AI for Founders with Ryan Estes

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

The Stealth Decade That Built a CategoryMost founders ship in six weeks and pivot in six months. Sameet Gupte and his four co-founders did the opposite. They put pen to paper in 2007, built in stealth from 2009 to 2019, and only then incorporated EvoluteIQ. No customers. No revenue. Just five operators with a thesis that everyone else in automation was solving fragments of the problem instead of the whole thing.When they finally went to market, they made another contrarian bet. They would sell only to Fortune 500 enterprises, the slowest and most cynical buyers on the planet. The first big pitch was to a Fortune 100 telecom that listened for two hours and politely showed them the door, telling them this was a 2030 problem. Sameet and his co-founder Naveen went straight to a London pub at 2:30 on a Tuesday. By the third pint they had decided they were coming back to win that account. A year and a half later, the same customer signed a multi-million dollar licensing deal.Today, 85 percent of EvoluteIQ's customers are Fortune 500. Net revenue retention runs above 120 percent. They have raised roughly $73 million, led by Baird Capital, and ARR is roughly doubling year over year. The shift that unlocked everything was philosophical. Sameet stopped selling technology and started selling outcomes, telling enterprise buyers, "Don't pay us if we don't deliver." That single sentence reframed every conversation from a transaction into a partnership.The Whole Problem, Not the PartsInputs and outputs are connected by people, culture, and processMost automation vendors automate fragments (a bot here, a workflow there)EvoluteIQ's thesis is full-stack, end-to-end orchestration of the process itselfThe technology must think, build, self-heal, and self-learn so humans can step out of executionSame Problem, Forever (The Anti-Pivot)Health and wellness is the example: reactive treatment 500 years ago, proactive screening 50 years ago, real-time wearables today, predictive prescriptive intervention tomorrowThe problem stays constant, the technology stack changes underneath itFounders should commit to a problem they would solve for life, not a featureOutcome-Based SellingStop pitching technology specs to non-technical buyersCo-define the outcome with the customer up frontTie commercial terms to delivery of that outcomeResult: shared accountability, not vendor-customer transactionsThe Partner Backdoor Into the Fortune 500A startup with no logos cannot get past procurement at a Fortune 500Pick 15 or so credible system integrators (HCLTech, PwC, WNS Capgemini, etc.) who already have 10 to 20 year relationshipsLet those partners carry the credibility while you carry the technologyOnce you deliver consistently, expansion becomes inboundRead the Tea Leaves on Two AxesBuild the right technology AND build the right distribution modelMost founders only optimize one of the twoEvoluteIQ optimized both: end-to-end stack plus partner-led GTMhttps://evoluteiq.comhttps://aiforfounders.cohttps://kitcaster.comhttps://createaloop.orghttps://www.linkedin.com/in/sameet-gupte-3421a71⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠

In a market obsessed with AI multiples and overnight unicorn exits, Bryce Nagels is making a different bet. The CEO and co-founder of Planteva Farms is building what he calls a "halo company": high asset, low obsolescence. The kind of business that doesn't get wiped out when the next model drops, and actually gets stronger every time AI improves.Planteva specializes in propagation. They take seeds, grow them into uniform, pest-free, disease-free transplants in a tightly controlled environment, then ship those young plants to commercial growers, indoor farms, greenhouses, and field operations. It's the most overlooked step in agriculture, and Bryce realized it was also the highest-leverage one. Get the first 12 to 14 days right, and the entire downstream economics of farming change.In this conversation with Ryan, Bryce walks through how a former software engineer ended up running a CapEx-heavy biology business, what he learned pitching 120 VCs and getting shut down by most of them, and how his agronomists are now using Claude to wire together multispectral cameras, climate systems, and lighting protocols without writing a line of production code themselves. He gets candid about the mental health toll of founding capital-intensive companies, why "the goalpost always moves," and why celebrating wins matters when you're already filing your Series A paperwork the day your seed closes.This episode is for founders who want to think bigger about white space — the categories AI can't replace, only amplify — and the specific advantages of building where software can't follow.The Halo Company Thesis (High Asset, Low Obsolescence)Sit at the intersection of physical infrastructure and biological realityBuild things that must exist and can't be digitized awayAI makes the business more valuable, not obsoleteDefensible moats: hard assets, proprietary processes, real-world outputsThe pressures (labor shortages, supply chain fractures, climate) compound your value over timeThe Brake Pad Strategy (Specialize on the Critical Step)Don't try to own the whole stack; own the step nobody else is optimizingPropagation is to farming what brake pads are to automotive: invisible, essential, and underbuiltConvergence creates opportunity: as industries mature, secondary solutions emerge that streamline the whole systemPosition yourself as the upgrade input, not the end productThe Multi-Recipe Propagation MethodOne seed, multiple growth recipes throughout a single 12 to 14 day cycleLighting changes 4 to 5 times based on destination environment (indoor vs. field)Multispectral cameras detect photosynthesis in real time and trigger biofeedback loopsSame crop, different protocols based on where the plant is going nextResult: celery germination jumped from 50 to 60 percent up to 89 to 95 percent, with crop cycle cut from 65 to 80 days down to 40 to 45The Capital-Intensive Founder's Investor FilterVCs want unicorn exits; CapEx businesses need different moneyTarget family offices, strategic corporates, large-scale operators with personal stake in the outcomeLook for investors with operational vision, not just capitalExpect rejection at scale (Bryce pitched 115 to 120 VCs); treat the muscle of rejection as a deliverableThe Founder Mental Health Operating SystemAcknowledge the isolation: high-stakes decisions early in your career with limited peers who get itBuild founder community deliberately (Bryce supports the Quebec ecosystem; Ryan referenced Hampton)Reject the "4:30 a.m. tech CEO" archetype as fiction for most operatorsCelebrate wins explicitly with your team, because the goalpost always moveshttps://www.plantevafarms.com/linkedin.com/in/brycenagels⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://trynina.co/

Jim Ferry has spent his career on the investor side of the table at Volition Capital, a Boston-based growth equity fund that writes Series A and B checks into capital-efficient companies between $1M and $10M in revenue. He's seen thousands of pitches, sat on dozens of boards, and watched the rules of building a defensible business get rewritten in real time over the last 24 months.The throughline of this conversation: code used to be the moat. It isn't anymore. What's replacing it is messier, more human, and harder to fake — distribution baked into a founder's personality, communities built on Reddit and LinkedIn, and a willingness to tinker at midnight with tools that didn't exist last quarter. Jim makes the case that the next generation of trillion-dollar businesses will not be built by the technical purists who dominated the cloud era. They'll be built by operators who know what they don't know, hire around their weaknesses, and treat AI not as a feature but as a substrate.He also gets candid about how Volition itself is changing. Their analysts now work alongside sandboxed Claude agents that surface 50 potentially interesting companies every morning. The traditional cold email playbook is dead. The dinner you weasel your way into is worth more than the conference you paid $25K to exhibit at.The Founder Journey in Three StagesBuild — Zero to one. Founder has hands on everything.Growth — Repeatable processes get installed. Trusted hires take work off the founder's plate. (This is where Volition typically enters.)Scale — The founder transitions from builder to operator.The Five Things That Matter in an InvestmentProductMarketManagementManagementManagement(Volition's half-joking internal mantra. The repetition is the point.)Make Yourself the Dumbest Person in the RoomSelf-awareness is the most underrated founder trait.The best founders identify their weaknesses and hire world-class talent against them.Jack of all trades, master of none — every time.The Optimist–Pessimist Co-Founder BalanceSkill complementarity matters less than mindset complementarity.Optimist + pessimist pairs tend to land on better decisions because they negotiate toward the middle.Durability in the AI EraCode is no longer defensible.New moats: first-party data, distribution baked into founder personality, proprietary integrations via non-public APIs, community ownership.The key diligence question at every firm right now: what makes this durable in three years?The New Sourcing RealityCold email is saturated; AI made canned outreach so good people now recognize it instantly.LinkedIn inboxes are next to flood.The unfair advantage: in-person meetings in a Zoom-default world. Founders remember a 45-minute coffee far longer than a Zoom call.https://www.volitioncapital.com/https://www.linkedin.com/in/jim-ferry-91b33375/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://trynina.co/ https://x.com/JimFerryVChttps://www.jimmyfund.org/

In 2017, while most founders were still debating whether chatbots had a future, Punit Singh Soni was studying speech models with the patience of someone who'd already seen what came next. He wasn't a healthcare guy. He'd run games at Google, built mobile apps, sat in the social team. But he understood one thing the rest of the industry was about to learn the hard way: AI was about to become the new UI, and the biggest unlock would happen wherever sophisticated users were drowning in repeatable, unstructured workflows they hated doing.That pointed straight at medicine. Doctors had become data clerks. Patients were getting 13 minutes of face time, half of it spent watching their physician type. So Punit founded Suki with a single mission: bring presence back to healthcare. Today, Suki is the ambient clinical intelligence layer running quietly inside Zoom, Optum, Athena, Meditech, and a growing list of healthcare giants, valued at roughly half a billion dollars and built on the contrarian belief that the best product in a regulated, bureaucratic industry isn't a feature, it's giving someone their time back.The Four Arcs of Ambient Clinical IntelligencePunit's mental model for what an AI layer in healthcare actually does:Clinical documentation — capturing what happened in the encounterAssisted revenue cycle — extracting financial information so the doctor and system get paidClinical reasoning — providing contextual information back to the doctor based on patient historyClinical operations — running agents on the encounter output to automate downstream tasksThe Android Analogy for Platform StrategyHow Suki structured its dual go-to-market without splitting focus:The Suki app is the "Pixel" — the reference implementation Suki sells directly to health systemsThe Suki platform is "Android" — given to companies like Zoom, Optum, and Athena to power their own clinical AI productsSelling the reference product teaches the company how to build the platform; the platform creates ecosystem footprintWhere AI Will Have the Biggest ImpactPunit's filter for picking a market in the AI era. Look for the intersection of:A sophisticated userLots of unstructured dataRepeatable workflows the user finds boring or burdensomeThe Eating Glass / Love Is a Strategy TensionBuilding requires a constant willingness to confront your own inadequacy. Surviving that requires self-empathy, which means extending care outward too. Aggression and warmth aren't opposites; they're the two halves of a sustainable founder operating system.The Future DoctorTomorrow's clinician is a student of medicine and AI both. The role shifts from gatekeeper of knowledge to guide who takes responsibility for the patient navigating a sea of tools and information.https://suki.aihttps://www.linkedin.com/in/punitsoni/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://trynina.co/

Most founders treat SEO like a slot machine. Pull the lever, publish a blog, pray to the algorithm gods. Kaelan Donadio, co-founder of Nina (trynina.co), walked into the studio and dismantled that fantasy in the first sixty seconds. Your blog posts aren't bad, he says. They're invisible. Google literally cannot find them, and no amount of ChatGPT-generated content is going to change that until you understand the mechanics underneath.What unfolded was a masterclass on the unsexy fundamentals that actually move organic traffic. Domain authority, backlinks earned through real PR, onsite content density, and the boring data markup that LLMs and search engines both depend on. Kaelan came up through startups before going out on his own, and that founder-to-founder lens shapes everything Nina builds. They're not a content mill. They're a system for the early stage operator who knows they need SEO but has zero hours to execute it.Then came the heretical take. GEO, AEO, whatever the latest acronym, is 90% just good SEO with an omnichannel layer on top. The brands winning in AI search are the ones doing the boring work right. Title tags. H1s. Internal links. FAQs that answer the question before anyone asks it. Kaelan walked through how Google treats AI generated content (it doesn't care, as long as it's good), why thin content gets ignored, and how podcast appearances function as both backlink engines and LLM training signals. He even ran a free audit on the AI for Founders domain mid-episode.The conversation closed on something deeper. Marketing is a game of resiliency. Most founders quit at three episodes, three blog posts, three cold emails. The ones who win are the ones who keep showing up after the dopamine wears off.The Domain Authority Threshold FrameworkBelow 35: Google is ghosting you, manual indexing requiredAbove 35-40: Content gets crawled and indexed faster, keyword growth visible in 1-3 weeksDomain authority is built through two levers: time + backlinks + onsite content densityManual submission through Google Search Console is the workaround almost no one usesThe Earned Backlink HierarchyTier 1: Earned PR through podcasts, industry media, local news (highest credibility transfer)Tier 2: Self-driven press releases (lower link value but high LLM dissemination value)Tier 3: Bought backlinks (use sparingly, never point all to one page, Google punishes patterns)Avoid: Bulk purchased backlinks pointing at homepage (instant penalty territory)The Three-Hour vs Three-Minute Content TestAI lets you compress three hours of work into three minutesFounders expect three-hour results from three-minute effortThe fix: either accept fractional results, or invest in human "massage" of AI draftsBrand voice, internal linking, external linking, and image relevance are where AI failsThe High-Ranking Blog Post ChecklistTopic research: blend low keyword difficulty with high search volumeContent quality: net new information, not regurgitated jargonLink structure: internal links AND external links (even to competitors)Data markup: H1, H2, author schema, image alt text, meta descriptionFAQ block at the bottom: answers questions before they're asked, drives LLM visibilityThe 10-15% Content RuleBlog content is roughly 10-15% of your SEO successSite health (load times, 4xx errors, mobile responsiveness) carries the restPlug content into a sound system or it underperforms regardless of qualityhttps://trynina.cohttps://www.linkedin.com/in/kaelan-donadio-0b09b7113/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠https://aiforfounders.co

Most founders are still asking how to use AI. Dave Sifry is asking something stranger: what if the org chart itself is the product?Nine companies in, Dave is running what he calls a Meta Factory, a system that spawns entire businesses with AI co-founders at the helm. Two of those companies are already live. One is cashflow positive. And the AI CEO, not Dave, is the one deciding to plow the money back into go-to-market instead of more product.The episode opens with a heretical idea: corporations were always proto-AGI. They run 24/7, outlive any single human, coordinate thousands of moving parts, and operate without emotion. So if we already trust corporations to act like superintelligences, why not formalize the analogy and let the agents actually run them?Dave walks through the architecture he's been refining. There's an AI CEO, an AI COO running standard operating procedures, an AI CFO holding the wallet, a chief of staff verifying that SOPs are actually being followed, and an "eye in the sky" agent that watches every other agent without being seen by any of them. Human contractors get tasked, paid, and managed by the agents above them, and they have a direct escalation line back to Dave the moment anything feels off.The juicy part is the operating cadence. Every day at 6pm, a daily retrospective runs across the agent stack. Roses, thorns, votes, ranked outputs, fed straight into tomorrow's goals. It's an hour-a-week ritual when humans run it. Agents run it in minutes, ten times a day, and never get passive aggressive about it.But the real lesson Dave keeps hammering: policies, guardrails, and gateways are not the same thing. A policy is a sentence in your agents.md. A guardrail is a prompt that audits behavior. A gateway is the actual credit card limit, the GitHub action, the CI/CD hook that makes the wrong move literally impossible. If you only have policies, you have wishes.The Hybrid Human Agentic Org ChartFounder sets direction and high-level goalsAI CEO drives strategy and reports to founderAI COO owns SOPs and organizational designAI CFO holds the wallet and enforces spendChief of Staff verifies SOPs are followedSpecialist agents (marketing, sales, security review, architecture review)Eye-in-the-sky agent watches everyone, visible to no oneHuman contractors handle judgment, taste, platform-specific work, and ethics escalationThe Identity-Memory-Governance StackIdentity: every agent has a clear, consistent role and personalityMemory: agents need a sense of past decisions and current goalsGovernance: hierarchy, accountability, isolation between agentsVerification: adversarial review by other agents with different rubricsLearning: daily retrospectives feed organizational memoryPolicy vs Guardrail vs GatewayPolicy: written rule (e.g. "spend no more than $100/day")Guardrail: prompt or check the agent runs to self-auditGateway: hard enforcement at the infrastructure layer (credit card limits, CI checks, GitHub actions)Without gateways, policies are just suggestionsThe Daily Retrospective LoopEach agent submits roses and thorns privatelyAllocate 5 votes across each categoryRank outputs collectivelyDiscuss top items brieflyFeed conclusions into tomorrow's goals and SOPshttps://repofortify.comhttps://braingem.aihttps://www.linkedin.com/in/dsifry/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠https://ainativestudent.com/⁠https://aiforfounders.co⁠https://inboxalchemy.cohttps://trynina.co/

Most founders don't think about HR until HR thinks about them. And by then, it's a letter on the desk demanding $38,000 and a lien notice attached for good measure.This week on AI for Founders, John, the founder of CogNet HRO, walks through the quietly catastrophic world of multi-state payroll, the surprise tax bills no one warns you about, and why a guy who spent fifteen years running this thing as a side hustle suddenly grew it from 67 to 600 employees in under five years. He moved offshore back when "doing business in India" still made boardrooms nervous, built a 600-person team in Chennai, and now runs a service operation that lets founders skip the part where they wake up at 2 AM wondering if California changed its overtime laws again. (Spoiler: California changed its overtime laws again.)The conversation goes deep on what AI can actually do for HR right now, what it absolutely cannot, and why CogNet built its own internal ingestion tool called Drive instead of letting client PHI bounce around inside Claude or ChatGPT. John is refreshingly blunt: most of the AI tools the big payroll providers are bragging about are still glorified bots. The real wins are in robotics, document migration, and the unsexy automation work that lets a small founder team punch above its weight.Frameworks discussed:Land and Expand: Solve one acute pain (usually a tax notice), then earn the right to handle payroll, benefits, finance, and HRIS implementation. CogNet is internally organized by practice area, not client, so the expansion is structural.The Bus Theory of Hiring: Don't fire fast, reseat fast. The hard skill is figuring out where someone fits, not deciding they don't. Took John three years to nail this with one senior manager.Predictive Hiring Modeling: CogNet is pulling its own historical hiring data to model who actually thrives, knowing humans are irrational but the patterns aren't.Ingest First, Decide Second: Drive is built to absorb anything (PDFs, registers, JSONs from terminated providers) before any decision gets made about whether AI, robotics, or humans handle it.Robotics Over AI for Repeatable Tasks: When the job is "do these five steps 500,000 times," skip the LLM. Spin up 18 robots on AWS and let them grind 24/7 without exposing data.Multi-State as the Trigger Point: The moment a company hires across more than one state, the compliance math changes. That's the founder's signal it's time to outsource.https://www.cognethro.comhttps://www.linkedin.com/in/john-sansoucie-033b20/https://www.linkedin.com/in/estesryan/⁠⁠https://www.inboxalchemy.cohttps://www.aiforfounders.cohttps://trynina.co/

Rebecca Liao spent her career advising the most powerful people in the world. Clinton's campaign. Biden's transition. The Pentagon's policy halls. And then one day she realized something brutal: she didn't want to give advice anymore. She wanted to build.Now she's running Saga AI Labs, a company quietly rewiring how brands acquire customers. Forget influencer budgets. Forget CPM. Forget cold email. Rebecca's team is training character agents (think Mario, think the Trivia Crack mascot Willie) to slide into your DMs, hold real conversations, and convert at rates that make traditional UA look like a slot machine.Willie alone is hitting 90% engagement on every comment he posts.In this episode, Rebecca breaks down why character-driven AI isn't just a gaming play. It's the next distribution model for every consumer brand on the internet. She talks about the day she realized blockchain wasn't going to solve the scale problem (AI was), the philosophical knife-edge of synthetic relationships, and why she thinks Anthropic just wrote the playbook every founder should be studying.The Synthetic Relationship FrameworkTrain agents on the lore, history, and personality of an existing IPDeploy across Instagram, TikTok, X, Reddit, WhatsApp, Discord, MetaUse modular personalities so individual traits can be tuned without rebuilding the whole agentMatch user energy in conversation while holding brand guardrails (no politics, no religion, no cursing)Turn one-to-many advertising into one-to-one relationships at scaleThe Saga User Acquisition PlaybookCrawl social platforms for users matching the core demographicComment on trending topics, not branded keywordsOpen a DM channel and let it warm naturallyConvert through MNP links tracked by the studioRe-engage churned users without becoming spamThe Compelling Agent TestPersonality holds even under stress-testing from usersConversations move from functional ("I'm stuck on this level") to personal ("how was your day")The agent leads users deeper into the community, not just the productPlatform algorithms reward quality, not chat-bot volumeThe Two Saga Business ModelsMonthly package covering text messages plus voice and video minutesRevenue share averaging 50% of agent-attributable saleshttps://www.saga.xyzhttps://www.linkedin.com/in/rebecca-liao/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://inboxalchemy.co/

Most founders are racing to build on top of the foundation models. Dan Pratl is doing something stranger and more interesting: he's betting against them. Or more precisely, he's betting against the assumption that the artifact, the output, the polished deliverable, is the thing that matters. Dan thinks expertise itself is the scarce resource of the AI era, and he's building Quadron to capture, verify, and trade it.His path to this thesis is improbable. He started his career at the SEC during the Great Recession, watched regulators chase the wrong things, and walked. He moved into open source, then crowdfunding (where he co-founded Alum Shares and raised roughly $4.5M at $5,000-per-clip from strangers online), then crypto as Chief of Staff to the CEO at Ava Labs. Each pivot taught him the same lesson from a different angle: incentive systems get captured, mechanisms calcify, and the people doing the actual work rarely get rewarded in proportion to what they create.Quadron is the culmination of those scars. The company has three product layers. The institutional layer is what Dan calls "a judo move against the 800 pound gorillas," a multi-tier agentic system that gives organizations persistent memory, context, security, and auditability, things the foundation models will never offer because they want you in their sandbox. The individual layer is "verification," which captures what Dan calls your lens: the encoded prism of how you think, weigh evidence, and make judgment calls. The third layer is "credibility markets," an inversion of prediction markets where you bet on yourself by exposing your lens to other people's lenses and getting real-time calibration of your value.The big idea underneath all of it: the artifact is no longer where the value lives. Output is becoming abundant. What matters now is the prism by which you got there. Quadron wants to make that prism structured, portable, durable, and tradeable.The Lens vs. The ArtifactThe artifact is the output (book, brief, deck, code). AI can generate infinite high-quality artifacts.The lens is the encoded expertise: how you weigh evidence, spot issues, deduce uniqueness.Organizations keep the artifact. Individuals keep and carry the lens.The lens dynamically updates over time based on accuracy and effectiveness.The Three-Layer StackInstitutional AI: persistent memory, auditability, ensemble approach across models.Verification: structuring secrets so individuals own their prism while organizations get utility.Credibility Markets: a marketplace where lenses are tested against other lenses for real-time signal.The Inversion of Prediction MarketsTraditional prediction markets bet on outcomes.Credibility markets bet on the process that produced the outcome.Reputation becomes portable, not trapped inside Uber, Upwork, or LinkedIn.Good Friction as Design PrincipleLLMs are an "easy button" that hallucinate because users have no skin in the game.Pride of authorship in your tools forces quality control.Friction is the feature, not the bug.Maslow's Hierarchy as a Founder Targeting ToolGet as low on Maslow's hierarchy as possible.AI anxiety hits at a primal level (am I still valuable?).Solve a real problem at the bottom of the pyramid and you have a market.The Unbundling ThesisMedia unbundled over 30 years (NBC monoculture became Reddit's network of communities).Markets are next: assets, market makers, and evaluators all collapse into the individual.Real-world assets on chain is just "putting radio on television." The interesting question is what becomes an asset that wasn't one before.https://quadron.techhttps://pratl.me/https://www.linkedin.com/in/danpratl/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠https://inboxalchemy.co/

⭐⭐⭐⭐⭐The Anti-AI Asset: How Nathan Jameson Builds Fortress Wealth in a Market Obsessed With HypeNathan Jameson sits outside Philadelphia with a human skull (replica) on his desk and a fundamentally different worldview than the founders currently torching runway chasing the next model update. While Silicon Valley places hundred-x bets and watches whole categories get absorbed in a Tuesday release, Nathan quietly compounds mid-teens IRRs on assets everyone else finds unsexy. Mobile home parks. RV parks. Self-storage. The stuff nobody brags about at dinner.His firm, arxventures.com (Latin for fortress), was born in 2016 after Nathan spent his early career in land development and home building, including a front row seat to the carnage of the Great Recession, when a single webpage tracked the thousands of home builders filing for bankruptcy week after week. That scar never left him. It shaped an investment philosophy built around one question most founders are too busy to ask themselves: are you building something that depends on attention, or something that compounds without it?The frameworks Nathan uses to answer that question are the real meat of this episode.The Recession-Resistant Asset FrameworkTarget mid-teens IRRs over the life of the investment, yielding a high 1x to low 2x equity multiplePrioritize assets with meaningful depreciation to offset gains from other investments, including tech exitsRequire a roughly one-third higher return from any non-real-estate asset to match the tax-adjusted return of manufactured housingRefuse to over-leverage, so the investment never goes "poof"Make the first and largest commitment from the family office before inviting outside capitalThe Supply-Demand Imbalance ThesisDemand for affordable housing is through the roof because a home can be bought for $75K to $150K with lot rent plus utilities of $500 to $1,000 a monthSupply of new manufactured housing communities is effectively zero nationwide, particularly in the NortheastEveryone wants affordable housing. Nobody wants it near them. That imbalance is the opportunityFocus on regions where the right to build is hardest to secure, not the "smile states" where supply catches up fastThe Cave People Problem (Citizens Against Virtually Everything)Municipal meetings are dominated by the loudest opposition, not the silent majority coaching little leagueDown-zoning acts as an uncompensated takingMunicipalities in Pennsylvania have been known to sue their own zoning hearing boards to block reasonable parking reductionsBureaucracy plus "we just want to wait it out" is why real estate is notoriously slow to adaptThe AI Disqualification StackUse Claude (primary) and ChatGPT to sift deal flow and kill bad deals before human underwriting time is wastedRun non-negotiables as an automated first pass: property in a regulated floodway, aging private infrastructure like a 60-year-old wastewater treatment plant, missing financialsLeverage Claude's Excel integration for reporting and formatting that used to require an Excel whizBuild outbound lists and mailing campaigns to find park owners who don't live on-siteThe Density ArgumentA half-acre lot is not open space, it's someone's private propertyTrue open space preservation requires building as densely as possible where you do buildAggregate green space into shared pocket parks rather than scattering it across suburban lawnsAutonomous vehicles will eliminate most parking requirements, and municipal planning is nowhere near readyhttps://www.arxventures.com/https://www.linkedin.com/in/nathan-jameson/https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠

Bob Matteson grew up around a father who quietly carried a piece of history with him for decades. The dad attended Game 6 of the 1945 Cubs vs. Tigers World Series. Bob never knew. The story surfaced only after his father passed, dug up secondhand from his mother. That single missing thread, a baseball game his dad never spoke about, planted the question that would become a company: what happens to the memories we never bothered to capture in context?Years later, Bob became a father himself. He noticed his behavior had quietly shifted. He was photographing everything. His daughter's first laugh. The eggs his babies ate at their tiny breakfast table. The vaccine band-aid from her first pediatrician shot, kept in a box because it felt right to both him and his wife. He looked at the chaos of his camera roll, looked at his pre-kids and post-kids self, and realized the camera roll was not a memory system. It was a graveyard.Then he did something most founders never do. He waited. He sat with the idea for months. He let himself fall in love before spending a single dollar of someone else's money. Only after he was fully committed did he raise pre-seed capital, mostly from friends, family, and operators who believed in his vision.The original Relivable was a consumer-facing memory app. Then six months ago, a venue showed him something he wasn't expecting. The hotels and resorts he was meeting with kept asking if they could use Relivable internally for sales. They couldn't find good content to show prospects. They couldn't personalize the pitch for a black-tie wedding versus a casual buffet party. So Bob took a step back, did the research, and built a second product. Relivable became B2B2C overnight, with consumer reach distributed through every venue partnership.The seed round closed this spring. The cap table now includes hotel operators, event planners, and the celebrity event planner whose team is actively giving product feedback. The conviction is clear: today's couples have had iPhones their entire adult lives. They expect instant gratification, personalization, and AI-driven curation. Hotels know this and have no idea what to do about it. Bob does.The "Fall in Love First" Capital FrameworkBob's discipline around when to take outside money is a masterclass in founder accountability:Spend your own capital during research and validation. Losing your own money is acceptable. Losing someone else's is a contract.Only raise pre-seed when you are fully committed. The investor relationship is a formal promise to do your best for an outcome.Use the pre-seed period to validate, not to scale. Mistakes are expected. Communicate them."Graduate from pre-seed" by hitting three markers: conviction in product, paying customers (even if not product-market fit), and a validated go-to-market strategy you can execute on.Use seed capital to go faster, not to do more. Speed is the moat when AI compresses build cycles to weeks.The Distribution-on-the-Cap-Table FrameworkBob built two cap tables this way and it has become his signature move:First checks should come from operators inside your target customer base. They give you access to what they control plus their peer network.Diversify stakeholder types. For Relivable, that meant venue owners, venue operators, event planners, and the celebrity-tier event planner whose team becomes a live focus group.Cap table relationships compound. The introductions you get from a strategic investor are worth more than the check.One investor type is not enough. Distribution requires hitting the category from multiple angles.https://www.relivable.com/https://www.linkedin.com/in/bobmatteson/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠⁠⁠https://ryanestes.info⁠⁠⁠

Stephen Rouse didn't set out to pick a fight with Google, OpenAI, Amazon, and Microsoft. He just noticed something broken. Every founder in his orbit was tracking their body through a circus of apps that refused to speak to each other. A Whoop on the wrist. A Garmin for skiing. MyFitnessPal for food. Epic MyChart for labs. Strava for runs. Six logins, zero clarity. Meanwhile, the 21st Century Cures Act had quietly opened the door: third parties could now legally pull patient medical records directly from hospital EHRs. Stephen and his co-founder Amit Shah had already spent years building exactly that infrastructure at their previous company, Protocol First, which was acquired by Roche Pharma via Flatiron Health after becoming the first FHIR app to extract patient health data from Epic hospitals for FDA clinical trial submissions.So they built Savva. A unified health intelligence layer that pulls in your medical records, your wearables, your labs, and your meds, then lets you run them through Claude, GPT, Gemini, Grok, Llama, Falcon, Mistral, and Med Gemma like a round table of second opinions. For ten dollars a year. Stored locally on your device. Not sold to insurers. Not uploaded to a cloud that gets monetized in a bad quarter. Not harvested when the CEO decides he wants a bigger house in Tahoe.The philosophical core of the episode is trust. Stephen argues that people lie to their doctors because the incentives are broken. Admit you smoke a cigar on the golf course and your life insurance premium jumps three hundred dollars a month. Admit you had seven vodka sodas last night and it lives on a clipboard forever. But you'll tell the AI. Because the AI already has the data, doesn't judge you, and isn't reporting back to your payer. When healthcare finally gets a system that sees everything and costs nothing, the entire concierge medicine model starts looking expensive by comparison.The Unidentified Data Principle — Most apps say encrypted, in transit, at rest, de-identified. Stephen goes one step further.No accounts. Nothing tied to a person.Local device storage, not cloud storage.App grows on your phone as records accumulate, not on their servers.If acquired tomorrow, there's no data sitting there to monetize.The business model physically cannot pivot into data harvesting.The Round Table of Second Opinions — Instead of marrying one model, let the user poll them.Ask the same health question to Claude, GPT, Gemini, Grok in sequence.Each model has different training data, different personality, different blind spots.Cost is distributed: roughly 12,000 questions a year across all models for ten dollars.Replaces the "I don't trust that doctor, I want a second opinion" loop with a two-second model switch.The Blue Collar Infrastructure Play — How Savva got to 314,000 connected healthcare institutions without venture capital.Direct EHR integrations instead of Health Information Exchanges like Commonwealth or Health X.No middleman API fees to bleed unit economics.Wearables pulled through Apple HealthKit instead of direct Whoop, Garmin, Oura APIs.Free ingestion on both sides, which is what makes a ten-dollar price point survive.The Global Footprint Thesis — The reason the price is ten dollars a year is not marketing.One hundred million people in the West have access to modern EHRs.A billion people in underserved regions do not, and will not in our lifetimes.An EHR build costs hundreds of millions of dollars and takes a decade.Savva works without an EHR: upload a document, it treats it as a visit, and chronological history emerges.The ten-dollar price is designed to be swallow-able in Dar es Salaam.⁠https://www.savva.ai⁠https://www.linkedin.com/in/rousestephen/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠⁠⁠https://ryanestes.info⁠⁠⁠

The Will You Don't Have Is Already Costing YouMost people think estate planning is something you do when you're old, wealthy, or both. David Rosati spent 15 years as a corporate and M&A lawyer watching that assumption wreck families. The paperwork gets avoided. The conversations never happen. And then someone dies, and suddenly everything that should have been simple becomes a courtroom fight.So he built something to fix that. Succession Wills is a flat-fee online will builder, starting at $79.99, designed to give regular people the legal document they need without the lawyer bill they've been dreading. David is one half of a fully bootstrapped two-person team. They launched in January. They have no investors and no office. And they rebuilt their entire front end, from scratch, in a matter of days, using AI.That's not the wild part. The wild part is how they're using AI inside the product itself.Framework 1: Deterministic Logic Plus Conversational AIMost online will builders are wizard-based forms. You fill in fields, answer dropdowns, and a document gets generated. The problem is that approach assumes you already know what you want and understand every question being asked. That's almost never true.David describes the traditional lawyer experience as a back-and-forth conversation. A lawyer asks questions, interprets answers, explains concepts, offers examples, and gently redirects when you're overthinking something. That's the experience Succession Wills is trying to replicate.Their solution is a split architecture:The will itself is generated by a fully deterministic system. Every line of text that could appear in the final document was authored by David and his co-founder Nick. No AI is drafting legal language.The AI layer sits on top of that system as a trained conversational guide. It walks users through the process, answers questions in plain language, and surfaces the right prompts at the right moment.The result is something closer to having a lawyer in the room than clicking through a form.Framework 2: Perfect as the Enemy of Good (Applied to Estate Planning)David has a clear take on how to actually get a will done: stop waiting until it's perfect. The biggest threat to completing a will isn't complexity. It's the emotionally loaded questions, like who gets Dad's guitar, that cause people to stall and never finish.His advice:Get the document done first. "All my stuff goes to my kids equally" is a legally valid will.Sentimental and specific bequests can be handled in a separate non-binding rider that doesn't tie the executor's hands if circumstances change.Succession Wills offers lifetime platform access for one flat fee. You can revise whenever life changes, without paying again.The core insight is that a will should be a living document, revisited after major life events, not a one-time ceremonial act.Framework 3: The LLM-as-Wireframe MethodDavid has developed a practical framework for how founders and individuals can use AI responsibly in legal contexts without replacing professional counsel entirely.Use an LLM to draft a first version of any agreement: partnership, NDA, employment contract, prenup.Treat that output as a wireframe, not a final document.Bring that wireframe to a lawyer. The expensive part of legal work is the blank-canvas drafting. Show up with 80% done and you've cut the billable hours significantly.This is a reframe most founders haven't considered. AI doesn't replace the lawyer. It dramatically reduces what the lawyer has to do, which reduces what you pay.https://www.successionwills.com/https://www.linkedin.com/in/david-rosati-aa8b91100/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠⁠⁠https://ryanestes.info⁠⁠⁠

Devansh walked into the legal tech market and saw a graveyard of point solutions. Word doc plugins. Document hosting tools. Niche contract reviewers. Each one promising to make attorneys more efficient, and each one adding another tab to an already fragmented workflow.That is the problem Irys was built to eliminate.Devansh, co-founder of Irys and creator of the AI Made Simple newsletter, reaching over 1.5 million people monthly through what his community calls the Chocolate Milk Cult, did not set out to make a better legal AI tool. He set out to rebuild the infrastructure underneath legal work entirely.The Fragmentation ProblemMost legal AI today is what Devansh calls a system prompt wearing a trench coat. A niche product wraps a general-purpose model, calls itself a legal AI, and charges per word or per page for the privilege. The result is that small and mid-sized law firms get overwhelmed trying to stitch together 10 point solutions, none of which talk to each other and none of which understand the full context of a case.Irys attacks this from the foundation.Built ground-up as a full end-to-end legal platform, not a wrapperProcesses unlimited documents without vector search limitationsBuilds entity maps and relationship graphs across the entire document setFlags contradictions, jurisdictional mismatches, and contextual gaps that RAG-based systems missDelivers a transparent, auditable thinking trace so attorneys can verify every recommendationRuns 50 to 60 argument simulations and identifies which ones are likely to succeedThe Three Categories of HallucinationDevansh breaks legal AI hallucinations into three categories:Citation hallucinations. The AI cites a case that does not existApplicability hallucinations. The case exists, but the jurisdiction, domain, or context makes it inapplicableContext hallucinations. The AI misses a relationship between documents, where one document modifies, contradicts, or conditionally applies to anotherThe third category is the most dangerous and the hardest to catch with traditional vector search. Irys addresses it with a self-updating knowledge graph that links entities, propositions, and assertions across the entire document set.The Democratization MissionDevansh grew up watching legal inaccessibility cause real harm. In India, civil cases carry a 10-year backlog. In New York City, tenants get bullied by landlords because they cannot afford to fight. His co-founder, a former Big Law attorney, had lived the inefficiency from the inside.Their shared conviction is that there is no technical reason legal work has to take this long or cost this much.That is why Irys is free to sign up. That is why Devansh open-sources parts of the stack, including latent space reasoning work he believes will define the next generation of AI reasoning models. That is why the platform is being positioned not just as a tool for firms, but as infrastructure for justice.https://www.irys.ai/https://www.linkedin.com/in/devansh-devansh-516004168/https://substack.com/@chocolatemilkcultleader⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠⁠⁠https://ryanestes.info⁠⁠⁠

Most founders obsess over the wrong leverage point.Not the funnel. Not the product. Not the team. The voice in your head running all three.Dr. Dhruva Gulur grew up in Juneau, Alaska, the child of a schizophrenic mother, a father with full narcissistic personality disorder, and a brother struggling silently with addiction. He watched his family fracture in real time and absorbed it all without language to process it. What he built instead was architecture, behavioral scaffolding that helped him survive, but later threatened to bury him.He made it to India. Got seven scholarships into medical school. Became a doctor. And then, quietly, began drowning. Sixty pounds of weight gain. A $300,000 gambling debt. A hundred thousand dollars in credit card debt. A cocaine-induced manic episode. Three months in a dual-diagnosis rehab center in Warrior, Alabama.He had everything society said meant success. And he hated himself.What followed was not a redemption arc powered by willpower or a mentor or a morning routine stolen from a podcast. It was ten years of radical solitude, daily writing, rapping through emotional honesty, and the systematic reconstruction of identity from the inside out. It produced a framework he now calls Mind Hygiene, and a philosophy of self-reliance he calls Neuro Spiritual Sovereignty.He calls the outcome Structural Density: a life so internally clean that your files are labeled, your fridge matches your mind, and you operate from full presence rather than constant cortisol.Framework 1: The ACES FrameworkDr. Dhruva's daily writing practice follows the ACES structure:A: Accept your awareness around any event without trying to fix, suppress, or reframe itC: Compassion expressed through doing something you do not want to do, forging health through action not feelingE: Empathize with yourself and others involved in the situationS: Soften and Alchemize by turning resentment into purpose, and easing the process so it does not feel like sufferingThis replaces FACES (Fixing, Avoiding, Controlling, Escaping, Suppressing), which is how most people handle difficult emotions.Framework 2: Neuro Spiritual SovereigntyThe journey from fixed mindset to sovereign self moves through three stages:Fixed Mindset: External validation required, cortisol constantly elevated, dopamine sought through substances, food, attentionAcceptance Mindset: Beginning to observe without judgment, writing to engage the prefrontal cortex, reducing amygdala activityConsecrated Mindset: Full self-reliance, surrendering to higher purpose, 60 to 70% emotional baseline of well-being without external inputFramework 3: Structural DensityA state in which the internal and external environment are aligned and uncluttered:One tab open at a timeLabeled files and clean digital environmentsDiet free of inflammatory foodNo emotional dependency on others for baseline stabilityMission-driven financial consecration (donating 70% of speaking fees, 30% of book sales)Framework 4: Mind HygieneA four-year retrospective observational study on 4,000+ patients using 90-second writing reflections every 90 minutes for 90 days produced measurable improvements across five domains of health:Spiritual Health: Clarity of mission and purposeMind Health: Awareness and self-compassionPhysical Health: Reduction of inflammatory behaviorFinancial Health: Consecration of resources toward higher purposeExecutional Health: Single-task focus, delayed gratificationThe neuroscience backing it: writing by hand engages the prefrontal cortex, decreases amygdala activity, stabilizes serotonin, and has been shown in multiple studies to improve immune function.https://dhruvamd.com/https://www.linkedin.com/in/dhruvamd/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠⁠⁠https://ryanestes.info⁠⁠⁠https://www.createaloop.org/

Most founders aren't short on information. They're short on signal. Kevin, founder and CEO of Snipd, has been quietly solving the problem that every high-volume podcast listener knows intimately: you have hundreds of episodes queued up, a finite amount of attention, and no good way to extract the gold without siting through the banter.In this return visit, Kevin pulls back the curtain on Snipd's newest feature: the Podcast DJ. Think of it as a personalized audio moderator that analyzes an episode, identifies the highest-value moments, and guides you through them one by one, complete with intros, segues, and a closing takeaway summary. You still hear the real voices. You still get the original tone and energy. You just skip to the parts that matter. Kevin's promise: get through a podcast episode in 25% of the time.Frameworks DiscussedThe Signal-to-Noise Problem in Content ConsumptionThe Highlight Reel ModelPersonalization as the North StarThe Hive Brain AdvantageContent Creator vs. Listener ControlGet a month free with Snipd -> https://link.snipd.com/Cx7S/ryanesteshttps://www.linkedin.com/in/kevin-smith-673714b4/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠⁠⁠https://ryanestes.info⁠⁠⁠

Dr. Ian Ellis, Founder of voafit.com | Precision Dosing, Peptides, and the Future of Human PerformanceThe story starts in an emergency room. Dr. Ian Ellis spent almost a decade watching the same patients cycle through with the same problems, receiving the same treatments, never actually getting better. Just bailing out the pool, he says. That disillusionment became the seed of something bigger.When Dr. Ellis was prescribed semaglutide in 2022, he experienced what millions of people experience every day: real weight loss with a catastrophic tradeoff. Thirty pounds gone. But the body composition scan told the real story. He had lost twice as much lean mass as fat. Same body fat percentage. Just a lighter, weaker version of himself. The drug had done what it was designed to do. The problem was the dosing.That realization sent him down a research rabbit hole that ended with the founding of his concierge practice and an app called My Level, designed to help patients find their minimum effective dose of GLP-1 medications, not the maximum tolerated dose. The results at his clinic have been remarkable: faster weight loss than clinical trials, on half the medicine, with zero desistance due to side effects.Key Frameworks:The Precision Dosing Model: Standard GLP-1 protocols escalate doses on a fixed schedule regardless of individual response. Dr. Ellis argues this is backwards. The goal is to find the lowest dose that suppresses appetite just enough to create a 500-750 calorie deficit, not to eliminate hunger entirely. Think dimmer switch, not on/off toggle.The Appetite-as-Physiology Framework: Willpower is not a weight loss strategy. Dr. Ellis compares appetite suppression to sleep deprivation. You can fight it for a day or two, but biological drives increase in intensity until they become inevitable. The solution is not discipline. It is solving the physiologic problem.The Nutrition Hierarchy on GLP-1s: Because appetite is suppressed, what you eat first matters enormously. If you fill up on carbs, you will never reach protein and plants.The Cost-Convenience-Quality Triangle: You only get two. Cheap and convenient equals low quality. Convenient and high quality equals expensive. Inexpensive and high quality means you are cooking it yourself. There is no fourth option.Peptides as Information Systems: Peptides are strings of amino acids that act as keys for specific biological locks. Their safety profile is relatively predictable because they bind to one receptor and produce effects that follow logically from what that receptor does. GLP-1 receptor? Suppresses appetite and slows gastric motility. Overdose? Stomach stops working. Predictable. Manageable.The 15% Body Fat Sweet Spot: Evolutionary biology has calibrated human attraction toward function, not aesthetics. Studies show 15% body fat consistently ranks as most attractive across populations because it signals strength, capability, and survivability. Single-digit body fat is not optimal health. It is a performance liability.https://voafit.com/https://www.linkedin.com/in/voafitmd/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠⁠⁠https://ryanestes.info⁠⁠⁠

★★★★★You can automate your outreach. You can spin up agents overnight. But you cannot automate the moment someone walks into a room and feels seen.Virginia Frischkorn has produced several hundred million dollars worth of live events across 18 years. She is the founder of Partytrick, a platform she describes as having a professional event planner in your pocket. Her user is not the professional event planner. It is what she calls the Secret Event Planner: the founder, the team lead, the parent, the person who got voluntold into hosting something they've never done before and needs to not embarrass themselves.This conversation is a masterclass in why the further we go into technology, the more a well-designed room is worth.Frameworks from the EpisodeStart with the WhyVirginia returns to this principle every time the conversation drifts toward logistics. Before you book the venue, before you curate the guest list, before you order the swag, ask why you are doing this event. Is the goal press? Lead gen? Community? A brand moment? A splashy launch? The answer to that question changes every single downstream decision. Founders who skip this step run events that feel busy but accomplish nothing.The Secret Event PlannerPartytrick was not built for professional event planners. It was built for the person who is suddenly responsible for a networking happy hour or a product launch and has never done it before. Virginia calls this person the Secret Event Planner. The platform walks them through blueprints, timelines, and checklists so that the basics are covered and the founder can spend mental energy on the things that actually create memory.Engineer the Room, Do Not Just Fill ItGuest list curation is a strategic act. Virginia deliberately mixes people across career stage, industry, and background because friction between unlike people creates energy. She also recommends going 60/40 for community-building events: 60% recurring attendees to create the sense of tribe, and 40% new faces to keep it from going stale. A room full of people who are exactly alike is comfortable and forgettable.The Peaks, Pits, and Bookends Principle (The Power of Moments)People do not remember the middle of an experience. They remember the beginning, the end, and the moments that surprised them. Virginia designs for surprise and delight deliberately: a magic eight ball at a trade show booth, a garden gnome hidden in the bathroom, a key party fishbowl at a product demo. These are not gimmicks. They are engineered memory anchors.Start Small and Get the RepsVirginia told Ryan the same thing she told her 11-year-old son before a difficult apology: practice in safe spaces before you do the big thing. A 10-person dinner in your living room is a real event. It gives you the reps to become a confident host. Confidence is not cosmetic. Guests read the energy of the host immediately. If the host is anxious, the room is anxious.The Duck PrincipleSomething will go wrong at every live event. The job of the host is not to prevent this. The job is to respond with the energy of a duck, calm on the surface while paddling underneath. No one in the room knows what was supposed to happen except you. If you act like it was planned, most people will believe you.Pre, During, and Post: The Full Arc of an EventVirginia sends playlists after her parties. She makes introductions via email after the night ends. She helps clients craft follow-up moments that extend the experience and deepen the memory. The event is not over when the last guest leaves. That post-event window is one of the most underused tools founders have for building real relationships.https://partytrick.com/https://www.linkedin.com/in/virginiatfrischkorn/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠⁠⁠https://ryanestes.info⁠⁠⁠

The average patient gets seen and disappears. No signal, no follow-up, no data trail. Just a receipt and a co-pay. Lauren Larson, CEO of Videra Health, knows exactly what lives in that gap, and he has spent six years building AI to close it.Lauren came up through HireVue, where video-based AI interviewed 100 million job candidates and surfaced the best ones through behavioral signal, not resume gatekeeping. When the company sold in 2019, he took everything he learned about reading humans through a screen and pointed it directly at behavioral healthcare.The Problem Videra Is SolvingThe system rewards patients who are good at making appointments. The people who are actually in crisis, the ones who missed their last visit, the ones who stopped their medication because of nausea, the ones who are not sleeping, those people spiral quietly. Videra uses AI-powered check-ins via audio and video to reach those patients between appointments, collect behavioral data, and surface the ones who need intervention back to their clinical teams.The platform is not trying to replace providers. It is trying to make sure providers only get interrupted when it actually matters.Core Frameworks DiscussedPassive vs. Structured Assessment: Lauren emphasizes the difference between conversational AI that just listens and structured clinical AI that knows which questions to ask first. The opening prompt is everything. Random check-ins produce noisy data. Calibrated sequences produce signal.Observational Biomarkers at Scale: Rather than guessing which features predict a condition, Videra trains on as many features as possible and lets the model surface what matters. The goal is 30 to 40 observational biomarkers detected in a single two-minute session, tracking movement, voice, language, and facial affect over time.The ROI Problem in Healthcare Innovation: Cool technology does not get deployed unless someone can pay for it. Lauren learned this lesson early. Videra had to expand beyond assessment into clinical documentation, patient intake, and provider coaching before the sales motion started working.Bias Testing Through Model Cards: For every predictive model, Videra builds model cards that track false positive and false negative rates across demographic and intersectional groups. Not just men vs. women. Not just race. But black women vs. black men vs. white women, and so on. Then they monitor for drift over time.The Elevate Product: AI that listens to provider-patient conversations and gives clinicians direct, specific feedback on where their empathy broke down and what they could have done differently. The goal is not to replace human care. It is to make every clinician perform closer to their best.Founder Experiment: Build a Behavioral Signal Intake BotUsing a voice or text-based AI agent (Claude, GPT-4o, or a similar LLM with tool access), build a simple structured intake flow for your product that collects behavioral signal, not just preference data.Start with three seed questions designed to elicit emotional state rather than factual answers. Log the responses. After 10 interactions, review the transcripts and flag any response patterns that correlate with disengagement, churn risk, or user distress. Run that as a lightweight customer health model before you ever touch a clinical dataset.If your product drives human decision-making in any way, behavior is your biggest data layer. This experiment will show you how much you are currently leaving on the table.⁠https://viderahealth.com/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠⁠⁠https://aiforfounders.co⁠⁠⁠⁠⁠⁠⁠https://kitcaster.com/application⁠ ⁠⁠⁠⁠⁠⁠⁠https://ryanestes.info⁠⁠⁠⁠

Say Hello to Your AI Data Analyst: How Bruin Is Replacing Headcount, Not Just DashboardsThere is a question Burak Karakan wants every founder to ask themselves right now: Do you know where your agents are?Burak is the co-founder of Bruin, an AI data analyst that connects directly to your data warehouse and answers any question in under 90 seconds, right inside Slack, Microsoft Teams, or a clean web UI. No dashboards to wrangle. No tickets to the data team. No waiting two days for a report that is already out of date by the time it lands in your inbox.Calling in from Istanbul, one of the world's oldest crossroads of culture and commerce, Burak brings the kind of perspective that only comes from years of building data infrastructure inside big enterprises and scrappy startups alike. That experience is the foundation Bruin was built on.The Framework: Data as the Operating System of Agentic AIBurak lays out what he calls the Virtual Data Team model. As companies begin spinning up multiple AI agents across marketing, sales, operations, and support, those agents will need to collaborate, just like humans do. The missing piece is not more agents. It is a centralized, governed, trustworthy data layer that all of them can query reliably.Bruin fills that role. Think of it as the data team member that every agent in your org chart can ping before making a decision.Key principles of the framework:Data still lives in your warehouse (Snowflake, BigQuery, etc.). Bruin does not move or copy it.Every action the agent takes is traceable. You can click through and see exactly how it arrived at any answer.Granular access control means marketing agents only see marketing data, while executive channels get broader access.Multiple deployment models are available: fully managed cloud, hybrid, or fully on-premise with your own LLMs.An MCP server exposes Bruin's full capabilities so other agents can query it programmatically.The Experiment: From Reactive to Proactive IntelligenceBurak draws a sharp distinction between a reporting tool and a reasoning system. Bruin starts as the former and is actively evolving into the latter. Current customers are already using it to route incoming support tickets through the AI analyst before the support agent even sees them, pulling customer purchase history, validating claims, and generating accurate responses. What used to take two to three hours per ticket now takes about 40 seconds.The next frontier Burak is building toward: agents that proactively surface problems you have not thought to ask about yet. Upcoming capacity shortfalls. Campaign spend misaligned with available sales bandwidth. Churn patterns hiding in plain sight. The data already knows. Bruin is learning to tell you before you ask.The Wild West Warning: A Framework for Agent GovernanceBurak introduces what might be called the Do You Know Where Your Agents Are test. As organizations deploy more and more autonomous agents, the risks compound fast if data access is uncontrolled.His governance framework:Run data quality checks at onboarding before the agent ever touches live data.Assign read-only permissions scoped to exactly what each agent needs.Use agent-controlled outputs (one agent checks another agent's answers before they surface to users).Set hard spending limits per query so no agent can run a runaway Snowflake job.Control internet access permissions per agent, per channel, per use case.The punchline: if your agent only has read access to two marketing tables, the blast radius of any mistake is tiny. Structure the permissions right and you can let the agents run free.https://getbruin.comhttps://www.linkedin.com/in/burakkarakan/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠⁠⁠https://ryanestes.info⁠⁠⁠

Procurement Is Not Boring. It's Just Broken.There is a word that kills deals before they start. A word that makes investors yawn, makes journalists skip the story, and makes founders steer away from the category entirely. That word is procurement.Alex Yakubovich has spent his entire career proving that instinct wrong. As co-founder and CEO of Levelpath, and previously co-founder and CEO of Scout RFP (acquired by Workday for $540 million in 2019), Alex has made procurement his life's work. Not because it is glamorous. Because it is genuinely broken. And because broken things, when fixed well, are worth a fortune.This episode covers what it actually means to build an AI native company from the inside out, why delightful procurement is a real mission and not a marketing tagline, and what founders building in any category can learn from a man who took the most overlooked function in business and turned it into a $100M+ venture-backed platform.The Anchor Framework: What Doesn't ChangeAlex opened by addressing the thing that keeps most founders anxious right now: the pace of change. His answer was not to slow down or resist it. It was to find the anchors that hold steady underneath all the noise.At Levelpath, those anchors are their four values:Obsess over the customer (the north star above all others)A players only (owners, not passengers)Elevate our employees (growth that sometimes comes with pain, and is always worth it)Earn the trust of others (not just "have integrity," but actively earn it, every single day)The insight here is structural. When everything else is accelerating, values are not motivational posters. They are operating instructions. They tell every person in the company what to optimize for when no one is watching.The Experiment Framework: Run More, Not FewerCounterintuitively, Alex argued that the right response to AI-driven chaos is not more focus. It is more experimentation. The cost of experiments has collapsed. What used to take two weeks of spreadsheet warfare now takes seconds. That changes the calculus entirely.But the filter for which experiments to keep? That never changes. His rule: name the customer this experiment will serve better. If you cannot answer that question with a specific person in mind, kill it. If you can answer it clearly, run it.The Delight Framework: Predictable, Not SurprisingAlex built his case for "delightful procurement" not on feature lists or dashboards, but on a feeling. The highest compliment Levelpath receives from customers is: "This is the product I would have built if I were a product person." That is not a UX win. That is empathy at scale.His practical examples of delight in enterprise software:Label your icons. Or remove them entirely. Cognitive load kills trust.Pre-configure the AI assistant to deliver an insight the moment someone lands on a page, before they ask. (A negotiation strategy based on your company's playbook, generated automatically when you open a contract, is a delight.)The Pavlovian ping. DocuSign's signature sound. Quicken's completion tone. Small audible moments that signal: you did something right.The through line is predictability. Delight is not surprise for its own sake. It is when the product does exactly what you needed before you knew to ask for it.https://www.levelpath.comhttps://www.linkedin.com/in/alex-yakubovich/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠⁠⁠https://ryanestes.info⁠⁠⁠

Mitchell Jones did not set out to build a payments company. He set out to solve a problem he could not stop running into: brilliant people paralyzed by plumbing. The API keys, the secret credentials, the subscription walls, the context switches. Every one of those friction points is a tax on thinking, and Mitchell decided the tax was too high.Lava is his answer. At its core, it is an AI gateway that sits between end users and the services they need, handling authentication, payment, and routing so the human never has to. Install the Lava MCP, load your wallet, and your Claude Code or Codex instance can immediately reach financial data, LLM models, go-to-market enrichment tools, blockchain queries, and dozens of other paid APIs without a single secret key or signup flow.The Two-Sided Marketplace FrameworkLava operates on a marketplace model with two distinct customer types, each with a distinct problem Lava solves:End users: founders, operators, and builders who want to access paid services without managing credentials or subscriptions. Lava handles the plumbing and acts as their universal AI service wallet.Merchants and service providers: companies sitting on valuable APIs and data who have no native way to meter, monetize, or convert the agent traffic already hitting their endpoints. Lava becomes their monetization layer, tracking usage, enforcing paywalls, and remitting payments, without requiring any new infrastructure.The Manager-of-Instances FrameworkMitchell introduced a framework that reframes the exhaustion founders feel after long AI work sessions. The shift from individual contributor to manager is not metaphorical. When you run multiple Claude Code instances simultaneously, you are no longer doing the work. You are directing it, context switching constantly, evaluating outputs, making judgment calls. The mental load is managerial, and it compounds quickly. Recognizing that shift is the first step toward managing your energy alongside your instances.The Systems Over Goals FrameworkMitchell's team at Lava does not set goals for how they adopt new AI tools. They set systems. Teammates experiment freely, share their wins and learnings weekly, and those learnings get baked into default files, memory blocks, and shared context that the entire org benefits from automatically. The system compounds. The goal-setting would not.Founder AI ExperimentUsing Cursor or Claude Code with the Lava MCP installed, build a one-prompt podcast production workflow. Start by listing every tool in your current production stack that has an API. Then prompt Claude to check which of those tools are already accessible through the Lava gateway. For any that are available, write a single system prompt that takes a recording timestamp as input and chains all the downstream production tasks: transcription, show notes generation, title creation, and asset formatting. Time how long the workflow runs versus your current manual process. This gives you a real cost-per-episode number and a live demonstration of the "one-shot your whole tech stack" concept Mitchell describes.https://www.lava.so/https://www.linkedin.com/in/mitchell-jones-333559a2/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠⁠⁠https://ryanestes.info⁠⁠⁠

The theme of Q1 2026 is "I feel behind." Every founder, from the scrappy solo operator to the venture-backed exec, is feeling the same anxiety. Site traffic is dropping. AI chatbots are answering questions that used to send customers to your website. And the brands that wait to figure this out are not just losing clicks. They are losing the narrative.Justin Inman spent nearly a decade at Google selling enterprise ad tech to the world's largest marketers, companies like Coca-Cola, L'Oreal, and Unilever. He watched those companies resist the digital shift, then scramble to catch up. When he left Google and started watching his own AI usage explode, and then noticed his mom casually quoting ChatGPT, he knew something bigger was coming. He got demos of the biggest players in the AI visibility space. One demo was so underwhelming, so narrow in its thinking, that he started his own company the very next day. That company is Emberos, and it is building what Justin calls the operating system for AI brand visibility.The core insight Justin brings to this conversation is deceptively simple: your brand exists inside AI systems right now, and you have zero control over what those systems are saying about you. Every LLM, from ChatGPT to Gemini to Perplexity to Grok, has formed its own opinion about your pricing, your product, your genre, your identity. And those opinions are often wrong. Emberos measured 500 brands and found that 90% have factual errors across at least one major language model. One small studio picked up a festival film that every AI in the world had mislabeled as a violent thriller with a John Wick comp. Nobody dies in that movie. It took four weeks of strategic fix packs to correct the narrative.The Framework: Paid, Owned, and Earned Across the AI LayerJustin's central argument is that most players in the AI visibility space are thinking too small. Their answer to the problem is to publish more AI-generated content, flood syndicated publishers, and hope the LLMs pick it up. Justin calls this "push to publish," and he says it is not only ineffective, it is dangerous. LLMs will get smarter. The brands that played these hacks six months ago are already getting delisted.Emberos takes a fundamentally different approach, mapping AI visibility across the full digital footprint:Paid: Connected TV ads, programmatic spend, and paid placements all feed signals into AI systems. Emberos is running live studies with major streamers to measure the correlation between TV exposure and generative AI search behavior.Owned: Your website, FAQs, schema markup, and YouTube captions all contribute to how LLMs read and cite your brand. If your site is not structured for LLM readability, it is invisible to the systems now acting as the front door of the internet.Earned: Podcasts, PR placements, influencer content, and press all create citations inside AI systems. Remarkably, Emberos now recommends podcast appearances as a strategic fix pack for brand visibility, because podcast transcripts are among the cleanest, most credible training data available to LLMs.https://emberos.ai/https://www.linkedin.com/in/jinman11/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠⁠⁠https://ryanestes.info⁠⁠⁠

The dream of AI that actually knows your business has been haunted by two enemies since day one: hallucinations and speed. Everyone building on top of large language models has accepted these as the cost of doing business. Ankit Dheendsa, CTO of Morphos.ai, decided not to.Ankit came on to build something that most of the industry had already written off as impossible: a vectorization engine that doesn't just compress data, it fundamentally rethinks how a vector is constructed. The result is Green Vectors, Morphos's patent-pending core technology that reduces vector database size by up to 99.5%, speeds up queries by 4x, and pushes search accuracy to the 99th percentile. That's not an incremental gain. That's a category redefinition.What makes this sticky for founders is the affordability story. Enterprise RAG used to cost $50,000 and up, delivered mediocre accuracy, and still left your team second-guessing every output. Morphos.ai now delivers that same infrastructure layer for $20 a month, the same price as ChatGPT Pro, with dramatically better performance across the board.https://www.morphos.aihttps://www.linkedin.com/in/ankit-dheendsa/⁠⁠https://www.linkedin.com/in/estesryan/⁠⁠⁠⁠https://aiforfounders.co⁠⁠⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠⁠⁠https://ryanestes.info⁠⁠⁠

Most founders spend their careers chasing customers who are already convinced. Nick Lopez spent his learning to find customers who don't even know they need you yet, in a market worth hundreds of billions of dollars that most of the startup world has never touched.Nick is the co-founder and CEO of Prosal, a capture intelligence platform built for federal defense contractors. But before you write that off as too niche or too complicated, stick with the story, because the principles buried inside this conversation are universal.Nick started at Lockheed Martin as an engineer out of Georgia Tech, working on programs he still can't fully talk about. What he could see, though, was a massive structural gap. The people building the technology and the people selling it were operating in completely separate worlds. Business development teams with decades of domain knowledge were spending their most valuable hours doing slow, manual research instead of talking to the customers who could change their entire trajectory.That insight became the seed of Prosal. But the path there wasn't straight.https://prosal.comhttps://www.linkedin.com/in/thenicklopez/⁠https://www.linkedin.com/in/estesryan/⁠⁠https://aiforfounders.co⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠https://ryanestes.info⁠⁠

⭐⭐⭐⭐⭐There is a moment every founder hits. You have spun up agents, handed them access to your systems, pointed them at your data, and watched them go. It feels like progress. It feels like leverage. And then someone asks you a simple question: do you know what your agents are doing right now?The honest answer, for most teams, is no.Jasson Casey has spent years thinking about the gap between the speed at which companies adopt AI and the speed at which they reckon with what that adoption actually costs. He is the CEO of Beyond Identity, a company that has protected over 10 million identities, and his newest product, Ceros, was built for exactly this moment: the moment founders realize they have handed the keys to a car that can drive itself anywhere, including off a cliff.This conversation is a field guide for founders who are moving fast and want to stay alive.The AI Transformation SpectrumJasson opens with a framework that every founder needs to internalize before they ship another agent.Most companies think they are doing AI transformation. Most of them are not.AI Enabled: You turned on the AI features that already existed in your software stack. Superficial. Table stakes. Not a strategy.AI Native: You questioned every assumption about how your business is organized. You asked which processes exist only because a human had to do them. Then you rebuilt around the answer.The gap between those two positions is where most companies are quietly stuck. The board is asking for AI transformation. The team is checking boxes. And nobody is asking the harder question underneath it all: what had to be true about how we work for humans to do this, and does any of that still apply?https://beyondidentity.aihttps://www.linkedin.com/in/jassoncasey/https://x.com/jassoncasey⁠https://www.linkedin.com/in/estesryan/⁠⁠https://aiforfounders.co⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠https://ryanestes.info⁠⁠

There is a moment in every founder's journey where they realize the bottleneck in their pipeline is not their product, not their pricing, and not their pitch. It is time. Specifically, the time between when a prospect raises their hand and when someone, or something, responds.Will Del Principe discovered this the hard way. At 16, he was a solar sales rep dialing through a list of thousands of warm leads on an iPad, burning out after five or six calls, leaving a fortune in uncontacted interest sitting in a CRM. A decade later, he is the head of growth at Thoughtly, an AI voice agent platform that calls those same kinds of leads within 10 seconds of form submission, runs 13,000 calls a month for a single client, and once had to be reprogrammed after one of its agents agreed to go get coffee with a prospect.This episode is about what happens when you stop asking humans to do what machines can do endlessly, and start letting your best salesperson work around the clock without ever needing a break.https://www.thoughtly.com/https://www.linkedin.com/in/will-del-principe-57b18b2a5/⁠https://www.linkedin.com/in/estesryan/⁠⁠https://aiforfounders.co⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠https://ryanestes.info⁠⁠

Guest: David Karandish, CEO and Co-Founder of Capacity.comIn December 2016, the top-selling product on Amazon was not a toy, a book, or a video game. It was Amazon's Alexa. For most people, that was a holiday novelty. For David Karandish, it was a starting gun.David had just finished one of the most successful runs in the history of vertical search. He built Announced Media, acquired answers.com, merged the two companies, scaled them into a powerhouse, and sold the whole thing for $900 million. He took five months off. He made his laundry list of what to do next, somewhere around 50 ideas. Forty were terrible. A handful were decent. One made him feel like he would regret skipping it for the rest of his life.That one became Capacity.He founded it in early 2017, before the world understood what AI was about to become. Blockchain was the darling. AR and VR were getting the hype cycles. AI was maybe fourth on the list of things people were excited about. David bet on fourth place, and he was right.But here is where the real story starts. Because building Capacity was not a straight line. In the early days, the product worked better for some customers than others, and the market was sending a confusing signal. Small companies had the problem but not the budget. Enterprise companies had the budget but needed security certifications, compliance frameworks, and infrastructure that a scrappy startup did not yet have. David built those things. SOC 2. HIPAA compliance. Role-based access controls. And while he was building the enterprise credibility, something else was happening: his customers kept asking for more.Not more features inside one product. More products that actually talked to each other.Over and over, David kept hearing the same thing. "We are so tired of duct-taping solutions together. We don't want five vendors. We want one platform that works." He heard it a dozen times before he finally went to his executive team and said, "I think I know what we need to build." They looked at him like he had three heads.He built it anyway.Today, Capacity serves 20,000 customers, including T-Mobile, Verizon, Nike, and American Express. Annual revenue has surged past $50 million. And the strategy behind all of it is something David calls the Compound Startup.https://capacity.com/https://www.linkedin.com/in/davidkarandish/https://www.linkedin.com/in/estesryan/⁠⁠https://aiforfounders.co⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠https://ryanestes.info⁠⁠

There is a moment in every founder's journey where they realize the map they were given was wrong. The old map said: have an idea, find a developer, wait months, launch, iterate. David Alonso, co-founder of Bloom and ETH Zurich robotics graduate turned mobile app revolutionary, is handing founders a new map. One where the distance between idea and working product is measured in minutes, not months.David didn't plan to build Bloom. He planned to build robots. But somewhere between reinforcement learning research and quadrupeds, he fell in love with the tight feedback loop of app development, met a world-class design engineer in his co-founder, and the two of them started following an obsession that eventually led them through Y Combinator, a $3.5 million raise closed before Demo Day, and a product that left investors texting their friends mid-demo saying it was the best tech demo they had ever seen.This episode is the story of what happens when you decide the bottleneck is not code. It is imagination.The Core Problem Bloom Is SolvingBuilding a mobile app used to take David and his co-founder four months from idea to having it on someone else's phone. Four months. And that was with two technical co-founders who knew exactly what they were doing. For a non-technical founder, the timeline was effectively infinite. Bloom collapses that timeline to minutes by combining three opinionated technology choices into a single agentic coding experience:Expo as the front-end framework, enabling one codebase to deploy to web, iOS, and Android simultaneouslyConvex as the backend, providing real-time sync between devices out of the box, full type safety, and a database that just works without configurationApp Clips as the distribution layer, an underutilized Apple feature that lets anyone open a fully native app from a single link without visiting the App Store, downloading TestFlight, or entering an invite codehttps://bloom.diy/https://www.linkedin.com/in/david-oort-alonso/⁠https://www.linkedin.com/in/estesryan/⁠⁠https://aiforfounders.co⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠https://ryanestes.info⁠⁠

Jesse Marble did not set out to build a typical VC firm. Growing up steeped in Colorado culture, watching people chase outdoor adventure, physical health, and something resembling a meaningful life, he kept noticing a gap. We have more technology in our pockets than it took to land Americans on the moon. And yet, by almost every subjective measure, people are not thriving more. They are thriving less.That tension became Wildwood Ventures, a Denver-based early-stage VC firm with a deceptively simple thesis: invest in human flourishing through technology. Not hiking apps. Not yoga trackers. The whole sprawling category of what it actually means to be healthy, connected, and alive in the modern world.What Jesse brought to this episode was not a polished fund deck or a rehearsed pitch. It was something rarer: a practitioner's honest account of what he sees every week sitting across from founders, scoring pitches in real time, and asking himself whether he would put his own money on the line.The answer, he admits, is increasingly complicated.https://wildwood.vc/https://www.linkedin.com/in/jessemarble/⁠https://www.linkedin.com/in/estesryan/⁠⁠https://aiforfounders.co⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠https://ryanestes.info⁠⁠

There's a moment in every founder's journey where the market stops being theoretical and becomes deeply personal. For Lucas Consoli, co-founder of EmpathEQ, that moment happened in a hospital room, watching his mother in an induced coma for two weeks, his emotional state entirely at the mercy of whichever nurse happened to be on shift. Some had zero empathy. Some brought calm into chaos. That gap, that wildly inconsistent human experience inside one of the most high-stakes environments on earth, became the foundation for everything EmpathEQ is building.Lucas grew up in Argentina, a country he describes as one that forges entrepreneurs not through comfort but through necessity. When institutions can't be trusted, you build your own moral compass. You develop a muscle for solving problems that most people would walk away from. He took that muscle to Berlin, co-founded two companies without speaking German, met his American wife, and eventually landed in Cincinnati with a green card, a vision, and a co-founder, Alex, who had five exits to his name and the capital to fund the first six months of the dream.The problem EmpathEQ is solving is enormous. Nursing burnout is at crisis levels. A significant portion of the workforce is leaving the profession. And the root cause isn't clinical incompetence. It's emotional overload from interactions that nobody ever trained them to handle. Angry family members. Anxious patients. Charged situations that escalate in seconds. The traditional solution has been to hire an actor, schedule 200 students, give each of them three minutes of practice once a year, and hope it sticks. EmpathEQ blew that model up entirely.Their platform puts nurses inside AI-powered simulations where a digital patient or family member reacts in real time to the nurse's verbal language, tone, facial expressions, and body posture. The AI orchestrator reads all of those signals and selects the next scene from a library of pre-rendered cinematic moments, choosing the response the patient would realistically give based on how the nurse is showing up. Afterwards, the nurse gets a full feedback report. Where they looked. How they sounded. Whether they validated emotions or bulldozed through them. It's a driving range for human connection.The tech stack is a hybrid of AI and cinematography because fully generative real-time video isn't there yet. Rather than wait for the technology to catch up, Lucas and his team engineered around the constraint, and the result is something hospitals and nursing schools are lining up to use. Sixteen institutions are already collaborating. None have said no. The next step is getting them to pay, and the pre-seed round of $600K is still open for one strategic partner, ideally from health systems, nursing staffing agencies, or higher education.The conversation also went deep on the philosophy of building, the danger of chasing exits without passion, the cognitive overload epidemic in the founder community, and why studying sociology or psychology might be the single smartest move a college freshman could make in the age of AI.Lucas isn't just building a company. He's building a case that empathy is a trainable skill, that soft skills deserve hard infrastructure, and that the healthcare system's most urgent problem isn't a drug or a device. It's the conversation in the hallway.https://empatheq.ai/https://www.linkedin.com/in/lucas-donato-consoli/⁠https://www.linkedin.com/in/estesryan/⁠⁠https://aiforfounders.co⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠https://ryanestes.info⁠⁠

When the Market Is a WhatsApp Group, That's Your OpportunitySome of the best startup ideas don't come from pitch decks. They come from watching thousands of people make high-stakes decisions inside a Facebook group, realizing there is no trusted infrastructure, and deciding to build it yourself.That's exactly what Francesco Hayes did. As co-founder and CTO of Luxxera, he spotted one of the messiest, most fragmented, and most consequential markets on earth: medical tourism. Specifically, the booming industry of people flying abroad to get cosmetic procedures done at a fraction of US prices. Hair transplants that cost $50,000 stateside can be had in Turkey or Greece for $2,500 to $5,000. IVF that runs $70,000 in the US costs roughly $5,000 at a top Greek hospital. The demand is massive. The information infrastructure is basically nonexistent.Francesco and his co-founder Nick didn't just see a gap. They walked into it, sometimes literally posing as patients to vet clinics before revealing who they were. What they built is part marketplace, part knowledge base, part concierge service, and 100% founder-brained.The Dual-Sided Marketplace FrameworkRunning a two-sided marketplace means you are always solving two problems at once. Francesco broke down how Luxxera manages the tension between supply and demand.On the clinic side:Free onboarding, no upfront cost to the clinicLuxxera provides booking systems, payment processing, and CRM infrastructureMost clinics currently run operations entirely through WhatsApp, so even basic tooling is a massive upgradeClinic quality is validated through peer-review surgical organizations like ISHRS and FUE Europe, plus in-person site visits by the Luxxera teamOn the patient side:A structured intake assessment narrows recommendations to two of five vetted clinicsTransparent, itemized pricing with a 10 to 15% fee added on top of the clinic's quoteFull concierge support throughout the entire patient journeySurge pricing planned for seasonal demand shifts, like winter being the peak season for hair transplantshttps://luxxera.comhttps://www.linkedin.com/in/francescohayes/⁠https://www.linkedin.com/in/estesryan/⁠⁠https://aiforfounders.co⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠https://ryanestes.info⁠⁠

There is a certain kind of founder who, after building and exiting a company, does not slow down. They just get quieter about it. Colin McIntosh is that founder. He sold Sheets and Giggles, the irreverently named sustainable bedding brand he bootstrapped into a multi-million dollar e-commerce operation, and then he did what most founders say they will do and almost never do: he kept building, but only the things he actually cared about.This conversation covers the real state of the 2026 job market, the counterintuitive content strategy that put SheetsResume.com at the top of Google without a single AI-generated word, and the framework Colin uses to decide which ideas are worth his time. Along the way, it takes a detour through Babylonian flood myths, float tanks, and a giraffe-shaped carafe business that may or may not be a real thing.WHY THE JOBS REPORT ISN'T TELLING THE WHOLE STORYColin breaks down the 2025 labor market with the clarity of someone who has seen thousands of resumes and placed hundreds of executives. The headline numbers look stable, but the underlying picture is messier.The US lost jobs in 2025 outside of healthcare, with healthcare accounting for roughly 90% of all new job creationMonthly job creation averaged a fraction of 2024's pace, with 2024 sitting around 149,000 jobs added per monthAI is manifesting primarily as a payroll freeze, not mass layoffs, as companies wait to understand what they can automate before committing to new headcountGeopolitical instability, on-again-off-again tariffs affecting retail and its roughly $7 to $8 trillion slice of the US economy, a 40% drop in international tourism, and 300,000 government workers flooding the private job market are all compounding the pressureThe people suffering most are those laid off in 2025 who cannot find work after six, twelve, or eighteen months of searchinghttps://sheetsresume.com/https://readynda.com/https://www.rivierapartners.com/ https://www.linkedin.com/in/colindmcintosh/⁠https://www.linkedin.com/in/estesryan/⁠⁠https://aiforfounders.co⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠https://ryanestes.info⁠⁠

There's a place in Denver, inside a buzzing AI builder clubhouse, where the future gets stress-tested out loud every Wednesday night. That's where this conversation happened, and it did not go the direction you'd expect.Carson Vest is an investment associate at Denver Ventures, a generalist fund covering pre-seed all the way to Series B. She sees everything. Hundreds of founders, hundreds of pitches, hundreds of ideas competing for the same finite pool of attention and capital. And yet the most radical thing she said had nothing to do with a hot deal. It was this: you might not need us.That single idea runs like a thread through this entire conversation, pulling at the assumptions most founders carry into every investor meeting without even realizing it.The Frameworks You Need to StealThe Founder DNA Thesis: Why the person always comes before the productDenver Ventures bets on founders first, especially at pre-seed and seedPrior company experience, big tech background, or deep channel relationships signal real distribution potentialIf you can't sell the vision to an investor in a casual conversation, how will you sell it to a team, a customer, or a market?The Distribution Co-Founder Gap: The missing piece on most cap tablesMost founders plan to hire for distribution after raising, but bringing that person in as a co-founder from day one dramatically increases investabilityThe strongest founding teams Carson sees came up together, school friends, former colleagues, people who already trust each other under pressureDistribution is not a marketing problem. It is a survival problem.The Moat Has Moved: Why code is no longer defensibleAn MVP that cost $320,000 and 18 months in 2022 now costs $20 and a weekIf your only edge is the technology, someone with a Claude account can clone you by FridayThe new moats: proprietary data, founder network, channel relationships, and obsessive domain expertiseThe VC Gut Check: The question every founder should answer honestlyCarson asks founders point blank: why do you actually want VC money?Many founders admit they just assumed it was the next stepBootstrapping to $500k or even $1M ARR may give you more leverage, more equity, and more freedom than a seed round ever couldThe Retention Signal VCs Actually WatchHigh AI margins look great on paper, but paradoxically can signal low usageInvestors want to see high inference costs because that means users are actually on your platformRetention is the metric that separates a product people want from a product people try once and forgetThe Agentic Shift: Where the smart money is moving post-ChatGPTThe infrastructure layer, models, GPUs, wrappers, is maturingThe next wave is workflow automation and vertical AI that disappears into the backgroundThe winner is not the best chatbot. It is the tool that makes the task vanish entirely.https://denverventures.co/https://www.linkedin.com/in/carson-janae-vest/⁠https://www.linkedin.com/in/estesryan/⁠⁠https://aiforfounders.co⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠https://ryanestes.info⁠⁠

Josh Gilmer on AI video journaling, founder self-awareness, searchable memory, and the future of personal growthMost founders say they want self-awareness.What they usually mean is they want a cleaner notes app.In this episode of AI for Founders, Ryan Estes sits down with Josh Gilmer, founder of Historic, to explore a wild and increasingly relevant idea: what if the most valuable founder data is not in your CRM, your calendar, or your analytics dashboard, but in the raw, unfiltered way you talk when nobody is grading the performance?Josh argues that handwritten journaling and polished note-taking often miss the point. By the time a thought hits the page, it has already been edited, softened, and made presentable. Historic takes the opposite path. It uses video journaling plus AI to capture tone, posture, energy, hesitation, and emotional context, then turns that into searchable, structured memory.The conversation starts with founder productivity and quickly opens into something bigger: burnout detection, AI coaching, parenting, second brains, the future of memory, and whether technology will help humans reconnect or just become even more insulated.This one is for founders building hard, thinking fast, and wondering whether the biggest blind spot in the company might be the person running it.What you’ll learnWhy written journaling often captures polished thoughts instead of real thoughtsHow video journaling can reveal emotional and cognitive patterns text missesWhy searchable personal memory may become a founder advantageHow AI could eventually detect burnout, mood shifts, and recurring decision patternsWhy productivity might shift from doing more to remembering betterHow Historic is being built and positioned for founder adoptionWhy Josh believes AI should strengthen human relationships, not replace themhttps://historic.app/https://www.linkedin.com/in/joshuagilmer/⁠https://www.linkedin.com/in/estesryan/⁠⁠https://aiforfounders.co⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠https://ryanestes.info⁠⁠

This conversation starts with a blunt idea: most AI companies are moving fast enough to impress people, but not carefully enough to survive themselves. What looks like momentum from the outside can be chaos on the inside, and James Everingham makes the case that the next real layer of AI infrastructure will not be another flashy model. It will be the systems that govern, audit, orchestrate, and preserve what those models and agents actually do.From there, the story widens. James pulls from years inside Meta, where he worked on developer infrastructure and saw firsthand what happens when agentic systems start touching real enterprise environments. The lesson was not that agents are weak. It was that they are powerful enough to require governance, access controls, traceability, and compliance like any serious employee or internal system.The conversation then moves into a bigger historical frame. Browsers, spreadsheets, infrastructure shifts, platform wars, and the collapse in the cost of intelligence all become part of the lens. James argues that we are not just watching better tools arrive. We are watching corporate infrastructure reorganize around agents, much like the internet reorganized business around the browser. The winners may not be the companies with the loudest demos, but the ones that can make their systems stable, reusable, secure, and multiplayer.It also gets personal. James talks about building again after a successful career, the difference between burnout and lack of inspiration, why network matters more than people admit, and why founders should not start companies just to start companies. They should wait for the idea they cannot ignore.https://guild.aihttps://www.linkedin.com/in/jevering/⁠https://www.linkedin.com/in/estesryan/⁠⁠https://aiforfounders.co⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠https://ryanestes.info⁠⁠

Ryan opens with a founder gut check. Scale sounds sexy, but control is the real addiction. Then Marcin walks in with a real world mirror, because warehouses do not care about your pitch deck, and robots do not care about your assumptions.Sevensense builds the “eyes and brains” for mobile robots, not the whole robot. The story starts in the ETH Zurich ecosystem where robotics talent is dense, labor is expensive, and the only way to win is to build high-value systems that actually work outside the lab. Marcin explains how early industrial robots were basically obedient roombas with a job title, rigid paths, brittle behavior, and zero ability to handle a changing environment.Then the thesis lands. Vision-based navigation uses natural features, so you do not need QR codes on the floor, magnetic tape, or a warehouse redesigned around your machine. Instead, you give a robot something closer to human perception, cameras, inertial sensing, wheel and leg signals, and enough compute to reason about space. The result is not just navigation. It is adaptability.The conversation expands into the social layer. Robots need to communicate intent so humans trust them. Lights, sounds, turn signals, speed indicators. And robots need to understand humans as humans, not as just another obstacle. Predict motion. Yield. Negotiate the sidewalk dance. The future of robotics is not only engineering. It is manners.Marcin’s founder journey is a deep tech reality check. Early money gets wasted on cool R&D nobody needs. The breakthrough comes from a gritty commercial project, autonomous cleaning machines that forced them to ship systems that worked for non-roboticists, with real customers and real consequences. That pain becomes the advantage. Robustness becomes the moat.https://sevensense.aihttps://www.dymczyk.com/https://www.linkedin.com/in/dymczyk/⁠https://www.linkedin.com/in/estesryan/⁠⁠https://aiforfounders.co⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠https://ryanestes.info⁠⁠

Here’s the uncomfortable truth: social media isn’t preserving your memories. It’s strip-mining their meaning.We built trillion-dollar machines so strangers can watch us live… while the people who were actually there are already scrolling past it.Founders obsess over growth, distribution, scale. Reach. Impressions. Virality.But what if the most valuable product isn’t reach?It’s recall.You host a retreat for your top 50 customers. Magic happens. Voice notes at midnight. Inside jokes. Breakthrough conversations.Two weeks later? Buried in camera rolls. Lost in Slack threads. Emotion turned into data exhaust.What if there was a product that automatically stitched those fragments into a shared living story?Not for the algorithm. For the tribe.Because here’s the conflict: attention is rented. Memory is owned.In a world optimized for attention… are you building something that deepens connection — or just consumes it?That’s the deep question.Welcome to AI for Founders, I’m Ryan Estes. And today you’ll learn how Oleg is rethinking memory itself — building technology that turns scattered moments into structured meaning. This is for founders who care about product psychology, community retention, and designing experiences people actually remember.If you’re building in AI, you need signal, not noise.Go to aiforfounders.co.That’s aiforfounders.co — where ambitious builders sharpen their edge.If this episode sparked something, leave a review like you’re time-stamping a moment that mattered.And if you’re a founder with a story worth remembering, go to Kitcaster.com. Kitcaster is the premier podcast booking agency for high-growth companies. They don’t just book interviews. They position you as the authority in your space and turn conversations into customers. Kitcaster.com. Be heard.https://www.linkedin.com/in/oleggolynker/https://www.trueli.me/https://www.amazon.com/Confessions-Unicorn-Founder-Obsession-Chasing/⁠https://www.linkedin.com/in/estesryan/⁠⁠https://aiforfounders.co⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠https://ryanestes.info⁠⁠

Most founders are accidentally running a casino.Not a company.They’re bragging about ROAS, celebrating revenue spikes, and somehow… still bleeding cash.Because if you don’t know how much you should be spending, “ads” isn’t a strategy.It’s gambling with better graphics.Here’s the real conflict.AI is about to flood the world with “growth tools” that promise the moon, but they still can’t ask the right questions.AI can do the math.It just can’t build the equation.So here’s the deep question.If your business is growing, but you can’t explain why you’re not making money, are you building a company… or a very expensive coping mechanism?Welcome to AI for Founders, I’m Ryan Estes.This is for founders building with AI, especially if you sell real products, run paid media, or you’re staring at a P&L like it’s written in ancient Sumerian.You’re going to learn how to stop guessing, set a profit foundation first, and then scale like you actually mean it.And now, meet Adam.He took an e-comm brand from zero to $60 million in sales, then built Pentane, software that basically “encapsulates his brain” and tells operators what to do to get profitable.Even wilder, he plugged in an agent so you can literally ask, “How do I hit 5% net profit this month?” and get a direct answer in seconds.Founders, if you want your business to run like a system, not a mood, go subscribe to the newsletter at aiforfounders.co.If your calendar is chaos, your margins are chaos, your brain deserves better, aiforfounders.co.Join 27,000 founders who want signal, not noise, aiforfounders.co.Quick favor, leave a review of the podcast like you’re rating a parachute after you actually jumped.And a word from Kitcaster.com, if you’re a founder who should be on podcasts but you keep “meaning to,” Kitcaster books you on shows your customers already trust.They handle the outreach, the follow-up, the scheduling, and the chaos.You just show up and sound like the person who built the thing.__https://www.linkedin.com/in/adammcallinan/https://www.linkedin.com/in/estesryan/https://pentane.comhttps://aiforfounders.cohttps://bigskybravery.org⁠https://kitcaster.com/application ⁠⁠https://ryanestes.info⁠

If stillness is the source of your best decisions, why is your calendar built like it is trying to kill it?Be honest.When was the last time your biggest breakthrough happened in a meeting?Not a brainstorm. Not a sprint. Not a Slack war.I’m talking about the idea that actually changed your trajectory. The hire you finally understood. The product pivot that suddenly made sense.It probably happened in the car.On a walk.On a random Thursday when you ditched work and went snowboarding.And yet your calendar looks like a competitive sport. Back-to-backs. Fifteen minute blocks. “Quick sync.” “Fast follow.” “Rapid alignment.”Alignment with what? Exhaustion?Here’s the uncomfortable truth.Most founders are not blocked by strategy. They’re blocked by noise. And now we’re adding AI to the noise.Welcome to AI for Founders, I’m Ryan Estes.Today you’re going to learn how a builder thinks after an exit, why exploration is not procrastination, and what “AI-native” actually means if you’re serious about product, health, and human behavior. This is for founders who want leverage without turning their life into tab toggling.My guest is Alyssa Eidam from Inkfish Studio.She built AI agents in healthcare, specifically to support clinicians and solve staffing bottlenecks, then exited after about a year and a half and did the thing most founders refuse to do. She stopped. Traveled solo. Got present. Let her attention tell her what to build next.And the big takeaway for your company is this.Do not use AI because it is powerful. Use it because it is intentional. If the system is broken, AI does not fix it, it makes it break faster.Also, “AI-native” is not a chatbot. Chat interfaces should die.AI-native is picking the exact moments in the workflow where prediction, pattern matching, and reasoning actually change what is possible. Surfacing what matters before the user even knows to ask.Founder use case.Instead of building another chat box, build a product that watches the process, detects the bottleneck, predicts the next step, and removes the need for five apps and thirty tabs. Less typing, more outcomes.Go subscribe to the newsletter at aiforfounders.co.It’s for founders building in the mess, not founders collecting prompts like trading cards.If you want ideas that ship and frameworks that punch back, you’ll like it.Leave a review of the podcast by writing one sentence that would make your smartest friend immediately hit play.https://www.inkfish.studio/https://www.linkedin.com/in/eidamam/https://www.linkedin.com/in/estesryan/https://aiforfounders.co/ ⁠https://kitcaster.com/application ⁠⁠https://ryanestes.info⁠

What if the most valuable asset in your company isn’t your tech stack, your team, or even your brandWhat if it’s the quiet archive sitting on your laptopIn this episode of AI for Founders, Ryan sits down with Dr. Jonathan Schaffer, a 40-year AI pioneer, professor, and now founder of a privacy-first AI platform called Kind. What unfolds is not just a product conversation. It is a philosophical reckoning with who AI is supposed to serve.From competitive chess in the 1970s to launching a company in 2026, Dr. Schaffer shares how decades of teaching, research, and observing AI hype cycles led him to one convictionThe moat is not the modelThe moat is your datahttps://synsira.comhttps://www.linkedin.com/in/estesryan/https://aiforfounders.co/ ⁠https://kitcaster.com/application ⁠⁠https://ryanestes.info⁠

Your startup idea is probably garbage.Not because you are dumb.Because you are in love.And love makes you build… a product nobody wants.Here’s the controversial take: If you cannot survive 10 uncomfortable customer conversations, you do not deserve to write a single line of code.Because validation is not “vibes.” It is evidence. It is bruises. It is getting told “no” until your ego stops bleeding on your roadmap.Deep question before we go any further:If your idea fails, does that mean you failed… or does it finally mean you are free to become who you said you wanted to be?Welcome to AI for Founders, I’m Ryan Estes.Today you’ll learn how one founder built a system to help you validate ideas faster, map your market, analyze real customer interviews, and even assemble a pitch deck that is not just a bedtime story for investors.This is for first-time founders, serial idea hoarders, and anyone who has ever wasted months building a “brilliant” product with zero buyers.The mind behind this is Ohad Shaked, the founder of ThinkUp Global.His whole thing is turning the founder rollercoaster into an actual map: problem, solution, personas, market sizing, competitors, interview analysis, go-to-market, and the deck.And here’s the spicy founder use case: run five ideas through the process at once, and let reality pick your next company, not your dopamine.If you want more stuff like this, go to aiforfounders.co and get the newsletter.It is basically a weekly shipment of “build less, validate more” for your brain.Also it is cheaper than learning these lessons the hard way.Again: aiforfounders.co.And if you like the podcast, leave a review like you are writing a Yelp review for my personality.Quick 15-second note from my other life: Kitcaster.com is the premier podcast booking agency for founders.If you want to get booked on shows your customers actually listen to, and turn interviews into pipeline instead of “nice conversations,” Kitcaster does it end-to-end.You show up and be interesting. They handle the rest. Kitcaster.com.Final question to sit with:What are you protecting more right now… your idea’s success, or your identity as “the person with the idea”?https://thinkup.globalhttps://www.linkedin.com/in/ohad-shaked111/https://www.linkedin.com/in/estesryan/https://aiforfounders.co/ ⁠https://kitcaster.com/application ⁠⁠https://ryanestes.info⁠

Most founders don’t have a software problem… they have a decision problem.We spend weeks “researching” tools, comparing top 10 lists, reading reviews written by people who’ve never run payroll, never closed a deal, never felt the pressure of making the wrong call. Meanwhile, your team is stuck. Momentum dies. And you call it due diligence.Here’s the tension: choosing a restaurant takes five minutes. Choosing the software that runs your company takes five weeks… and usually gets dumped on the least technical person in the room.Deep question: how many hours of your life have you burned trying to pick the “right” tool when what you really needed was the right guide?Welcome to AI for Founders. I’m Ryan Estes, and today, you’ll learn how founders and operators can shortcut the chaos of software selection with a human-centric approach, how to avoid analysis paralysis, and how to turn tech decisions into a competitive advantage. This is for builders who are tired of guessing.If you care about leverage, clarity, and smarter bets, go to aiforfounders.co.Join thousands of founders turning AI into actual ROI.Your unfair advantage is one newsletter away.If this helped you think differently, leave a review like you’re recommending your favorite hidden restaurant to a friend.And if you want your voice on the world’s top podcasts, go to Kitcaster.com, the premier podcast booking agency that gets founders in front of their ideal audience, builds authority, and turns conversations into customers.__https://www.linkedin.com/in/adnan-malik/https://www.linkedin.com/in/estesryan/https://aiforfounders.co/ ⁠https://kitcaster.com/application ⁠⁠https://ryanestes.info⁠

AI music companies are treating creativity like disposable garbage, and they’re about to hit a wall so hard it sparks the next artistic renaissance.Hot take: Generative AI didn’t democratize music, it cheapened it.Because when anything can make a trillion songs a second, the algorithm stops rewarding artists and starts rewarding… sludge.Here’s the tension.The stats say AI music is everywhere.But creators feel something emotionally wrong, deep in the bones.And when culture feels “wrong” like that, history usually flips the table.Creators do not want infinite options.They want constraints.Because constraints make human decisions matter again.Founders, here’s the use case you’re missing.Stop building “make content faster” tools.Build “make authorship undeniable” tools.Music is the language of emotions, so the product isn’t output, the product is the feeling of making it.Think Roblox and Fortnite. Not streaming.Not feeds that feel fake, but places that feel real.Not a billion views, a small room, shared time, witnessed creation.That’s culture. And culture moves before scale catches up.So here’s the deep question.If your product makes everything frictionless, are you freeing people… or quietly erasing the part of them that needs to struggle to feel alive?Welcome to AI for Founders, I’m Ryan Estes, and today you’re going to meet Siggi, the CEO of Overtune, to unpack why constraints fuel creativity, why witnessed creation beats generated content, and why the next music renaissance is happening in gaming, not streaming. This is for founders building creative tools who want to understand where culture is actually moving, before the numbers lie to you.Sign up for the newsletter at aiforfounders.co.We turn the chaos into signal you can actually use.No fluff, no “AI will change everything,” just the plays that make you dangerous.And if you enjoyed this, leave a review that’s not “great podcast.” Write one sentence that sounds like a startup pitch you’d actually fund.This episode is brought to you by Kitcaster.com, a premier podcast booking agency. If you’re tired of begging for attention on the internet, get booked on the shows your customers already trust. Kitcaster handles the outreach, the follow up, the scheduling, and the prep, so you just show up and deliver your story. Want to turn your expertise into pipeline, credibility, and audience growth? Visit Kitcaster.com. That’s Kitcaster by Moburst.__https://www.linkedin.com/in/sigurdur-arnason-2b690311a/https://www.overtune.comhttps://aiforfounders.co/ ⁠https://kitcaster.com/application ⁠⁠https://ryanestes.info⁠

"Stop hiring AI passengers, they're dead weight. If your team says 'this is what AI thinks,' fire them. Here's why..."Two billion people use AI every day, but they won't pay a dime for it. That means enterprise has to foot the entire bill, and right now, they're hemorrhaging cash on $30/month seats that nobody's actually using. The brutal truth? CEOs spend a year bragging about being "AI-first" while only 10% of employees touch the tools. The rest are paralyzed, terrified they're automating themselves into unemployment.But the smartest founders aren't just deploying AI. They're building companies where 32 people do the work of 45. The secret weapon? They demand AI drivers, not AI passengers. No cutting and pasting. No "AI said to do this." You own the decision. You own the conviction. Because when you hit turbulence, and you will, nobody's going to rally behind "well, the chatbot thought it was a good idea."Are you building a team of AI drivers who own their outcomes, or AI passengers coasting toward irrelevance?Welcome to AI for Founders, I'm Ryan Estes. You just learned the enterprise adoption playbook from Gregory Shove, 7-time founder, $250M in exits, and the guy solving the billion-dollar question: how do you get big companies to actually use AI?Get the full playbook at aiforfounders.co, weekly insights that'll have your competitors wondering how you're shipping 3x faster. Subscribe before your competition does.If this hit different, leave a review, podcasts run on ratings like startups run on caffeine.This episode is brought to you by Kitcaster.com, the premier podcast booking agency that gets founders like you on shows that actually move the needle. Stop cold pitching, start converting listeners into customers. Whether you're raising capital, launching products, or building your brand, Kitcaster puts your voice in front of audiences that matter. Visit Kitcaster.com and turn your story into your unfair advantage.⁠⁠https://www.linkedin.com/in/gregshove/⁠⁠⁠⁠https://www.gregshove.com/⁠⁠⁠⁠https://aiforfounders.co/ ⁠⁠⁠⁠⁠https://kitcaster.com/application ⁠⁠⁠⁠⁠⁠https://ryanestes.info⁠⁠⁠

The best AI companies won't use LLMs. Here's why most founders are building the wrong thing...Everyone's chasing ChatGPT wrappers while the real money is buried inside boring businesses making $100M a year. Cabinet factories. Paint mixers. Ball-bearing manufacturers. They're sitting on decades of proprietary data, proprietary SOPs, chemical formulas, machine configurations, and nobody's talking to them because software engineers and cattle ranchers don't hang out at the same bars.The kids at Stanford and MIT are building for space and quantum computing while ignoring AI for actual industries. There's a class divide keeping founders away from the unglamorous problems that print money. Meanwhile, these factory owners would love to partner, you just have to show up, tour the facility, and actually talk to the people doing the work.Here's the play: Find a lower-middle-market company with unglamorous IP. Tour their factory. Don't waste time with the sales team, talk to the guy making $20/hour who actually runs the machines and fixes things when they break. That's where the real value lives. Give key partners early equity tied to sales milestones. Build ONE hyper-specific feature—so niche you can describe it in five words or less. Then sell one enterprise license for $83K/month. That's $1M ARR from literally four lines of code packaged as an executable.Before you even start, check three boxes: Do you have distribution on your cap table? Do you have defensible IP? Do you have an industry expert involved? If you can't check all three, don't build it.So ask yourself: Are you building a company, or are you just building your ego? Because the real arbitrage isn't in the technology, it's in the relationships nobody else is making.That's from Josh Furstoss, exited founder, CEO advisor, and the guy who launched four companies last year by finding moats where nobody's looking.This interview is for founders who want to escape the AI hype cycle, find distribution on their cap table, and build zero-to-one products that actually sell.Ready to build differently? Head to aiforfounders.co for frameworks that 27,000 AI founders use to validate their next move. Every week. Zero fluff. Just builders building.Drop a review if this made you rethink your whole strategy.This show runs on Kitcaster, the podcasting platform that makes you sound professional without the headache. Record, edit, and distribute from one dashboard. Start free at kitcaster.com.https://www.linkedin.com/in/josh-furstoss/https://www.doctorswithoutborders.orghttps://aiforfounders.co/ ⁠https://kitcaster.com/application ⁠⁠https://ryanestes.info⁠

Hot take: AI isn’t killing creativity, it’s exposing how emotionally lazy founders have become.Because most people use AI to move faster, not to feel deeper. AI can either make you more human… or quietly turn you into a productivity zombie who panics when the tools shut off.Then I met Ziah Orion from Deep Gem Interactive.And instead of talking dashboards and prompts, we went somewhere unexpected.He uses generative music to help people process grief, identity, love, even their inner archetypes.Think songs for your dad, your partner, your future self.Not content. Connection tech.Founder takeaway: if your product only saves time, you’re competing on features.If it helps people feel seen, regulated, or grounded, you’re competing on meaning.So here’s the real question.What part of your life or business are you trying to automate because you’re avoiding actually feeling it?And here’s the twist.This interview turned into less of a formal conversation and more of two curious humans going deep.We barely scratched the surface of Ziah’s actual work, so we’re absolutely bringing him back to go deep on what he’s building at Deep Gem Interactive.If you’re a founder, builder, or creator who wants to use AI for human growth, not just speed, this one’s for you.We talk tools, identity, discipline, and how to build without burning out your nervous system.If AI feels exciting and terrifying at the same time, aiforfounders.co is your weekly grounding ritual.Real tools, real builders, no hype loops, just what actually works.Subscribe at aiforfounders.co before your competitors copy the insights and pretend they discovered them first.If this episode stretched your brain even a little, leave a review, it’s how the show survives in the algorithm wilderness.https://deepgeminteractive.com/https://www.linkedin.com/in/ziah-orion/https://aiforfounders.co/ ⁠https://kitcaster.com/application ⁠⁠https://ryanestes.info⁠

College didn’t get expensive. It got unnecessary for anyone who wants to make real money in the next 10 years.Because the future isn’t “learn more.” It’s learn fast, get licensed, get paid.America has about 700,000 registered apprentices. That’s roughly 0.4% of the workforce. Basically… nobody.Meanwhile we’ve got over a million electrician jobs open, licensed workers retiring, and data centers sucking power like a black hole.So the government did what it always does.It didn’t “incentivize” apprenticeships. It basically said:“If you want the juicy tax credits on big renewable energy projects… you need apprentices on the job.”Andy Seth saw the mess up close. The tools were trash. The bureaucracy was thicker than a Denver winter.So during COVID, he taught himself to build software, apprenticed under a real dev, and built apprentix.io.Then he did the scary founder move. He niched down hard.And it worked.He hit $1M ARR with zero W2 employees. SaaS margins. Seven-day sales cycles.Not because he “hustled harder.”Because he found the hidden lever: businesses don’t buy training. They buy revenue and compliance that doesn’t ruin their life.Founder idea: stop building better education.Build less paperwork.Every regulated industry has a compliance bottleneck begging to be turned into a software ATM.If your product disappeared tomorrow, would your customers miss the value… or would they miss the relief?If you’re a founder obsessed with leverage, niche strategy, and finding markets where demand is literally written into law, you’re going to want the full breakdown.If you like founder stories with receipts and real numbers, get on the newsletter at aiforfounders.co.It’s the closest thing to business school that won’t charge you rent. aiforfounders.co.Your next unfair advantage might be one email away. Go subscribe: aiforfounders.co.If this made you think, leave a review like you’re rating a rollercoaster you survived… and include one word: again.Founders, quick reality check: being great at what you do isn’t the bottleneck.Being known is the bottleneck.And the fastest way to become known, trusted, and repeatedly referenced is still the same: go on podcasts.Kitcaster helps founders get booked on shows your customers already listen to.Not random podcasts. Not your aunt’s mindfulness hour.The shows where buyers hang out, where deals start as conversations, and where credibility compounds.Podcasts do what ads can’t.They make you sound like the person who’s already won.You get 30 minutes to explain your thinking, tell the real story, and build trust at human speed.And if you’re thinking, “I don’t have time to pitch shows,” perfect.Kitcaster handles the targeting, outreach, booking, and coordination so you just show up and perform.If you want inbound leads that don’t feel like pulling teeth, go to kitcaster.com and get booked.https://apprentix.io/https://www.linkedin.com/in/andyseth/https://aiforfounders.co/ ⁠https://codestory.co⁠https://warmstart.ai ⁠⁠https://kitcaster.com/application ⁠⁠https://ryanestes.info⁠