AI for Founders with Ryan Estes

aiforfounders.co
  • 5.0 (48)
  • Entrepreneurship
  • Updated Weekly

AI for Founders is where 47,000+ founders learn to build and scale with AI. Hosted by Ryan Estes, a Denver investor, creator, and founder, the show breaks down real strategies from top operators and AI visionaries. AI-ready data, zero-dependency workflows, founder-led distribution, and the tools driving revenue for today’s fastest-growing companies. If you’re a technical or non-technical founder who wants to work smarter, scale faster, and stay competitive, this podcast is your weekly unfair advantage.

  1. 1d ago

    800,000 Lives, 210 Engineers, One Bet: Inside Collective Health's AI Push

    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.com https://aiforfounders.co https://inboxalchemy.co

    53 min
  2. What It Do: First-Time Founders Build Product. He Built a Distribution Robot.

    2d ago

    What It Do: First-Time Founders Build Product. He Built a Distribution Robot.

    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.com ⁠⁠https://aiforfounders.co ⁠⁠https://linkedin.com/in/jasonkatz99/ ⁠⁠https://linkedin.com/in/estesryan/⁠⁠

    30 min
  3. AI Heart Doctor (And 150 Fortune 500s Are Buying)

    5d ago

    AI Heart Doctor (And 150 Fortune 500s Are Buying)

    Your blood pressure spikes the moment the cuff goes on. You are sitting on crinkly paper in a cold room, and the number on the screen has almost nothing to do with the life you actually live. This is the white coat problem, and it is a tidy little metaphor for everything broken about reactive healthcare: we measure people at the exact wrong moment, in the exact wrong place, and then we wonder why outcomes lag. Amir from Hello Heart spends his days inside that gap. Hello Heart is a preventive heart health platform built around a connected blood pressure monitor, a smart pill box, and a mobile app, and it is trusted by more than 150 Fortune 500 and government employers. The newest piece is Nia, which the company launched in October 2025 as the world's first AI heart health assistant. This episode is the rare founder conversation that hands you the blueprint instead of the brochure. If you are building vertical AI, health tech, or any agent where a wrong answer carries real consequences, this is the one to study. The throughline is trust. Amir keeps returning to a simple idea: humans were never meant to be the data layer. The job of AI here is not to replace the doctor. It is to absorb the 90% of a visit that is administrative friction so the 2% that is actually human, the fear, the reassurance, the "how does this fit your life," can finally breathe. He calls it the shift from reactive to preventive, and he is blunt that the only way to earn it is to build guardrails most teams skip. https://www.helloheart.com https://www.linkedin.com/in/amir-dolev-b5618421/ https://www.helloheart.com/press/hello-heart-launches-the-worlds-first-ai-heart-health-assistant-nia https://ainativestudent.com ⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠ ⁠⁠https://aiforfounders.co⁠⁠ https://inboxalchemy.co/

    55 min
  4. The Self-Driving Car Of Men's Fashion

    Jun 19

    The Self-Driving Car Of Men's Fashion

    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/membership https://www.linkedin.com/in/zzkaru/ ⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠ ⁠⁠https://aiforfounders.co⁠⁠ https://inboxalchemy.co/ https://ainativestudent.com/

    44 min
  5. 40,000 Models, One API Key, And A $25M Bet On Open Source

    Jun 18

    40,000 Models, One API Key, And A $25M Bet On Open Source

    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.co⁠⁠ https://inboxalchemy.co/ https://ainativestudent.com/

    1h 2m
  6. He Analyzed Millions of Calls. The Move That Closed Deals Was a Laugh.

    Jun 17

    He Analyzed Millions of Calls. The Move That Closed Deals Was a Laugh.

    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.ai https://www.linkedin.com/in/nick-deveau-a6241379/ https://www.linkedin.com/in/estesryan/ https://aiforfounders.co https://inboxalchemy.co https://robinhood.org

    54 min
  7. AI Law Firm: The Logan Brown Playbook

    Jun 16

    AI Law Firm: The Logan Brown Playbook

    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/loganbrown799 https://www.linkedin.com/in/logan-brown-03765552 ⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠ ⁠⁠https://aiforfounders.co⁠⁠ https://inboxalchemy.co/ https://ainativestudent.com/

    56 min
  8. America Spends $5 Trillion On Health. This Is Where It Leaks.

    Jun 13

    America Spends $5 Trillion On Health. This Is Where It Leaks.

    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.health https://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/id1774334723 https://aiforfounders.co https://inboxalchemy.co https://ainativestudent.com https://www.linkedin.com/in/estesryan/

    57 min
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5
out of 5
48 Ratings

About

AI for Founders is where 47,000+ founders learn to build and scale with AI. Hosted by Ryan Estes, a Denver investor, creator, and founder, the show breaks down real strategies from top operators and AI visionaries. AI-ready data, zero-dependency workflows, founder-led distribution, and the tools driving revenue for today’s fastest-growing companies. If you’re a technical or non-technical founder who wants to work smarter, scale faster, and stay competitive, this podcast is your weekly unfair advantage.

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