent swarms are mostly a novelty. Velocity without a moving product roadmap is theater. And your customers, without exception, want you, not your bot. Zero percent of them have ever asked for the agent to run the meeting.Ryan opens up about his own fix: killing calls on Mondays, Wednesdays, and Fridays, stacking deep work, and trading short-term speed for the ability to close the laptop at 6 PM with enough energy left to cook dinner and put on a record. Ilan counters with quarterly self-audits, treating your own workflow like a system you run analytics on.If you're excited about AI but exhausted by the hustle culture version of it, this episode is your permission slip to build something durable instead.https://www.paradoxmachines.comIlan Man on LinkedIn: https://www.linkedin.com/in/ilanmanhttps://www.linkedin.com/in/estesryan/#1 AI Founder Newsletter!https://aiforfounders.coBuild your audience for life!https://inboxalchemy.co/If you're not AI native; you're not getting the job!https://ainativestudent.com/Get 35% off any supplement subscription with Momentous!https://crrnt.app/MOME/8RDrnXDdUse code RYAN30 to save $30 on your AI men's fashion stylist!https://taelor.style/Your podcast's autonomous AI sponsorship agent!https://gethowdi.com/

Trust is the most expensive thing in business, and nobody bills you for it until it is gone. Four nine-figure receivables frauds hit the industry in a single year, and every one of them traces back to the same quiet failure: a lender who built a relationship, got comfortable, and stopped checking. Anthony Eden watched that pattern from inside one of the world's most secretive private equity shops, and he decided the fix was not more clerks making phone calls. It was agents making thousands of them.Anthony is the founder of Iridium (iridiumcredit.com), a company that automates the entire lifecycle of invoice finance for lenders: verification, fraud detection, collections, and cash reconciliation. In most of the world, borrowing against invoices is the default way businesses get short-term cash. In Latin America and parts of Europe it runs around 15% of GDP by Anthony's telling, with Belgium as high as 22%. In the US it is roughly 2%, because without government e-invoicing registries, verifying that an invoice is real means emails, phone calls, and logging into accounts payable portals by hand, at a cost Anthony puts at about $22 per invoice. Iridium replaces that grind with email agents, voice agents, and browser agents, so lenders can profitably finance invoices they used to turn away, and the 58% of SMBs who Anthony says get denied the credit they seek finally get a shot.The origin story is just as good as the product. Anthony started as an intern at Cerberus Capital Management, came back to build credit underwriting automation alongside PhD scientists who wrote his college textbooks, watched it print millions for European banks, and realized someone was going to compress financial services into a hyper-efficient market. He decided that someone would be him. He joined an accelerator a month late, teamed up with co-founder Preesha Gehlot, an ex-Bloomberg and Microsoft machine learning engineer who published two AI papers before graduating from Imperial College London, and closed their first customer in a two-week sales cycle. Today the four-person, fully Claude Code pilled team is packing for New York with a contracted book of revenue and a pipeline Anthony describes as massive.What does Iridium do? Iridium (iridiumcredit.com) automates invoice verification, fraud detection, collections, and cash reconciliation for invoice finance lenders using email, voice, and browser AI agents.How does invoice factoring make money? A lender advances roughly 80 to 95% of an invoice, collects the full amount when it is paid, returns the remainder minus a 1 to 3% fee, which annualizes to a 10 to 15% APR product per Anthony Eden.Why is invoice finance small in the US? The US lacks government e-invoicing registries, so verifying invoices is manual and costs lenders about $22 per invoice, per Anthony Eden, pricing out small invoices entirely.How do AI agents detect invoice fraud? Document forensics, IP and location checks on emails, domain checks, portal verification via browser agents, and network-level detection of double-pledged invoices.Who founded Iridium? Anthony Eden and Preesha Gehlot, both Imperial College London alumni, after Anthony built credit underwriting automation inside private equity.https://www.iridiumcredit.com/https://www.linkedin.com/in/anthony-eden/https://www.linkedin.com/in/estesryan/#1 AI Founder Newsletter!https://aiforfounders.coBuild your audience for life!https://inboxalchemy.co/If you're not AI native; you're not getting the job!https://ainativestudent.com/Get 35% off any supplement subscription with Momentous!https://crrnt.app/MOME/8RDrnXDdUse code RYAN30 to save $30 on your AI men's fashion stylist!https://taelor.style/Your podcast's autonomous AI sponsorship agent!https://gethowdi.com/

It is midnight in a mountain town. You have been driving for nine hours, your kids are asleep in the back, and the hotel lobby is empty except for a bell on the counter and a sign that says "ring for service." Nobody comes. Now imagine instead a human-sized hologram greets you by name, checks you in, and books your fishing guide for the morning. That is not science fiction. That is already running in dozens of hotels across Europe.Ryan sits down with Filip Linek, founder of FLAE Robotics and creator of BE-A, the holographic AI receptionist built by a hotelier who could not hire humans fast enough. Filip's story is the founder arc in miniature: he built packaging distributor OSKAR PLAST from 1997, sold it to global giant Bunzl in 2014, tried retirement, lasted three months on the golf course, then bought two hotels in the Czech Republic and discovered the industry's dirty secret. Hospitality is drowning. Hoteliers tell him the same thing every month: we hire anyone who shows up to the interview, if they show up at all.So he built the receptionist he could not find. BE-A is not a chatbot bolted onto a website. She handles the full guest journey across email, WhatsApp, phone, and soon a human-sized holobox at the front desk, with a physical humanoid targeted for the end of 2027. She matches OTA prices within set limits, escalates to humans on demand, recognizes groups of guests and tracks each person, and gives hotels something they have never had: a full transcript of every guest conversation. Filip says the company is live in roughly 60 hotels, sitting at about $400K ARR, converting one in three demos, and preparing a Series A to enter the US market through, of all places, Denver.The deeper thread of this conversation is a contrarian bet: that guests will start to prefer AI as the first touch, because speed, accuracy, and availability beat a tired human at midnight. Filip is refreshingly honest about the limits too. He is a self-described skeptic on general-purpose humanoids, walking robots, and robot housekeepers. The front desk, he argues, is the one perfect use case: all communication, no locomotion.https://flaerobotics.aihttps://be-a.aihttps://www.linkedin.com/in/filip-linek-a70292318/https://www.linkedin.com/in/estesryan/⁠⁠_#1 AI Founder Newsletter! - ⁠https://aiforfounders.co⁠⁠Build your audience for life! - https://inboxalchemy.co/ If you're not AI native; you're not getting the job! -https://ainativestudent.com/Get 35% off any supplement subscription with Momentous! - https://crrnt.app/MOME/8RDrnXDd⁠Use code RYAN30 to save $30 on your AI men's fashion stylist! https://taelor.style/Your podcast's autonomous AI sponsorship agent! - https://gethowdi.com/

The happiest day of your founder life might be the emptiest. The wire hits, the champagne pops, and 90 days later the divorce papers get filed, the workouts stop, and you are staring at an earn-out agreement wondering why you hate the company that just bought yours.The official launch announcement:https://www.prnewswire.com/news-releases/rich--sassy-wealth-strategies-launches-qiretreat-a-china-expedition-for-leaders-and-changemakers-302817416.htmlThe invitation page:https://richandsassy.com/chinaCece Leung has watched it happen for more than 20 years. Born and raised in Hong Kong, she landed in Canada at 16 with one suitcase, taught piano and tutored math to get by, and clawed her way through the Big Four and Wall Street into a corner office, multiple CFO titles, and a string of IPOs. She spent nine months in dusty Chinese storage rooms hand-auditing paper contracts before AI could do it in seconds. She hit every number, then woke up rich and empty.So she burned the playbook. In January 2026 she launched Rich & Sassy Wealth Strategies, a New York advisory firm that pairs institutional-grade IPO and exit strategy with something almost no banker will touch: philosophical counseling. Alongside advisor Dr. David Kaye and her brother Kevin Leung, who leads the firm's invitation-only QiRetreat expeditions in Guangdong, China, Cece helps founders answer the question that no term sheet covers: who are you when the hustle finally stops?In this conversation, Ryan and Cece get into why deals take 18 to 36 brutal months and leave everyone too burned out to plan what comes next, why smart founders sign terrible earn-outs, why the shortest post-exit break Ryan has ever heard of was three days and the longest was nine months, and why Cece thinks movement, nature, and a Sunday morning coffee overlooking Manhattan beat any dashboard.https://richandsassy.com/https://www.linkedin.com/in/cscfo/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠_#1 AI Founder Newsletter! - ⁠https://aiforfounders.co⁠⁠Build your audience for life! - https://inboxalchemy.co/ If you're not AI native; you're not getting the job! -https://ainativestudent.com/Get 35% off any supplement subscription with Momentous! - https://crrnt.app/MOME/8RDrnXDd⁠Use code RYAN30 to save $30 on your AI men's fashion stylist! https://taelor.style/Your podcast's autonomous AI sponsorship agent! - https://gethowdi.com/

When China cut off rare earth exports, the American car industry came within two weeks of shutting down. Two weeks.That is not a hypothetical, that is the world we live in now, and Jeremy Wrathall saw it coming a decade ago.In 2016, Jeremy was a mining engineer and investment banker walking to work in London when a friend's comment about lithium in Cornish mine water sent him down a rabbit hole that would change his life. Everyone thought he was insane. Lithium? In Cornwall? The county famous for pasties and Poldark? But Jeremy knew two things most people didn't: the energy transition was going to need staggering amounts of critical minerals, and the West had voluntarily handed its supply chains to China because digging in the dirt wasn't glamorous enough for Wall Street.Ten years later, Cornish Lithium employs 100 people, has raised institutional capital from the National Wealth Fund, TechMet, and EMG, and holds the patents on one of the only lithium extraction technologies on Earth that China does not own and cannot switch off. The company is reviving a brownfield china clay pit at Trelavour, mining land that has been worked for 275 years, going deeper into rock nobody else bothered to look at. Cornwall itself has been mining for 4,000 years. The Bronze Age started there. Now the AI age might too.This conversation covers the two-week near-collapse of the US auto industry, why President Trump is invoking the Defense Production Act for minerals, how a $200 drone made the $2 million tank obsolete, why Jeremy handed the CEO seat to oil and gas veteran Jamie Airnes while keeping his hands on the wheel as Executive Chairman, and the outdoor clothing store failure that taught him to stick to his knitting. Plus: why he thinks Elon gets his billion robots, and why every single one of them needs what comes out of the ground in Cornwall.https://cornishlithium.com/https://www.linkedin.com/in/jeremy-wrathall-ba7891b/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠_#1 AI Founder Newsletter! - ⁠https://aiforfounders.co⁠⁠Build your audience for life! - https://inboxalchemy.co/ If you're not AI native; you're not getting the job! -https://ainativestudent.com/Get 35% off any supplement subscription with Momentous! - https://crrnt.app/MOME/8RDrnXDd⁠Use code RYAN30 to save $30 on your AI men's fashion stylist! https://taelor.style/Your podcast's autonomous AI sponsorship agent! - https://gethowdi.com/

Somewhere on a server right now, a striker who does not exist is deciding whether to cut left or right. Nobody scripted the choice. Not even the man who built him.That man is Tal Melenboim, a serial entrepreneur with more than twenty years of exits, patents, and AI ventures behind him, including Movota (sold to Bertelsmann AG), Score:Plug (acquired by Spil Games), VFR.ai, and Data+. His newest creation is Lega.bot, the first autonomous AI soccer universe: more than 20 teams, thousands of agents, each player with its own DNA, playing real 90-minute matches with outcomes nobody controls. Not a video game. Not fantasy soccer. Not generated highlight clips. A living league that runs 24/7, forever, launching right after the World Cup ends and the four-year soccer depression sets in.Tal walks Ryan through how he manages seven-plus simultaneous ventures without losing the plot, why he shares developers across projects and throws "founder dating" parties so his portfolio teaches itself, and why he bootstrapped the entire thing rather than pitch investors a dream they could not see yet. He also drops the line of the episode: every big unsolved challenge in your project is hidden value your competitors have not discovered. If you are suffering, you are early.https://lega.bot/https://www.linkedin.com/in/tal-melenboim/https://www.linkedin.com/in/estesryan/⁠⁠_#1 AI Founder Newsletter! - ⁠https://aiforfounders.co⁠⁠Build your audience for life! - https://inboxalchemy.co/ If you're not AI native; you're not getting the job! -https://ainativestudent.com/Get 35% off any supplement subscription with Momentous! - https://crrnt.app/MOME/8RDrnXDd⁠Use code RYAN30 to save $30 on your AI men's fashion stylist! https://taelor.style/Your podcast's autonomous AI sponsorship agent! - https://gethowdi.com/

Your website is lying to you. Right now, while you read this, visitors are hitting a broken form, bailing on a checkout button they can barely see, and bouncing off a page designed for someone else entirely. Eric Schneider built a company to catch every single one of those moments, and he built it without a dollar of venture capital.Eric is the co-founder of Cora, a website optimization and monitoring platform that tracks every button, form field, and component on your site, learns how real humans (and bots) actually behave, then rewrites the experience to convert them. One early customer added $20K per week in revenue, a figure Eric shares on air. Cora's bigger bet, full adaptation, reshapes the entire visual site per visitor persona, and Eric says his statistical models point to a 24X lift on yearly revenue, converting 75 to 85% of visitors instead of the classic 3%. These are Cora's own numbers, and they are audacious on purpose.But the product is only half the episode. Eric is one of the most distinctive builders in the Denver AI scene, a fine arts grad turned interaction designer turned bootstrapped founder who writes his product requirements documents from his shower, phone in one hand, coffee somewhere nearby, kids ages two and four safely on the other side of the door. He ships edgy demos weekly, open sources his utilities, controls Claude with tonal frequencies for fun, and still insists the most important product skill in the AI era is saying no.The conversation runs from the early days of the AI Clubhouse meetup (ten people and warm PBR) to a group now drawing 100 to 150 attendees a week, from AI on college campuses to humanoid robots doing blue collar jobs within three years, per a founder friend of Eric's. And it lands on the take that gives this episode its spine: stop training AI to act human. Make AI more AI. Make robots more robot.https://getcora.io/https://www.linkedin.com/in/ecschneider/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠_#1 AI Founder Newsletter! -> ⁠⁠https://aiforfounders.co⁠⁠Build your audience for life! -> https://inboxalchemy.co/ If you're not AI native; you're not getting the job! -> https://ainativestudent.com/Get 35% off any supplement subscription with Momentous! -> https://crrnt.app/MOME/8RDrnXDdUse code RYAN30 to save $30 on your AI men's fashion stylist! -> https://taelor.style/Your podcast's autonomous AI sponsorship agent! -> https://gethowdi.com/

A 6-person team just built in 3 months what took 18 months and $2 million the last time around. That's not a productivity story. That's a story about the ground shifting under an entire trillion-dollar industry.Tim Lidman knows consulting from the inside. He grew up in the collaboration industry: Webex before Cisco bought it, SuccessFactors before SAP bought it, then a decade helping run ThinkTank, the structured collaboration platform that Big Four firms used to run client workshops. When Accenture acquired ThinkTank's assets in 2021, Tim spent about four years operating at the partner level inside one of the biggest consulting machines on Earth. And what he saw was a workflow begging to be rebuilt: humans designing engagements, humans facilitating, humans synthesizing, and one poor analyst up until 2 AM cobbling together the PowerPoint.So he built Clyde, which launched April 7, 2026 at meetclyde.com. Clyde is what Tim calls AI-native collaboration: a workspace where you bring a real problem, collaborate with a library of AI advisors that act like human experts, pull in actual human stakeholders, and walk out with an aligned outcome and a usable deliverable. Not a wrapper. Not a chatbot bolted onto a legacy whiteboard. A guided system that extracts your true intent, because as Tim puts it, 99% of users don't know what they don't know about prompting.The results are early but loud: 1,300 users in the first month on a pure product-led growth motion, a fast-follow release shipping in June with adaptive workflows, and a customer base that already includes third grade teachers walking away with McKinsey-level curriculum plans. Everyone's getting a raise. Thanks, Clyde.Ryan and Tim also go deep on the founder condition in 2026: the guilt of stepping away from your desk, scheduling dedicated slots for original thought because AI can't invent new information, developers mourning the flow state as they become project managers of agent fleets, raising with extreme caution in a VC landscape where a Series A is the new pre-seed, and why Tim's kids get zero screen time while their dad builds frontier AI. Plus: heavy metal drumming, Suno experiments with his daughter Chloe, why Lovable's Anton Osika is the founder Tim admires most, and a charity using pediatricians as a distribution network.⁠⁠https://meetclyde.com ⁠⁠https://linkedin.com/in/timlidman ⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://inboxalchemy.co/ https://ainativestudent.com/

Jason Katz popped his LCL three weeks ago scrambling out of a leg entanglement, and honestly, that injury is the whole episode in miniature. You get excited, you move fast, you stand up into a hold you did not see, and something structural gives. In this What It Do check-in, Jason (co-founder of Kindling Solutions, back for another round) and Ryan trade war stories from the two weeks that turned both of their companies from build mode into go mode.Jason drops the concept that should be tattooed on every founder's forearm in 2026: built is not built to scale. Anyone can vibe code something that "works" in a single session now. Jason points to reports of vibe coders getting sued after losing company data through open-ended permissions, and he watches CEOs get star-gazed by AI demos, fire people AI cannot actually replace, then quietly rehire them. Kindling's answer is a governance layer: a way to let a client's internal Lovable and Claude Code tinkerers keep building while Kindling governs the builds it does not even touch. Operators first, then engineers. Jason claims his team has exited three companies at nine and ten figure outcomes, and that operating scar tissue is the product.Ryan, meanwhile, is in full sales dog mode. He restructured his entire week (calls only on Tuesdays and Thursdays, deep work on Monday, Wednesday, Friday) and promptly signed two newsletter sponsorship deals in one week: Momentous, the NSF Certified supplement company behind the grass-fed whey and creatine he already takes daily, and Taelor, the AI-plus-human-stylist menswear rental subscription that is about to give him a dramatic before-and-after wardrobe glow-up, per his daughter's demands.And the whole thing wraps with the two of them planning a Denver panel with Gabe Anderson and ID345's Danny Newman that may or may not end in a staged WWE brawl. Leopard Speedo has been threatened.https://kindlingsolutions.comhttps://taelor.stylehttps://www.livemomentous.comhttps://aiforfounders.cohttps://www.linkedin.com/in/jasonkatz99/https://www.linkedin.com/in/estesryan/

Most founders think the endgame is IPO or bust. Todd Furniss built a company that offers a third door: sell to someone who keeps your entire team, hands leadership three to five year employment agreements, and then drops patented AI into your operations like a turbocharger into a truck that's been stuck in third gear for a decade.Todd is the CEO and co-founder of AI Squared, formally AIAI Holdings Corporation, publicly traded on the Nasdaq under the ticker AIAI since May 14, 2026. The model is deliciously simple to say and brutally hard to copy: buy real operating companies with real revenue and real EBITDA, retain the management teams, and deploy what Todd describes as Nobel-nominated Transformational AI to create new products, amplify earnings, and redefine what the business can become. No pilots. No rip and replace. No layoff bloodbath. Todd says nearly a billion dollars of EBITDA is sitting in the acquisition pipeline, and here's the kicker: AI Squared didn't cold-call a single one of those companies. They all came knocking.In this conversation, Todd pulls back the curtain on why he listed in Dallas instead of New York, why a direct public offering democratizes AI upside for retail investors, why the scariest businesses are the best businesses, and why 600 years of economic history says the AI jobs panic has it exactly backwards. He also explains how behavioral psychometrics turned a construction company's bid estimator into a weapon, and why he told his kids the liberal arts just became the most valuable degree on campus.https://aiaiholdings.comhttps://skullgames.orghttps://aiforfounders.cohttps://inboxalchemy.co

The same artificial intelligence saved one insurer a billion dollars and cost another two billion. Same tool. Opposite outcomes. The only variable was who the machine was actually working for.That single tension is where this episode opens, and it turns out to be the question that quietly decides everything a founder builds. Gaurav Agrawal, Vice President of Engineering at Collective Health, has spent a career standing at the exact moment technology flips from impossible to inevitable. He was in the Apple atrium when Steve Jobs revealed the iPhone and watched the room's jaws hit the floor. He helped Reliance Jio connect 18,000 villages and vault India from 150th in the world for broadband penetration to first in a matter of months. Now he is pointing that same instinct at the most broken machine in America: healthcare.What makes this conversation land is that Gaurav refuses the easy framing. AI is not good or evil in healthcare, he argues. It is a mirror. Point it at margin and you get claim denials at machine speed. Point it at the member and you get a 24/7 companion that answers "why was my claim denied" in plain language, a copilot whispering the right answer into a service agent's ear so they can drop the robotic script and actually be human, and a roadmap that arrives in months instead of years. At Collective Health, the rule is blunt: every AI decision starts from "how does the customer benefit." If it also saves money, that is icing on the cake, never the recipe.The episode gets personal, and that is where it earns its rating. Gaurav's mother fell ill after moving to the US. The best healthcare system in the world, the one he trusted, failed her. He flew her back to India for care. She is no longer with us. That loss is the engine behind his work, and you can hear it. For founders, the practical payload is just as sharp: the benefits trap that springs the moment you hire your tenth person, the places AI absolutely should not go (claim rejections still pass through human eyes, every time), and how a lean team of around 210 engineers compresses an 18-to-24-month roadmap into six.https://collectivehealth.comhttps://aiforfounders.cohttps://inboxalchemy.co

Two founders sit down on a Friday with the World Cup playing in the background, and within ten minutes one of them casually reveals he has built a version of himself that works while he sleeps.That is the hook, and it is not hype. Jason Katz, co-founder of Kindling Solutions, walks through what he calls his personal content machine: a chain of Notion databases, AI agents, and approval triggers that takes a single spoken idea and turns it into finished video, social posts, and carousels, all before he sits down at a computer. The genius is not the automation. Plenty of people automate. The genius is that the output sounds exactly like Jason, because the system is engineered around authenticity instead of around shortcuts.Here is the part that should make every founder lean in. Jason does not let the AI write his ideas. He lets the AI interview him. He talks into his phone in the backyard with a coffee, an interviewer agent trained on the tactics of Joe Rogan, Oprah Winfrey, and Howard Stern pulls his real takes out of him across ten to twelve questions, and only then does the structuring begin. The words are his. The machine just gives them shape. As he puts it, the context truly does half the work, and that is the line nobody is saying out loud.Meanwhile Ryan turns the conversation into a masterclass on performance itself. After more than a thousand podcasts, he has reduced great content to a few unglamorous truths: sleep and caffeine are the real production stack, clarity beats cleverness, lead with a current event so your guest can find their feet, and tell yourself to speak ten percent slower so the ums take care of themselves. It is the kind of advice that sounds obvious until you realize almost nobody actually does it.Both threads land on the same destination. First-time founders obsess over product. Second-time founders obsess over distribution. Jason and Ryan are both, by their own admission, finally crossing that line, moving from "what is this business" to "let the world know what is up." The episode is the sound of two operators getting comfortable being the face of the thing they built.⁠⁠https://kindlingsolutions.com⁠⁠https://aiforfounders.co⁠⁠https://linkedin.com/in/jasonkatz99/⁠⁠https://linkedin.com/in/estesryan/⁠⁠

The same artificial intelligence saved one insurer a billion dollars and cost another two billion. Same tool. Opposite outcomes. The only variable was who the machine was actually working for.That single tension is where this episode opens, and it turns out to be the question that quietly decides everything a founder builds. Gaurav Agrawal, Vice President of Engineering at Collective Health, has spent a career standing at the exact moment technology flips from impossible to inevitable. He was in the Apple atrium when Steve Jobs revealed the iPhone and watched the room's jaws hit the floor. He helped Reliance Jio connect 18,000 villages and vault India from 150th in the world for broadband penetration to first in a matter of months. Now he is pointing that same instinct at the most broken machine in America: healthcare.What makes this conversation land is that Gaurav refuses the easy framing. AI is not good or evil in healthcare, he argues. It is a mirror. Point it at margin and you get claim denials at machine speed. Point it at the member and you get a 24/7 companion that answers "why was my claim denied" in plain language, a copilot whispering the right answer into a service agent's ear so they can drop the robotic script and actually be human, and a roadmap that arrives in months instead of years. At Collective Health, the rule is blunt: every AI decision starts from "how does the customer benefit." If it also saves money, that is icing on the cake, never the recipe.The episode gets personal, and that is where it earns its rating. Gaurav's mother fell ill after moving to the US. The best healthcare system in the world, the one he trusted, failed her. He flew her back to India for care. She is no longer with us. That loss is the engine behind his work, and you can hear it. For founders, the practical payload is just as sharp: the benefits trap that springs the moment you hire your tenth person, the places AI absolutely should not go (claim rejections still pass through human eyes, every time), and how a lean team of around 210 engineers compresses an 18-to-24-month roadmap into six.https://collectivehealth.comhttps://aiforfounders.cohttps://inboxalchemy.co⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠https://ainativestudent.com/

Your blood pressure spikes the moment the cuff goes on. You're sitting on crinkly paper in a cold exam room, and the number on the screen may say more about the moment than your everyday life. It's the classic "white coat effect," and it doubles as a metaphor for one of healthcare's biggest challenges: we often measure people at isolated moments instead of continuously, then wonder why better outcomes remain elusive. Amir from Hello Heart spends his days closing that gap. Hello Heart is a preventive heart health platform built around a connected blood pressure monitor, a smart pill organizer, and a mobile app that helps members better understand and manage their cardiovascular health. Today, Hello Heart partners with more than 150 leading employers, national health plans, and labor organizations, supporting millions of eligible members while helping organizations improve cardiovascular health outcomes through AI-powered prevention.The newest addition is Nia, launched in October 2025 as the world's first AI heart health assistant. Designed to complement, not replace, clinical care, Nia helps members better understand their heart health, stay engaged with their care plans, and prepare for more informed conversations with their healthcare providers. This episode is a rare founder conversation that goes beyond the product demo. If you're building vertical AI, healthcare technology, or any AI system where trust and accuracy matter, this is one worth studying.The thread running through the entire conversation is trust. Amir returns to a simple idea: people were never meant to be the primary data layer. AI works best when it reduces administrative burden, surfaces meaningful insights, and helps members stay engaged between clinical visits, giving healthcare professionals more time to focus on the conversations that require empathy, judgment, and human expertise. He calls it the shift from reactive to preventive care, and he's clear that earning trust requires thoughtful design, rigorous guardrails, and a deep commitment to responsible AI.https://www.helloheart.comhttps://www.linkedin.com/in/amir-dolev-b5618421/https://www.helloheart.com/press/hello-heart-launches-the-worlds-first-ai-heart-health-assistant-niahttps://ainativestudent.com⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://inboxalchemy.co/

A stranger gives you ten seconds. Before you open your mouth, before the pitch, before the handshake, they have already read your shirt and filed you away. Zoher Karu thinks that ten seconds is a data problem, and he left one of the biggest data jobs in tech to go solve it.Zoher spent years as Global Chief Data Officer at eBay and Chief Data and Analytics Officer at Blue Shield of California. Now he is Head of AI at Taelor, the AI-powered menswear rental subscription founded by Anya Cheng and Phoebe Tan. The premise is simple and a little radical: most men do not have the time, the skills, or the desire to shop, yet they still want the outcome of looking sharp. So Taelor sends you a box, you wear it, you keep what hits, you mail back the rest, and no one ever folds laundry or guesses at the mall again.Underneath the box is the hard part. Zoher calls it the matching problem. Picture Ryan, 30,000 pieces of inventory, and the question "which six go in the box." Basic rules thin the herd, no wrong sizes, no shirts you would hate. After that, you need to capture something almost nobody can write down: why a person on the street simply looks put together. Ask a great stylist to explain the rule and they cannot, the same way a driver cannot list every reason they tap the brake. Taelor's job is to bottle that instinct and run it at scale, with human stylists in the loop and the machine learning from every piece of feedback.The twist that should make founders sit up is the second business hiding inside the first. Every rental generates a signal about what real men actually like on real bodies in real contexts. Brands today buy on gut, betting that yellow is big this year. Taelor is building the feedback layer that turns a B2C rental into a B2B data product for the brands themselves, with sustainability as the upside, since roughly 30% of clothing reportedly reaches the landfill never having been worn.This one is for the founder who spent on the camera and the mic and still shows up in a college shirt. Your product may be great. In the first ten seconds, you are the product.https://taelor.style/https://taelor.style/pages/membershiphttps://www.linkedin.com/in/zzkaru/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://inboxalchemy.co/ https://ainativestudent.com/

Every month your inference bill climbs, and you tell yourself it is the cost of doing business. What if it is actually a tax on what you do not know? In this episode, the founder of Featherless makes a blunt case: the best model for most of what your startup does is open source, often runs for basically peanuts, and is frequently built in China. He has put real money behind that thesis, about $25M across a seed and a Series A led by AMD Ventures and Airbus Ventures, and a platform that holds tens of thousands of open models online at once through a single API key.The throughline is freedom. Eugene's grandmother speaks seven languages and none of them are English or Chinese, which is roughly half the planet that the closed, English-and-Chinese-first future would leave behind. Open source, he argues, is not just free as in money. It is free as in freedom: when the model runs on your terms, nobody can ever take it away from you. He walks through why the database wars of the past, Oracle and Microsoft and IBM, then MySQL and Postgres, are replaying in AI at ten times the speed, why "lazy" models are really just a mirror of us, and why the labs chasing superintelligence may be solving the wrong problem while businesses quietly beg for one thing: reliability.⁠⁠https://www.featherless.ai⁠⁠https://www.x.com/picocreator (Eugene on X)⁠⁠https://www.techtalkcto.substack.com (his Substack, Tech Talk CTO)⁠⁠https://www.wiki.rwkv.com (RWKV, Linux Foundation)⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://inboxalchemy.co/ https://ainativestudent.com/

There is thirty billion dollars a year in lost rent sitting in empty units across America, and that vacancy quietly erases roughly half a trillion dollars of property value. Everyone assumed the fix was price, amenities, or a slicker chatbot. Then Nick Deveau and his co-founder Ben Epstein got their hands on millions of real leasing calls from one of the largest apartment owners in the country, pointed a team of machine learning engineers at the data, and found something nobody scripted for. The single strongest predictor of a signed lease was not the special, not the square footage, not a scarcity tactic. It was whether the leasing agent laughed on the phone. The second strongest was whether they asked a genuinely curious question.So Grotto AI did the counterintuitive thing. While most of the industry raced to replace humans with voice agents, Grotto built a tool to make humans better at the one thing only humans can do: build rapport. A leasing agent gets a push notification fifteen minutes before a tour telling them the prospect has a dog named Fido, loves natural light, and drives a Subaru. They record the tour on a small clip-on mic, get instant feedback on what they crushed and what they missed, and Grotto drafts the personalized follow-up, catches the special they forgot to mention, and quietly does the CRM grunt work. Nick calls it targeted advertising for the real world. Ryan called it a second brain for the field. Both are right.This episode is the clearest case study going for vertical AI: pick one painful, measurable leak, capture data nobody else has, and sell revenue instead of cost cuts.https://grotto.aihttps://www.linkedin.com/in/nick-deveau-a6241379/https://www.linkedin.com/in/estesryan/https://aiforfounders.cohttps://inboxalchemy.cohttps://robinhood.org

Time kills deals. So does the fine print you never read.James Charles sold the fastest-moving makeup palette in history, did a reported $100 million in revenue, and reportedly walked with around $2 million, because somewhere in a contract he did not read, the math got decided for him. That is the horror story Logan Brown tells founders to wake them up. Then she hands them the antidote.Logan walked into the Douglas County District Attorney's office in Lawrence, Kansas at twelve years old and asked for a job. A secretary named Dolores made her a personal intern, and Logan spent her summers filing, dusting, and sitting in on hearings she had no business sitting in on. Vanderbilt valedictorian. Harvard Law. A machine-washable pantsuit company called Spencer Jane that she still runs out of her parents' basement. Two and a half years at Cooley billing $900 an hour to the founders she could not stop admiring. And then, when she watched ChatGPT and Claude crack open legal work, she did the unthinkable: she left to build the thing that competes with the very rates she used to charge.Soxton is an AI-powered outside general counsel for early-stage companies. You make a request on the site in plain English, AI takes the first pass, a startup lawyer with real experience reviews every single output, and you get your document back in 24 hours for $100. Form a Delaware C Corp for free through a banking partner. Get your influencer or advisor agreement papered for a hundred bucks. Run a priced round for $10,000 instead of the $50,000 to $100,000 Big Law charges. Logan is blunt about who she is fighting: her competition is not Cooley, it is Claude and ChatGPT, and her edge is the human in the loop plus the market data from thousands of deals that tells you when a provision is one you should never sign.This one is for the founder who keeps saying "I'll deal with legal later." Later just got a lot cheaper.https://www.soxton.ai/https://x.com/loganbrown799https://www.linkedin.com/in/logan-brown-03765552⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://inboxalchemy.co/ https://ainativestudent.com/

The real villain in American healthcare is not the insurance company. It is the hold music.The United States burns an estimated $350 billion a year on administrative waste, $266 billion of it from sheer complexity and $84 billion from fraud and abuse, and that sits inside a healthcare economy so large that if you sliced it off on its own it would rank as roughly the fourth biggest economy on earth. Patients lose their patience before they ever lose their health, and the industry has spent years selling a false binary: hire more humans who burn out, or unleash bots that collapse the moment a call actually matters.Frederik Mueller, Timm Schneider, and their team built Third Way Health on a different premise. Pair AI agents with embedded human operators, let the machines crush the repetitive volume, and free real people for the conversations that need a heartbeat. The company started before ChatGPT made AI a dinner-table word, which is why the name carries a double meaning: there was always a third way between low-tech service vendors and high-friction software, and there is now a third way between full automation and full staffing. Jamie Reddick, COO of Graybill Medical Group, lived the payoff. Over a two-year partnership, North San Diego County's largest independent multi-specialty group cut front-office costs by roughly $3 million, about 50%, while making patients feel less like a ticket number and more like a person.This episode is a clinic on building in a broken market without pretending the brokenness will disappear if you throw enough technology at it.https://thirdway.healthhttps://www.linkedin.com/in/frederik-mueller-53198a17/https://www.linkedin.com/in/timm-schneider-463a2683/https://www.linkedin.com/in/jamie-reddick-586691249/https://podcasts.apple.com/us/podcast/healthcare-ops-wave/id1774334723https://aiforfounders.cohttps://inboxalchemy.cohttps://ainativestudent.comhttps://www.linkedin.com/in/estesryan/

A CEO told Justin Watt his company was ready for AI. "We've got our data architecture together," he said, giddy. Justin asked to see it. The guy pulled up an Excel file. The filename? Data Lake.That moment is the whole episode in miniature. Justin Watt, co-founder of Switchboard, studied psychology, not computer science, and that turns out to be his unfair advantage. After stints at IBM and MetaLab (where his teams built products for Uber and Amazon and helped design Slack), Justin realized the hardest part of every technology project is never the technology. It's the humans. Every business challenge is a human challenge wearing a software costume.Switchboard works with mid-market companies, the $50 million to $500 million crowd, the businesses old enough to have 40 years of legacy process and young enough to actually change. These companies think they're AI-enabled because they bought everyone a Claude license. Meanwhile, month-end close runs through one person's spreadsheet that nobody else can read, and if that person quits, the business forgets how it works.Justin's fix is unglamorous and devastatingly effective: map the real workflow, not the org-chart version. Find where humans are doing machine work. Inject AI at the steps where it actually moves the needle. Keep humans in the loop everywhere else. The result isn't layoffs, it's smart people finally doing smart work. In Justin's experience, less than 5% of leadership conversations are about cutting headcount. The conversation is always about the endless pile of work standing between the company and its goals.Along the way, Ryan and Justin cover the AI washing epidemic (blaming layoffs on AI to cover up old hiring mistakes), why frontier lab doom marketing blew up in everyone's faces, the death of "bring your whole self to work," quiet quitting as cowardice, Garth Brooks selling his catalog for a rumored $2 billion, ravens that speak English, and the most surreal government website in existence.https://withswitchboard.comhttps://www.linkedin.com/in/wattjustin/https://aiforfounders.cohttps://inboxalchemy.cohttps://spcai.orghttps://www.war.gov/ufo (referenced as war.gov/ufo)https://suno.com (Suno, the AI music generator discussed)

What if the dumbest thing your startup does this year is hire?In Zurich, a six-person company is serving Fortune 500 clients with a rule that sounds like heresy: no human in the company can be assigned a task. The software literally locks them out. Every task goes to an agent first, and the agent decides when a human's judgment is actually worth the interruption.That company is Salfati Group, and its founder is Elon Salfati. Yes, Elon. No, not that one. This Elon is a former Israeli intelligence engineer, ex R&D Director at web security firm Reblaze, co-founder of RELE.AI, founder of intelligent testing startup Metiss, and now a PhD researcher in AI security. He has spent his career deleting more code than he writes, and now he is deleting org charts.The episode opens with a ripped-from-the-headlines jump off: Microsoft's Build 2026 announcement of Autopilots, always-on agents with their own identity that act on your behalf. Ryan asks the uncomfortable question: if 10,000 enterprises flip on the same agents, does diversity of thought dissolve into a hive mind? Elon's answer reframes the whole AI transformation conversation. Most companies are stuck sprinkling AI to please the board or deploying point solutions on annoying spreadsheets. The real unlock is flipping the entire model from "a human with an army of agents" to "an army of agents with a human."From there the conversation gets practical, then philosophical, then back again. Elon walks through a real client engagement: a service marketplace with a 51-step quote-to-cash process bleeding retention, and how color coding every step revealed exactly where humans add value and where they were just hands on keyboard. Then Ryan, a lifelong meditator and self-described student of human consciousness, pulls Elon into the deep end: what does it mean that Salfati Group calls its agents sentient? Elon's answer centers on memory, causality, and temporal understanding, and why he believes agent memory is the next great moat. Plants, cats, the Library of Alexandria, and Mr. Bridgewater the Denver farrier all make appearances. It is that kind of episode.salfati.groupaiforfounders.coinboxalchemy.coElon Salfati on LinkedIn: linkedin.com/in/elonsalfatiRyan Estes on LinkedIn: linkedin.com/in/estesryan

Two purple belts walk back onto the mat after years away, and the guy who is slow, mindful, and refuses to break a sweat starts sweeping and submitting the meatheads who are gassing out around him. That is not a jujitsu story. That is the whole episode.This week Ryan Estes and Jason Katz, co-founder of Kindling Solutions, skip the warmup and go straight into the thing every founder feels but rarely says out loud: the ground is moving under all of us, the tools are getting absurdly good, and the people winning are not the fastest or the strongest. They are the ones with stillness, leverage, and an authentic voice that no model can fake.Jason walks through the operating system he is quietly building around himself. A morning brief that reads his Slack, his Teams, yesterday's calls, today's calendar, and his open tasks, then hands him a five-line executive summary before he has even left the porch. A content pipeline that researches ideas, scores them, then interviews him in his own voice like Joe Rogan would, so the output is actually him and not another pile of generated mush. Then the conversation turns to the uncomfortable truth he calls his thorn: everyone is an AI consultant now, the way everyone in Colorado had a grow in 2009, and the single-workflow microservices people are productizing today will cost three dollars on a phone very soon. The question is not whether you can automate something. The question is where your margin lives once the press-a-button version arrives.Ryan counters with the optimist's case. The bigger the frontier models get, the wider the gap between AI-native founders and everyone else, and the more demand there is for people who can actually integrate this stuff with taste. His own proof: web traffic, newsletters, and podcasting, the three compounding channels he believes are the only distribution worth grinding for, because you own them and no single algorithm can switch them off overnight.It is fast, funny, and genuinely useful, with a side of hair powder and an au pair from South Africa. Pull up a chair.https://kindlingsolutions.com (relaunching, was not live at recording)https://www.linkedin.com/in/jasonkatz99/https://www.headset.iohttps://www.anthropic.comhttps://search.google.com/search-consolehttps://www.eastonbjj.comhttps://trynina.cohttps://aiforfounders.cohttps://inboxalchemy.cohttps://www.linkedin.com/in/estesryan/https://trynina.cohttps://ainativestudent.com

The inbox is dead, and the people who keep emailing it the hardest are the ones killing it fastest.David Connors has watched this happen up close. He sold his recruiting automation startup, Automately, to Sequoia Capital, spent two years inside the firm building tools so its investors and founders could answer one maddening question, "who do we actually know at company X," and walked out with a conviction that turned into a company. That company is The Swarm, the relationship intelligence platform he now runs as Co-Founder and CEO, and this is his second time on the show. In the twelve months since his last visit, the world sped up, the spam cannons got louder, and David got quieter, more grounded, and 35 pounds lighter. The throughline of this episode is simple and a little uncomfortable: AI made it trivially easy to write the perfect cold message, which means the perfect cold message is now worth almost nothing. What it cannot fake is trust. And trust, David argues, is the only currency left.The conversation moves from the personal to the tactical and back again. David opens up about how he protects his attention as a father of two with a third on the way, why he treats work like a sprinter treats a race rather than a marathoner who never stops, and why running yourself into the ground produces expensive decisions you pay for twice. Then Ryan steers into the meat: how The Swarm passively maps the network sitting around your entire company, not just your personal Rolodex, and turns it into a third sales channel that is neither inbound nor outbound. The numbers do the talking. A warm intro converts ten to twenty times better than cold. Google and Microsoft are now filtering out senders you do not recognize. The motion that used to eat ten to 15 hours a week of someone's time now takes ten minutes with agents. And the whole thing compounds, because every customer you close maps a new network you can map next.There is a bigger swing underneath all of it. David is not trying to be a $10 million enrichment-data business. He wants to carve into LinkedIn's roughly $18 billion revenue run rate by building the relationship graph that agents can actually use, the thing LinkedIn built for the SaaS era but will never open up. Whether you buy the vision or not, the practical takeaway lands either way: map your network, treat it like an asset, batch your asks, close the loop, and never become the neighbor who only knocks when they need an egg.https://www.theswarm.comhttps://www.linkedin.com/in/connorsdavid/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://inboxalchemy.co/ https://trynina.co/ https://ainativestudent.com/https://www.ymcasf.org

She didn't get maternity leave. So she rewired the entire way she worked, and accidentally redrew the map of what her career was worth. In 2020, Ashley Gross was just another marketer pulling 80 hours inside a 40-hour job, operating on the oldest visibility hack in the book: be the first one in, be the last one out. Then she became a mom with no leave on the table, and the math stopped working. So she started teaching AI to do her busywork, not to impress anyone, but to claw back time with her newborn.What happened next is the real story. The automation didn't free her. It exposed her. All the work she clawed back came flooding right back in, because she was the comfort person, the human Google, the one who knew where every document lived. Knowledgeable, indispensable, and quietly underpaid. That gap, between the work you do and the work people can see, became her whole thesis.She walked into the CMO's office, handed over her playbook, and built her own unpaid internal AI champion role to test one question: does this knowledge transfer to other humans? Within three months, the answer was a $25 million pipeline overachievement. That was the moment the imposter syndrome died. Then came the newsletter, zero to over 5,000 in two months of cringey, daily, ego-at-the-door posting. Then a Maven waitlist of more than a thousand people telling her they would pay. Only then did she jump, never risking the paycheck that fed her family until the runway was already built.Today AI Workforce Alliance runs on a team of twelve full-timers, ten-plus part-timers, freelancers, and a few agents quietly handling the admin in between. Notion is the centralized brain. Claude and MCP connectors do the talking. The tech stack went from sprawling to five tools. The plan for 2026 is to 10X through partnerships. And she still hates social media, which is exactly why you should trust her when she says you have to do it anyway.https://aiworkforcealliance.comhttps://www.linkedin.com/in/theashleygrossThe AI Work Week (Wiley), pre-order on Amazon and https://www.barnesandnoble.comhttps://tgpdenver.org (The Gathering Place, Denver)⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://inboxalchemy.co/ https://trynina.co/ https://ainativestudent.com/

The salesperson of the future never forgets you. The only question is whether that feels like care or surveillance.JP Grace has worked the floor. Publix bag boy, Breckenridge coffee shop, the whole tour. Now he's the CTO of Endear, the retail-first CRM powering one-on-one selling for brands like Reformation, Untuckit, Jones Road Beauty, AG Jeans, and Boll & Branch across more than 2,000 stores in 19 countries. And he's on a mission to give brick-and-mortar sales associates what B2B reps have had for decades: a system that actually remembers the customer.Here's the problem Endear attacks. A sales associate gets maybe fifteen minutes at the start of a shift to message VIPs. Finding the right person, drafting the right note, picking the right template: it's all friction. So most outreach never happens, and the customer who walked away from out-of-stock shoes last Tuesday just disappears forever. Endear's brand-new AI Opportunity Engine, launched the day after this recording, flips that. It surfaces the five to ten biggest opportunities for each associate every morning, pre-drafts the message, and lets them review and send in seconds. Early results: 6x more outreach in six weeks and a 35x return on delivered messages.JP's career arc is its own masterclass. He helped take LiveIntent from zero revenue to a valuation in the hundreds of millions, coached startup CTOs at AB InBev's ZX Ventures, and joined founders Leigh Sevin and Jinesh Shah after they'd spent years pivoting in stealth before catching their inflection point in March 2020, when the world went inside and brands scrambled for ways to keep selling without foot traffic.Meanwhile, Ryan relives his entire retail past, from selling 30 electronic drum kits to Colorado Springs mega churches at Guitar Center, to leading the nation in Finding Nemo pre-sales, to a return-counter horror story at Nordstrom you will not forget. Underneath the laughs is a serious thesis: the companies that win the next decade won't have the best products. They'll be the ones who remember you the warmest.https://endearhq.com/https://www.linkedin.com/in/josephpgrace/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://inboxalchemy.co/ https://trynina.co/ https://ainativestudent.com/

The wall you built to protect yourself is the same wall your team can't get past.Most founder advice is about adding. Add a growth loop. Add a framework. Add another seven habits. Tyler Dickerhoof showed up to AI for Founders to argue the opposite. The thing standing between you and the company you want is usually something you are spending enormous energy to keep hidden.Tyler is the founder of the Impact Driven Leader community, host of The Tyler Dickerhoof Show, a Cornell graduate, and the author of a new book called The Things We Hide. He has generated more than $700 million in business sales across a career that started, of all places, as a nutritionist for dairy cows in Ohio. He is not a guru who floated in from a TED stage. He is a farm kid who got told farm kids were not smart, spent decades proving his worth through intelligence and intensity, and watched that same intensity push away the people he cared about most.The conversation opens with a story he did not tell anyone for years. At 14, in a farming accident, Tyler drove over his three year old brother, who died. Sitting on the hood of a sheriff's car being questioned, a teenage Tyler hardened into a posture that would quietly run his leadership for the next 25 years. Get in line or get out. It took a normal employee dispute at a gym he owned, almost three decades later, to snap him back to that moment and realize, "Oh. That's how I deal with things."From there the episode becomes a working manual for founders on how fears and insecurities leak into leadership, tone, relationships, and revenue, and what to do about it. Tyler and Ryan trade their own defense mechanisms, intensity and anger and humor, and land on a hard truth every operator needs. The scariest part about leading with intensity is not that it fails. It is that it works, in the short term, which is exactly why founders double down on it until the carnage piles up.https://www.tylerdickerhoof.com/book⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠/https://inboxalchemy.co/ https://trynina.co/

Everyone thinks the magic is in the prompt. It is not. The magic is in everything you build around the prompt.That is the thread running through this build in public session, where the conversation goes deep on what it actually takes to make AI video that looks like a real person, sounds like a real person, and does not collapse into that plastic, uncanny mush we have all learned to scroll past. The answer is not a better sentence typed into a box. It is a system. A founder who spent nine months in trial and error walks through the exact chain of models, references, and approvals that turns a single orange hoodie character into a living, transforming short film. Along the way you get the unglamorous truths nobody puts in a launch video: the order you stitch voice and visuals in matters, your characters have to be locked before they are useful, and the cheapest thing in the entire pipeline is the thing that holds it all together.There is also a quieter story underneath the tooling. It is about why a founder builds anything as a system in the first place, the pull between shipping at scale and being present in your own life, and the strange new normal where your face and your voice can be reproduced from a phone full of selfies.https://www.linkedin.com/in/jasonkatz99/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://inboxalchemy.co/ https://trynina.co/

Every founder has a graveyard. Half-finished apps, abandoned prototypes, that "killer tool" you vibe-coded over a weekend and never touched again. Mariam Hakobyan, Co-Founder and CEO of Softr, thinks she knows exactly why those projects keep dying, and it is not your discipline. It is the chains. AI handed everyone a hammer and called them a carpenter, but it never removed the hard part. It just moved the complexity onto you: the authentication, the permissions, the security, the thousand boring edge cases that make a toy into a tool people can actually log into.Mariam is an engineer turned entrepreneur who led product and engineering teams of forty-plus people before walking away from a six-figure job to build something of her own. She and her husband Artur Mkrtchyan started Softr in 2019 with one stubborn belief: 80% of every business app is the same repetitive plumbing, and nobody should have to rebuild it from scratch ever again. They call it Lego for software. Connect your data, snap the blocks together, and a non-technical operator ships a full, secure, working app in about five minutes.The numbers tell a quiet, brutal story. A $2.2M seed they did not even plan to raise. A $13.5M Series A from FirstMark. Then a hard stop on fundraising, because the thing was already profitable. Today Softr runs eight-figure revenue with a lean team of fifty across fifteen countries, no traditional sales team, and growth that came almost entirely from a Product Hunt launch and word of mouth. Oh, and investors told a husband-and-wife founding team it would never work. Mariam's reply: they had a decade of conflict-resolution experience before they ever incorporated.This episode is for the founder who keeps starting and never shipping, the operator drowning in spreadsheets, and anyone trying to figure out when to reach for Claude Code and when to put the terminal down.https://www.softr.io/pricinghttps://www.linkedin.com/in/mariamhakobyan/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠ https://trynina.co/

Two fifteen-year-old rock climbing buddies from Long Island made a pact in a surf lineup: build one-of-a-kind experiences for causes they cared about. That idea died. So did the loyalty app before it, and the apparel company after it. What survived was the thing nobody planned, an agency born from following opportunity instead of forcing a vision.Justin Abrams and Mike Rispoli have been failing forward together for twenty years, and Cause of a Kind is the compounding result. The deal that let them quit their jobs was the Hospital for Special Surgery in New York, their first real foray into medical software and the moment Justin took out a half million dollar SBA loan and burned the boats. Today they build and modernize software for small and mid-sized businesses on a flat monthly model, no offshore handoffs, no surprise invoices.This conversation is a gut check for every founder currently drowning in shiny object syndrome. Mike has the scars of the Web3 era and sees the exact same pattern repeating with AI: companies slapping an "AI native" label on a context call to ChatGPT, then wondering why three competitors clone them in a month. His thesis is sharp and survivable. The magic is not AI. The magic is AI plus workflow plus deep domain knowledge, the combination that cannot be knocked off because you had to be the person on the inside to build it.Then there is the distribution story, which is the part founders will rewatch. Cause of a Kind went from roughly 7,000 to 160,000 plus YouTube subscribers in five months by doing one unglamorous thing relentlessly: they ship every single day. No filter, no precious production cycle, just two fast-talking Long Islanders who treat their business as a media house and treat publishing as the cheapest sales conversation on earth.https://www.causeofakind.com/https://www.linkedin.com/in/cuzzinjustin/https://www.linkedin.com/in/michael-rispoli-cto/https://www.youtube.com/channel/UCWAstEyCK6YsKVTTRsQr37w⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://trynina.co/

Some of the smartest engineers alive are designing the physical world with software older than their interns. Brake discs, axles, medical devices, aircraft, all built on tools that can take twenty minutes just to open a file, and a knowledge base that walked out the door when the industry shipped its expertise overseas. Hugo Nordell saw this up close. Trained as a theoretical physicist, seasoned in Silicon Valley's drone and autonomous driving years, then a digital transformation executive at Sandvik and Aker, he kept watching brilliant hardware teams fight their own tooling on a daily basis while production costs quietly ballooned.So he built the thing he wished he had. Encube is a browser based, collaborative design platform that sits between your CAD system and your release management, then layers AI on top of a foundation almost nobody else is building: a deterministic engine that actually understands manufacturability. Think of it as a FigJam board on steroids, where complex CAD models and heavy engineering drawings become first class citizens, loading in two to three seconds on a run of the mill laptop with no expensive graphics card required. People thought he was cheating. He was not.The deeper insight is the one founders in every category should tattoo somewhere visible. Generative AI is rewriting software engineering because software has forty years of validation infrastructure: compilers, linters, unit tests, CI/CD, stack traces that let an agent self correct. Hardware has none of that. There is no compiler for atoms. So Encube is building one, on the GPU, blazingly fast, deterministic where it must be, with large language models bolted on only at the edges where stochastic answers are safe. Get that order right, and you could reimagine hardware design the way Lovable, Bolt, and Claude Code reimagined software. Get it wrong, and you ship slop into the one place slop kills people.https://www.getencube.comhttps://www.linkedin.com/in/hugonordell/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://trynina.co/

That is the dirty secret of LinkedIn for most founders. You scroll, you cringe at the textbook-perfect ChatGPT posts, you maybe drop a like, and you log off feeling exactly as broke as when you opened the app. Ali Hafizji, founder and CEO of Wednesday Solutions and the builder behind Chime at getchime.co, has been quietly running a different playbook. He went from under 5,000 LinkedIn followers to 12,000 without leaning on a content engine. The trick was not posting more. It was commenting smarter, on the right posts, in front of the right tribe, every single day.In this episode, Ali breaks down why the comment section is the most underutilized lever in B2B SaaS, why your ICP does not want to be educated by you, and how he built an AI agent that does the soul-crushing work of finding the right LinkedIn conversations so you can show up, drop one human comment, and close the laptop in ten minutes. He also walks through the design partner pricing, the rare anti-predatory SaaS model where the price goes down as the user base grows, and the curation logic behind Chime's 40,000-influencer database. If you have ever felt invisible on LinkedIn while watching your competitors print pipeline, this one is for you.The Interest Graph Engagement LoopEngage on posts that match your expertise.Show up in the feed of your ICP automatically, because LinkedIn is an interest graph, not a follower graph.Get DMs and conversations started by people who already trust your thinking.Skip the cold outreach phase entirely.The Comment Quality BarNo teaching, no textbook tone, no "ChatGPT wrote this for me" energy.Lead with contrarian views framed without picking a fight.Add wordplay, wit, or one personal anecdote.Keep it to two or three lines.Always ask the author a question.The Post-Comment DM LoopDM the author of the post you commented on.DM other people who engaged in the comments.No agenda, just "coffee chat" energy.Invite them to your newsletter once trust is built.Send referrals their way and watch the favor return.The Anti-Predatory SaaS Pricing ModelLock in $39/month forever for the first 25 design partners.Add new data sources (Reddit, X) without raising the base price.Pass cost savings down to customers as the user base grows, not up.https://getchime.cohttps://aiforfounders.cohttps://linkedin.com/in/alihafizji/https://linkedin.com/in/estesryan/

Your IT team is drowning. Every "how do I get access to..." Slack message you fire off is making it worse. And while everyone in 2026 is busy debating whether AI is coming for the C-suite, Tom Bachant has spent the last four years quietly automating the layer of work that actually keeps companies running. The help desk. The ticket queue. The Jira dashboard you've been ignoring for three weeks hoping it disappears.Tom is the co-founder and CEO of Unthread, an AI-powered helpdesk built natively into Slack and Microsoft Teams. He's also a two-time founder who sold his first company, Dashride, to Cruise in 2018, lived through the Cruise unraveling, then went back into the trenches with Y Combinator's Summer 2022 batch. His new company has raised $3.5M, landed Intuit, Lemonade, and Automattic as customers, and finished as a TechCrunch Disrupt 2025 Startup Battlefield Top 20 finalist.In this episode, Tom walks Ryan through the inception of Unthread, the YC playbook that got him to his first 10 customers without spending a dollar on ads, and the philosophical bet that code is now free so distribution is the only moat left. He also explains, with a straight face, why he runs abolishcars.org as a side project despite his first company being a ridesharing platform.The conversation kicks off with cars (Tom hates them, Ryan rides fixed gear, they both agree on flipping people off responsibly), and ends with downhill mountain biking in Crested Butte. In between, you get one of the cleanest tactical breakdowns of agentic service management you'll hear all year.https://unthread.iohttps://aiforfounders.cohttps://abolishcars.orghttps://www.linkedin.com/in/tombachant/https://inboxalchemy.co⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠https://trynina.co/

Picture St. Louis, 1849. Two men with a bottle of champagne and a brutal choice: go north for beaver pelts, or go south chasing gold in California. Joris Delanoue does not even blink. He picks the gold. Not for the metal. For the belief.That single line tells you everything about this conversation. Joris, co-founder and co-CEO of Fairmint, has spent the better part of two decades pushing into frontiers nobody else wanted to settle. He sold a cloud computing company, Nexteem, before most people trusted the cloud. Now he is doing the same thing to the one document that quietly governs every startup's destiny: the cap table.Here is the uncomfortable truth he lays out. Fifty years ago, Microsoft went public at an eight hundred million dollar valuation, and ordinary people built entire retirements on the climb that followed. Today, companies stay private until they are worth five hundred billion, and the upside goes to a happy few. The frontier did not close. It just moved behind a velvet rope. Joris wants to tear the rope down, and he thinks the tool to do it is equity that lives on a blockchain: programmable, transferable, and liquid enough that the engineer who bet fifteen years of her life on a startup can actually borrow against her shares to buy a house.This is a conversation about wealth, about who gets to build it, and about why the most defensible thing you own in the AI era is no longer your product. It is your distribution. Buckle up.Compliance by Automation (not Intermediation)Joris frames the entire Fairmint thesis as a shift away from people and toward code.Old world: compliance happens through layers of intermediaries, lawyers, banks, and reconciliation.New world: compliance lives inside a smart contract that mimics securities law and applies the rules automatically.The promise: lower transfer costs, fewer trolls under the bridge, and a single source of truth for who owns what.The Shovel Seller's DilemmaThe gold rush metaphor that opens the episode is a strategy lesson in disguise.The prospector grinds sixteen hours a day and often ends with broken backs and empty pans.The shovel seller monetizes everyone else's dream regardless of who strikes gold.Joris flips it: do not just sell shovels, own a piece of the mine through programmable equity.https://www.fairmint.com/https://www.linkedin.com/in/delanoue/https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://trynina.co/ https://ainativestudent.com/

Everything you know about getting found online is about to be obsolete. For two decades, founders chased one algorithm. Backlinks, page speed, keyword stuffing, the whole exhausting machine. Then a handful of chatbots quietly took the wheel, and now they decide which businesses get recommended and which ones get ghosted. SEO is bleeding out. Google traffic is leaking. And a huge slice of buyers now ask ChatGPT to pick their solution before a human ever enters the conversation.Here is the twist that should make every founder sit up straight: the playing field is wide open for the first time in twenty years. Tiny brands are outranking billion-dollar incumbents. Unknown podcasts are beating the giants. The new game is not about who has the biggest backlink pile. It is about who tells the clearest story.In this return visit, Jenna Hannon, co-founder and CMO of Hatter, runs a live tactical teardown using Ryan's own podcast page as the guinea pig. She walks through what AI search actually rewards, why a lead who found you through ChatGPT shows up on the call already sold, and the exact content structure that gets your brand cited instead of buried. She also drops the unglamorous truth about where AI pulls its recommendations from, and it is probably not where you think.This is your chance to control your narrative before the bots write it for you.The Three Names, One Thing PrincipleThe category has a branding problem. AEO, GEO, AI search. They sound different. They are not.AEO stands for answer engine optimization.GEO stands for generative engine optimization.AI search is the plain-language version.All three describe the same goal: showing up inside AI chatbots. Ignore the LinkedIn posts insisting they are separate disciplines.The Magical MomentThe new tell that AI search is working for you.A lead arrives having done their research inside a chatbot, not a Google rabbit hole.They already know they have a problem and that you are one of the few recommended solutions.They land on the call warm, informed, and close to buying.The chatbot's endorsement carries trust, because the user already treats the AI like a trusted advisor.https://gethatter.aihttps://aiforfounders.cohttps://www.linkedin.com/in/jennahannon⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠https://trynina.co/

You are the smartest person in your company. That is exactly the problem.Every founder hits the same wall. The strategy lives in your head. The taste lives in your gut. The thousand tiny judgment calls that make your company yours live nowhere anyone else can reach them. So your team waits. They wait on your approval, your context, your answer to a question you have answered nine times already. And while they wait, the work does not move.Joshua Liberson, CEO and co-founder of Dobbin, has spent a career watching this play out. He designed editorial systems for magazines, ran brand and creative at One Kings Lane, and advised a long list of founder-led companies before deciding the bottleneck was always the same: the founder cannot be in every room. Dobbin is his answer. It is a company AI that captures the fifteen-or-so dimensions of an organization, its culture, values, brand, strategy, and objectives, and then delivers that judgment to every person on the team right inside Slack, where the work already happens.The pitch is deceptively calm. Dobbin is not a creative generator and not a design tool. It is a thinking partner. The designer drops a layout into a channel and Dobbin critiques it against the principles the team itself articulated. The intern asks what to do today. The CEO uses it for high-value strategic thinking. Josh's favorite proof point is a creative agency built around the photographer Mark Seliger, whose Dobbin was assembled from four and a half hours of audio about a forty-five-year career in lighting, composition, and printmaking. The result: a managing director who now answers RFPs in thirty minutes instead of three weeks and seventeen meetings.Underneath the warm language is a hard claim about modern work. Microsoft estimates 57% of our time goes to coordination, roughly 22 hours of a 40-hour week. Nobody's KPI is "coordinate more," yet that is what the calendar quietly becomes. Josh's fix is not more project management, which he thinks the world already drowns in. It is what his friend Howard calls ambient alignment: the strategy is simply present, in the channel, evolving as the company evolves, so people stop waiting and start shipping.And he is honest about the banana peels. A great team is a pirate ship, full of brilliant misfits who wither under too much rigidity. So Dobbin is built to bend. It is iterative, never bedrock. It watches where work drifts from the foundation, then proposes amendments the founder can accept or reject. Structure that empowers, not structure that scolds. Or, as Josh puts it through a borrowed line from a Greek philosopher, you never step in the same river twice, because the river is flowing and so are you.LinksDobbin: https://dobbin.aiJoshua Liberson on LinkedIn: https://www.linkedin.com/in/joshliberson/AI for Founders newsletter: https://aiforfounders.coRyan Estes on LinkedIn: https://www.linkedin.com/in/estesryan/

Everything you trust online is about to break, and André Ferraz built a company to catch the people breaking it.Picture a 12-year-old kid riding his bike through Brazil when a stranger points a gun at his face to steal it. That kid grew up with two computer scientist parents, an early love of code, and a peculiar fascination not with building systems but with breaking them. Three decades later, that instinct for thinking like an attacker became the foundation of Incognia, a company now embedded in 1.2 billion monthly active devices and built on a single contrarian belief: your location behavior is the strongest signal of who you really are.But the road there nearly ended before it began. André moved to the United States six years ago to chase the biggest market, bringing a thriving location-based advertising business with him. Then the pandemic hit. Physical retailers shut down. Revenue collapsed 95% in a single month. The team went from 250 people to 50, keeping only the engineers. Most founders would have folded. André and his co-founders looked at the precise location technology they had spent over a decade perfecting and asked a different question: what else can this do?The answer was fraud prevention, and it turned out the world needed it desperately. Incognia now serves banks, fintechs, crypto exchanges, and marketplaces, answering one deceptively simple question for every login, transaction, and signup: is this user who they say they are? The results speak loudly. Triple revenue growth. Six times the return on investment delivered to clients. A 100% trial-to-paid conversion rate. And a 180% net dollar retention rate that means customers keep expanding once they see the data.The conversation gets genuinely unsettling when André lays out the asymmetry of modern fraud. The criminals are professionals, not hoodie-wearing loners. They run 60,000 fake accounts in two days. They factory-reset devices in 30 seconds to dodge detection. They share tools and open-source software while the banks defending against them compete and stay siloed. The money pouring into making deepfakes dwarfs the money fighting them. As André puts it, if you brought him a deepfake detection company, he would not invest, because detection can never outspend generation.So Incognia plays a different game entirely. Rather than analyzing whether a video is a deepfake, it checks whether the camera feeding that video is even real. Rather than trusting a spoofable GPS coordinate, it fuses Wi-Fi, Bluetooth, cell tower, compass, accelerometer, and gyroscope signals to locate a device down to eight foot accuracy, close enough to separate two fraudsters in different apartments of the same building. The bet is that AI can fake your face, your voice, and your data, but it cannot cheaply fake the real physical world at scale. Make the attack economically unfeasible, and the fraudster moves on.The episode closes on a vision that goes beyond catching criminals. André imagines a world without buttons, where the hotel TV logs you in automatically, the thermostat already knows your preferred temperature, and the world quietly personalizes itself around you because it recognizes you everywhere. Stop the fraud first, because that hurts. Then make the world more elegant.The Asymmetry of FraudAndré's core mental model for why defenders are structurally disadvantaged:Criminals break rules freely while banks must follow heavy financial and privacy regulation.Fraudsters collaborate and share open-source tools while competing banks stay siloed.Deepfake generation attracts vastly more capital than deepfake detection ever will.The takeaway: never fight on the attacker's terms, find a different angle.https://www.incognia.com/https://www.linkedin.com/in/andreferraz/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://trynina.co/

Pradnesh Patil spent years as a product leader at Fortune 500 companies bringing in millions in revenue, and every single quarter the same thing kept happening. He would walk into leadership meetings, present data, get hit with the question "why is this number different from last week," and then watch the opportunity window close while his data team spent two months trying to figure it out.It was not a bad data team. It was every data team. Data work is complicated, the experts get pulled in fifteen directions, and the backlog never shrinks.So Pradnesh called up Aaron, his co-founder of ten years and a veteran data and ML engineering leader, and they did the same thing they had done a dozen times before: they built something together. Last time it was an autonomous crypto trading bot. This time it was Altimate AI, a company built on a single insight. The bottleneck in enterprise is not engineering talent. It is the gap between the institutional knowledge locked inside your 15 year veteran's head and the new hires who do not have it yet.They raised on a few slides without writing a line of code, then built a free product that hit a million downloads across 100+ countries. That feedback flywheel turned into an enterprise offering, a second funding round, and Fortune 500 logos. The latest chapter is Altimate Core, an open source agent data engineering harness that now sits at number one on the industry benchmark.The Four Components of an Agent HarnessContext: Metadata pulled from across the hybrid data stack, plus the tribal knowledge previously locked in employee heads.Governance: Rules, permissions, and access controls that respect regulated industries like healthcare and financial services.Tools and Skills: The specific recipes and connectors agents need for specialized data work.Infrastructure: Sandbox environments for hundreds of agents to work in parallel without touching production.The Tribal Knowledge Capture LoopThe system watches a senior engineer fix a problem and stores how they did it.When a less experienced person hits the same issue, the system recalls the fix and recommends it.Users can correct the memory when AI picks up the wrong pattern.Active coaching of agents is positioned as the new responsibility for senior engineers.The Token Efficiency StackRoute reasoning heavy tasks like data modeling to frontier models.Route simple tasks like writing column descriptions to cheaper models.Bring your own LLM, including open source, to control costs and meet governance requirements.Avoid brute forcing one model into every specialized task.The Four High Value Data Use CasesELT pipeline development and debugging.Data infrastructure optimization, with cost reductions of 30 to 40 percent.Governance reporting and sensitive data tracking.Legacy stack migrations without paying a services firm millions.https://www.altimate.ai/https://www.linkedin.com/in/pradneshpatil/https://www.linkedin.com/in/estesryan/⁠⁠https://www.hssv.org⁠⁠https://aiforfounders.co⁠⁠https://www.youtube.com/@AIforfounders1

When Punit Bhatia walks into a founder's office, the building is usually already on fire. Someone configured the CRM, blasted thousands of cold emails, scaled the AI agent stack overnight, and is now staring at a complaint, a regulator, or worse, a trending news story. The problem was never the AI. The problem was the speed without the guardrails.In this conversation, Punit walks Ryan through what responsible AI actually looks like for founders who are vibe coding at midnight with their credit cards burning. He pulls apart real client stories: the founder who built a beautiful email empire on top of a non compliant list and had to torch it, the developer who copied every field of personal data because it was easier than copying only what was needed, the executive team that listed transparency as a core value but refused to publish a five page policy because competitors might read it.Punit's view is simple and uncomfortable. Privacy is not a compliance issue. It is a brand issue. It is a trust issue. The moment a founder hesitates when asked "is my customer data safe," they have already done the work of identifying their next sprint.1. The Discovery to Deployment Loop (Punit's Consulting Engine)This is how Fit4Privacy actually moves a founder from chaos to compliance.One hour alignment training to lock vocabulary across the roomTwo to four hour discovery workshop with key decision makersOne week to a gap report and an action planCertification training for select staff, short capsule training for everyone elsePolicy creation that translates law into language developers can act onSelf control assessment by the team, followed by an independent control assessmentFix gaps before the product hits the market, not after a complaint hits the inbox2. The Responsible AI FoundationA reusable principle stack Punit applies before any AI product ships.Decide if you actually want to be ethical, private, compliant, and transparent (most leaders nod on three, hesitate on the fourth)Document those decisions as written rules, not vibesTest for bias, hallucination, and data quality, not just "does it run"Copy only the data you need, never the whole table because it is easierGovern the agents the way you would govern human employees, with named accountabilityRun a gut check: would you let your 12 year old use this product3. The Reactor Prompt FrameworkPunit's six part prompting structure that turns any LLM into something close to a senior consultant.R Role: tell the model who it is (your McKinsey consultant, your privacy auditor)E Example: show it what good looks likeA Aim: state what you are trying to achieve and whyC Context: situation, company, stakes, constraintsT Text: the source material it should work fromOR Output: the exact format, length, and structure you want back4. The Virtual Privacy Advisor PatternA blueprint for the AI agent founders should be building right now.Feed it the responsible AI policy, the rules, and the executive guidanceWire it as a quiet observer across the agent stackHave it review outputs, flag scripts that pull more data than they should, and challenge configurations before deploymentUse it as the security guard that never clocks out and never sends the client database to the wrong serverhttps://www.fit4privacy.comhttps://www.growskills.storehttps://aiforfounders.cohttps://www.kitcaster.comhttps://punitbhatia.comhttps://www.linkedin.com/in/punitbhatia/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://trynina.co/

Will Ruben spent more than a decade at the companies that taught the internet what attention looks like. He led ranking and recommendations across Instagram during the era when Reels stopped being a feature and started being the entire product. He worked on Coinbase's Web3 Wallet. He scaled consumer products for billions of people. And then he walked away from all of it to solve something almost embarrassingly small in scope: the back and forth of scheduling a meeting.That choice is the whole story. Will is not building Workmate because scheduling is glamorous. He is building it because scheduling is the gateway drug to giving every knowledge worker the kind of strategic support that used to be reserved for executives with assistants and corner offices. The premise is democratization, the wedge is the calendar, and the long arc is a world where you collaborate with a mix of humans and AI teammates that feel indistinguishable from coworkers.In conversation with Ryan, Will lays out a thesis that is unusual in this AI moment. While most founders are racing to make their agents louder, faster, and more obviously artificial, Will is doing the opposite. Workmate is engineered to disappear. It has an email address at your domain. It writes the same way every time. It is white-labeled, customizable, and in many cases, the people interacting with it do not know they are talking to AI. Will calls this a flex. The flex is appearing more important than you are.The conversation winds through the ethics of disclosure, the speed of building when the foundation models change every two months, the difference between sculpting and painting, and a tangent on Instagram Reels that will make you reconsider why your wife sees men cooking with no shirts on. It also lands somewhere unexpected: a quiet, almost paternal argument that the founders who win in this era are the ones who go to bed on time.1. The Trust Curve in AI DisclosureWill frames the disclosure question not as a binary but as a function of industry, demographic, and medium.Internal team communication: full transparency is the default because users know they are working with the productExternal client communication: depends on industry norms (some sectors expect executive assistants, where AI fits seamlessly into existing expectations)The Workmate position: provide both options and let the customer choose the level of transparencyThe bet: in two years the question will dissolve entirely because AI teammates will be normalized the way remote work was normalized between 2015 and 20252. The Three Waves of Instagram (and What They Taught Will About AI Products)Will identifies three distinct product eras at Instagram, each of which informs how he is building Workmate.Wave one: filters on the feed (self-expression)Wave two: stories (ephemeral connection)Wave three: constant content recommendations and Reels (algorithmic discovery)The takeaway for AI: the third wave succeeded because it gave users more control over what they saw, not less. Workmate applies the same principle to scheduling preferences.3. The Sculpting versus Painting DistinctionWill and Ryan agree that the founder's job is shifting from execution to taste.Painting: the founder hand-crafts the outputSculpting: the founder shapes what AI produces by setting parameters, reviewing direction, and arbitrating qualityThe implication: management skills, not technical execution, become the bottleneckThe catch: agents are not fully autonomous yet, so founders still cannot fully step awayhttps://www.workmate.comhttps://www.linkedin.com/in/wrubenhttps://www.care-international.orghttps://aiforfounders.cohttps://kitcaster.com⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠https://trynina.co/

When Tim Freestone first logged into ChatGPT on November 23, 2022, he turned to his wife and said, "Okay, this is a thing." Two and a half years later, he's the Chief Strategy Officer at Kiteworks, a PE-backed unicorn protecting how data moves in and out of the world's most regulated companies. This episode is part jazz appreciation, part AI philosophy, and part hard-earned playbook for any founder staring down the agentic era wondering whether their data exposure is about to catch up with them.Tim's path is the kind founders should pay attention to. He spent the early part of his career writing grants for a performing arts college, then bootstrapped a New York marketing agency from zero to fifty employees and nearly ten million in revenue across a decade. The throughline was always building systems, and when AI collapsed the gap between intent and outcome, he went all in. A year ago he didn't know what a CLI was. Now he has more terminal tabs open than browser tabs.Kiteworks itself is a study in repositioning. The company spent fifteen years as Accellion, a secure file transfer business that had commoditized into a struggling thirty-million-dollar revenue line. Then current CEO Jonathan Yaron, a veteran of Israel's elite 8200 unit, saw signal where others saw stagnation. He expanded the platform to cover every channel through which data enters and exits an organization: file share, email, managed file transfer, APIs, secure protocols. Tim arrived as CMO five years ago, recognized the brand confusion between Accellion and its Kiteworks platform, and convinced Yaron to elevate the product name to the company name. The rebrand stuck. The vision expanded. And now, in the age of agents, that same control plane is being extended to govern how AI systems access and move enterprise data.The Intent-Data Layer FrameworkSaaS historically sat as a complex translation layer between human intent and dataEntire job titles formed around mastering specific software stacks (Salesforce admins, etc.)AI strips out the complexity layer entirely, allowing natural language to bridge intent and data directlyThis democratizes data leverage for both good actors and bad actorsThe strategic implication: protection must move down to the data layer itself, not the software layerThe Control Plane for Data ModelTraditional security stacks at the perimeter, cloud, and endpointAll of those layers exist to protect data, but none control data directlyKiteworks operates at the data layer, mapping individual assets to individual agentsYes/no permissions on access, sharing, and use, asset by asset, agent by agentThis becomes the matrix companies need to maintain compliance in agentic workflowsThe Regulator Doesn't Care PrincipleData exposure penalties apply regardless of cause: human error, agent action, orangutan typingPII, PHI, and CUI regulations remain in force even as agent regulations lagCompanies will face audits in 12+ months on agent activity happening todayInsurance policy: instrument controls now, before the legislative wave catches upThe Failure-as-Muscle FrameworkFailures should be encouraged the way muscles must be pushed toward failure to growInsecure leaders pour gasoline on others' mistakes to distract from their own gapsStrong organizations normalize mistakes as part of the operating systemMentorship is less about seeking mentees and more about transparently sharing the lessons that informed every current decisionhttps://www.kiteworks.comhttps://www.linkedin.com/in/freestone⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://trynina.co/ https://www.montereyjazzfestival.org