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- Yesterday9 min
START pod: Teddy Li, Co-Founder, Prepse: “Train smarter. Sell better.”
Teddy li's first version of Prepse did something reasonableIt connected to your call recordings, pulled out the data, and filled in your CRM. customers told him it was a nice add-on. he could have explained why they were wrong. he chose to find out why they were right.So he looked closer, and what the most interested customers actually wanted was underneath it.They didn't just want cleaner data. they wanted to use it to improve how their teams sold, to make their median reps perform like their top ones.The data was the input. The training was the point.He then worked with hundreds of enablement managers to learn what the best teams do differently, and built Prepse around the answer: reps run simulations of real buyer conversations before they have them for real.The real product was hiding one question deeper than the one he set out to answer.The useful question about ai in sales isn't what it can replace. It's what it can't. It can't decide how your company should handle a pricing objection, or what a good discovery call sounds like in your market.That judgment lives in a handful of your best people, and it's the scarce thing.He built Prepse on that premise. Instead of automating the seller, it takes the judgment your best people already have and turns it into something every rep can practice against. Your playbook, your objections, your definition of good, run as simulations a rep can repeat until the real call feels like the fourth take.The leaders set the bar. The software makes sure everyone can reach it.🎙️ Teddy Li, Co-Founder, Prepse on Fondo START pod00:00 Teddy introduces Prepse and what an AI enablement manager actually does01:00 The original product: pulling call-recording data into the CRM01:25 Why customers treated it as an add-on, and what they actually wanted instead01:45 Studying hundreds of enablement managers to model best-in-class teams02:05 Snagging the six-letter domain for ten bucks, and what Prepse stands for02:40 His previous company, Nofin, and going through YC03:05 Why a founder's skills carry over non-linearly between startups04:00 The two kinds of teams Prepse sells to04:30 The real goal: turning the median rep into a top rep05:35 His onboarding philosophy, getting users to the magic immediately06:30 What he tells founders about cutting onboarding friction07:00 Revealing product depth one layer at a time, like an onionCheck out prepse.com
- 2 days ago11 min
START pod: Moody Abdul, CEO & Co-Founder, Klarify "AI Agent for Therapists"
AI shouldn't replace therapists.It should help them spend more time being therapists.Not because AI won't get smarterBecause good therapy isn't just informationIt's trustIt's compassionIt's the human element.Most therapists spend only about half their time doing therapyThe other half?Running the businessNotes. Paperwork. Marketing. Insurance claims.Klarify automates the work around the session so therapists can focus on the work only they can doToday, more than 7,000 therapists use the platformThe result is clear: they spend less time running a business, more time doing the work only they can doMoody Abdul, Co-Founder & CEO of Klarify, on Fondo START Podcast01:53 Therapy changed my life02:22 A therapist asked to use my previous product02:31 Therapists spend much of their time on admin03:22 Surpassing 7,300 therapists on the platform03:46 Why AI won't replace therapists05:07 The real value hidden inside therapy notes05:28 Turning session insights into therapist marketing06:09 Building tools for independent therapists07:00 Fighting insurance claim denials with AI07:28 Why therapist SEO and client discovery matter08:17 The therapist Klarify serves today09:32 From solo therapists to 60-person clinics10:00 Solving therapist-client matchingLearn more at www.klarify.ca
- 3 days ago21 min
START pod: Naman Bansal & Shreyans Jain, Cofounders, Manicule: "AI Native Developer Relations"
Most companies don't realize they have a documentation problem until everyone already depends on it.Customers use it. New hires use it. Engineers use it.And when documentation falls out of date, the whole system starts working against itselfPeople stop trusting what they're readingTeams lose contextAnd nobody can fix it, because the problem is everywhere at onceThe longer it goes unfixed, the harder it is to untangleThat's the opportunity Manicule sawThey're building an AI-native DevRel company for developer tools - owning documentation, technical content, GEO, and distribution across social channels.The premise isn't that AI should replace expertise. It's that expertise should scale.Their AI agents audit and test at scale. Their humans own the architecture, the writing, and the creative direction.Every review improves the systemEvery project creates more context. Every iteration raises the barWhat started as a highly manual business - helping developer companies create better technical content - has become a scalable AI-native operationToday, Manicule works with some of the fastest-growing developer tool companies - including Supermemory, Greptile, and Reducto - has scaled fast over the last few months, and has more demand than it can take on.Not because they publish more content. Because they help developer companies create content developers actually trust.🎙️ Naman Bansal & Shreyans Jain Co-founders of Manicule (YC P26) on Fondo START00:57 What Manicule is building03:43 The Supermemory customer that changed everything04:47 Building startups together in high school05:55 Early pivots, recruiting agencies, and first revenue06:18 Applying to YC as teenagers07:24 Lessons from being the first engineer at Supermemory08:49 How DevRel became a growth engine09:54 Why long-form content beats viral marketing10:53 Growing Manicule 6× and crossing $60K MRR12:17 Why developer documentation is often broken13:19 How AI changes go-to-market without replacing quality14:42 The biggest misconception about GEO16:00 What founders misunderstand about getting into YC17:42 The hackathon that led to YC19:05 Turning a manual agency into an AI-native company21:33 Building toward $5M ARRlearn more at manicule.dev
- 3 days ago11 min
START pod: Nicolò Magnante, CEO & Co-Founder, Superlog "Observability that installs itself and fixes the bugs it finds"
A production issue shouldn't require a detectiveYet that's how most observability works todayMost observability tools just dump alerts. Duplicates, no context, and you still fix it yourselfNicolò Magnante and his cofounder Arseniy Shishaev - who spent years building part of Datadog's metrics product - think that's backwardsSo they built Superlog. Observability that's meant never to be opened.A wizard scans your repo, installs proper OpenTelemetry, and runs daily to keep up as you shipWhen something breaks, it groups the errors into one incident, investigates with full context - logs, traces, recent deploys, past Slack threads - and drops a single mergeable PR in Slack.Merge itIgnore itOr open it in Claude Code and tweak itVendor-neutral, so you keep every log, trace, and metric - even if you leaveNot another notification. A fix.🎙️ Nicolò Magnante, CEO & Co-Founder, Superlog "Observability that fixes your bugs"02:00 Why existing observability tools create friction03:00 The YC pivot that led to Superlog05:22 Why observability must evolve beyond monitoring05:40 Installing observability with a single prompt06:14 Why startups are the ideal first customers10:01 Why the future is self-healing softwareLearn more at superlog.sh
- 4 days ago12 min
START pod: Manav Modi, CEO & Cofounder, AgentPhone “Phone numbers for AI Agents”
AI agents can write code, analyze data, and pass the bar examThey can't order you a pizza because they don't have a phone numberThink about how much of the real world still runs on phone numbersSMS verificationDelivery coordinationAccount creationCalling a business...Without one, an agent is stuck behind glassManav Modi & cofounder Meet Modi built AgentPhone to fix thatGive your agent a phone number and it can suddenly actHe told his agent to order DoorDashIt created an account, talked to the delivery driver, made the paymentPizza showed up at his door. Y Combinator is a customer. After An engineer tried Twilio and got buried in compliance, AgentPhone had him live in a dayEvery person will soon have hundreds, maybe thousands of agents working for themThe hard part isn't making them smartIt's giving them the tools to touch the real world 🎙️ Manav Modi, CEO & Co-Founder, AgentPhone on Fondo START pod00:57 Why AI agents need phone numbers to interact with the real world01:24 The tools that move agents closer to human-level autonomy01:50 The emerging infrastructure stack powering AI agents02:18 Why payments may become a critical layer for autonomous agents02:42 An AI agent ordering DoorDash end-to-end without human involvement03:08 What happened when 100+ developers built on AgentPhone03:26 Processing 4,000+ calls and 5,000+ messages in a single day03:43 Unexpected real-world use cases discovered during the hackathon04:24 How phone numbers unlock authentication and action05:37 The vision of every person having hundreds or thousands of agents06:16 Building identity and authentication systems for AI agents07:31 The startup pivot that led to AgentPhone and ultimately YCCheck out agentphone.ai
- 1 weeks ago8 min
START pod: Samuel Mirpuri, Co-Founder, flowscope “Their agents learn your business. Then automate it.”
Flowscope’s agents can map an entire department in two weeks.Then they automate it.It’s an AI-native consulting firm where agents learn how a business actually runs - process by process - then automate the most manual work directly inside the company’s existing systemsNot in quarters. In days.Samuel kept seeing the same pattern every time a consulting firm walked into a large organization:Great strategyBeautiful slidesMinimal implementationThe recommendations were smart. The operational change rarely came.He also saw a second problem: Consulting fees were disconnected from outcomes. Clients paid upfront whether the recommendations worked or not.The incentives were broken by designSo he and his co-founder Javier built the thing consulting always promised but rarely delivered:Implementation.The pitch to clients is simple:Grow your company with the headcount you already have.🎙️ Samuel Mirpuri, Co-Founder, flowscope on Fondo START pod00:57 Why traditional consulting stopped at recommendations instead of implementation02:33 The disconnect between consulting fees and measurable outcomes03:18 How Flowscope maps entire enterprise departments in two weeks04:24 Why AI should augment human judgment instead of replacing people05:30 From aeronautical engineering classmates to AI-native founders06:02 Sam Altman’s $2M OpenAI token offer to YC startups07:00 Why AI tokens may become a new startup currency layer07:29 Customer, Customers, CustomersCheck out www.flowscope.com
- 1 weeks ago10 min
START pod: Michael Egan, CEO & Co-Founder, CodeCanary: “Find and fix bugs from session replays with AI”
99% of session replays are your app working exactly as expected (hopefully)The other 1% is where the friction hidesThe bugs.The failed onboarding flows.The conversion leaks.No team has time to watch them all.That's the problem Michael Egan and his co-founder kept hitting at their last company. They had analytics. They had session replays. They had ideas to improve conversion.The small fixes always lost to bigger priorities..So they pivoted and built CodeCanary: An AI product engineer that connects to GitHub, PostHog, and Slack. It watches your session replays, finds the UX friction, and opens pull requests with the fixAlways on. Always shipping.Not dashboardsNot alertsActual fixes🎙️ Michael Egan, CEO & Co-Founder, CodeCanary on Fondo START pod00:57 AI agents connected to your product analytics and codebase01:20 "You wake up to pull requests the next morning"03:41 Pivoting from enterprise mapping software04:42 Why nobody actually watches their session replays05:02 Surfacing the 1% of user behavior that matters05:47 Autonomous A/B testing tied directly to revenue06:37 Why this solves problems engineers never had time for07:30 "With every new user, your product gets a little better"08:30 How to know when it's time to pivotCheck out www.codecanary.ai
- 1 weeks ago17 min
START pod: Jeff Liu, CEO & Co-Founder, FinalDose "Programmable DNA drug destroying all cancers, unlocking 80% of targets"
Most cancer drugs target proteinsFinalDose thinks the real opportunity is one layer deeper: DNAJeff Liu and his team are building a programmable drug platform that uses genetic mutations to identify and selectively destroy cancer cellsCells without those mutations are not targetedInstead of creating a completely new drug for every cancer type, the platform is designed as a reusable system with different genetic instructionsOne chassis.Different disease targets.The broader bet: DNA is more deterministic than proteins, which could unlock therapeutic approaches traditional drugs struggle to reachSearch.Destroy."A programmable cell elimination platform."🎙️ Jeff Liu, Cofounder & CEO of FinalDose on START 00:11 Why proteins may be the wrong layer for cancer treatment01:14 Using DNA mutations as programmable kill signatures03:20 Building a reusable therapeutic platform instead of one-off drugs05:00 Why hard biotech problems require interdisciplinary teams06:00 Getting into YC after a 4 a.m. interview in Japan08:00 Sam Altman’s $2M AI token offer — and why FinalDose passed10:08 How AI-native biotech is accelerating programmable medicine12:00 Why the future of medicine may look more like engineering13:05 The regulatory bottleneck for programmable therapeuticsLearn more at finaldose.ai
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