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The “buy a list and blast emails” era is endingNot because outbound stopped workingBecause the data got smarter than the emailsKathryn Wu and her co-founder built Openmart as an SMB intelligence layer:Verified ownersDecision-maker contactsGoogle reviewsWebsite qualityLocation intelligence & moreNow they've launched "OpenClaw for Sales"A conversational outbound workspace built on top of that dataNo spreadsheet cleanupNo disconnected enrichment toolsNo giant table viewsJust ask the database what you needDoorDash uses Openmart for regional planningWhatnot uses it to identify high-quality sellersClay customers use the data directly inside outbound workflowsTry it out at openmart.com🎙️ Kathryn Wu, Co-Founder of Openmart on Fondo START pod‍01:13 Openmart’s SMB intelligence database and Openclaw for Sales02:16 The shift from giant lead lists to AI qualification and scoring03:43 Why SMB data differs from LinkedIn-centric sales platforms05:57 How modern GTM teams use multi-channel outbound workflows06:39 The highest-value qualification signals in SMB sales08:25 Openclaw for Sales and conversational outbound workflows09:02 How DoorDash uses Openmart for regional planning11:28 Deduplication and the hidden pain of outbound infrastructure12:16 “The future is qualification and scoring”14:08 Why proprietary data is the moat behind AI outboundLearn more at openmart.com

A drug was approved in ChinaThen it failed clinical trials in the USNo one could figure out whyThe answer was hiding in the gut microbiomeAnto Bio’s model helped identify it99% of the genes in your body aren't yours They belong to your microbiomeOver two-thirds of drugs are heavily affected by how your gut processes themBut the microbiome data was too noisy. Too messy. Petabytes of it just sitting thereAnto Bio's mission: make the gut microbiome computable for the first timeThey're building foundation models that help pharma design drugs that work for more people🎙️ Arvid Gollwitzer, Co-Founder, Anto Bio on Fondo START pod1:18 What Anto Bio is building and why it's novel2:10 Why this didn't exist before3:05 99% of your genes aren't yours4:00 Why pharma ignoring the microbiome is a huge problem5:04 The microbiome is modifiable6:30 Modeling microbiome differences across populations7:00 Drug approved in China, failed in the US, and how Anto found out why8:02 How many drugs are affected by microbiome metabolism10:00 GLP-1s and the gut microbiome connection12:42 The biggest unsolved variable in drug developmentLearn more at www.anto.bio

Most people think they need more motivation to work outThey need less frictionBut training plans assume your life stays staticYou travelIt rains You have 20 mins between meetingsPeople don't quit because they lack disciplineThey quit because adapting the plan is harder than the workout itselfHYBRD brain can helpAn adaptive AI agent that adjusts your training to whatever life throws at youBuilt by ultramarathoners, Ironman finishers, and a founding engineer who won a 100-mile cycling race🎙️ Matthew Ruiters, CTO & Co-Founder, HYBRD on Fondo START pod02:01 Connecting every wearable into one training system02:42 Using sports science to measure total training load03:07 How former Whoop teammates started building HYBRD03:50 Why “serious athlete” is really a mindset04:49 The idea behind HYBRD Brain05:18 Adapting workouts around travel, weather, and hotel gyms06:13 The consistency insight from 895,000 athletes10:44 Why athletes wanted adaptation, not just tracking11:35 Why friction stops founders from staying healthy14:03 How AI tools are changing software engineeringlearn more at www.hybrd.com

Every voice AI has the same problemThe moment you stop talking, it starts talkingBut humans don’t work that wayIn real conversations, pauses don’t always mean interruption. Sometimes they mean: keep goingCurrent AI misses this completely.Amit Yadav spent years building real-time AI systems at Meta Reality Labs for Ray-Ban smart glassesNow he’s building Fern: a sales copilot that assists teams live during meetings.Not after the call.During it.The hard problem isn’t retrieval anymore.It’s judgment.Because the future of AI won’t be defined by smarter answers alone.It’ll be defined by systems that understand how humans actually communicate.🎙️ Amit Yadav, CEO & Co-Founder of Fern, on Fondo START pod‍01:24 “Imagine your sales rep hears a prospect question and answers appear instantly.”01:55 The hardest AI problem: knowing the right time to help02:09 “Our in-house model beats human judgment, ChatGPT, and Gemini.”02:46 Building realtime AI systems for Ray-Ban Meta smart glasses03:57 Fern’s desktop copilot listens and assists during meetings04:34 The industry shift from prompted AI → proactive AI assistance05:28 Replacing Slack searches, docs, and tabs during live calls07:10 “The most exciting thing is AI helping you without asking for it.”11:09 Why silence in human conversation doesn’t always mean interruption14:15 The need for a realtime social-awareness layer between humans and LLMs‍Check out getfern.ai

Speed to lead sounds like a sales tacticIt's actually the whole gameRuben Harris knows this better than anyoneHe built a 300-person call center across 3countries to reach 1M people a month ...and saw exactly where the ceiling wasThe problem isn't effort. It's physics. A working-class student fills out a form at 10 PM. Nobody's staffed at 10 PMSo 90% of leads go coldNot because they weren't interestedBecause nobody got back to them fast enoughOutrival's AI agents respond in under a minuteThey call, text, email, and follow upOne client made $10M in new revenue from leads they already hadThe best outbound AI isn't replacing humansIt's doing the work humans never had time to do🎙️ Ruben Harris, Co-founder & CEO, Outrival on Fondo START pod‍01:12 Why Outrival focuses on outbound AI03:18 Building a 300-person call center05:27 Why speed-to-lead changes everything08:52 Aged leads as hidden revenue09:57 100,000 calls in an hour14:11 Turning one school’s leads into $10M revenue18:43 Enterprise sales advice for AI founders24:48 Pricing digital workers like employees27:56 From cello to Wall Street to Silicon Valley50:14 Building startups in the AI eraCheck out www.outrival.com"Turn every interaction into a long-term relationship"

The way to make software faster was always: make the code happen fasterAI solved that Cursor, Claude Code, Replit...Building is nearly instant nowSo what's slow?Knowing if it actually works.When AI writes your feature, someone still has to answer: did it break everything else?That's the new bottleneck. Not creation. ValidationJack Brown is building Lark to solve exactly this. An AI QA engineer that writes tests, keeps them updated, and continuously validatesThere's the building, and then there's the thing that lives on after the buildingLark is focused on that second half‍🎙️ Jack Brown, Cofounder, Lark on Fondo START pod00:15 Building an AI QA engineer01:56 AI dramatically increased development velocity02:15 The bottleneck becomes verification02:25 Cursor writes the code. Lark writes the tests.03:24 Acceptance criteria → automated validation04:15 Non-technical founders building software with AI05:35  Lark agents autonomously defining tests06:31 Everything is just validation07:56 Fully agentic software creation08:53 Why testing becomes more critical in AI-generated codebasesVisit getlark.ai to learn more

Google used to surface the PDF of a law if you searched its exact name.Now it surfaces consultancies advising on it.And LLMs have gotten worse at this too. As they’ve tried to cut costs and focus on the information 99.99% of users want, long-tail edge-case data has become much harder to find.Natalie Aresta-Katz was at a big law firm. One of their biggest clients wanted to track new and proposed laws in 45 countries that didn’t publish in English.They hired lawyers in every single country. Tried probably 15 tools on the market. Ran manual searches.Nothing worked well.Now she's building the tool she wished she had.One workflow went from up to 13 paralegals and around 120 hours a month to one user and about an hour and a half.‍🎙️ Natalie Aresta-Katz, CEO & Founder of Regbase, on Fondo START pod (full ep in comments)‍00:20 “Regbase was really born out of a place of necessity.”01:32 Tracking new and proposed laws across 45 countries02:00 Why existing tools failed02:43 The “Wizard of Oz” backroom behind regulatory databases03:26 Why long-tail legal data is getting harder to find04:23 Dropping into YC after Andrew said, “an MBA isn’t really school”05:37 Finding unspent state-level funding for school safety upgrades07:05 From 120 hours to about 1.5 hours07:38 How Regbase uses LLMs, specialty search, and link-following08:33 Why legal work may shift from hourly billing to output09:38 Searching laws in languages teams don’t speak10:27 Why Regbase unlocks more opportunity for law firms11:00 Who should book a demo: government vendors, corporate lawyers, AI law trackers, employment lawyers, and teams tracking high-volume regulatory changevisit regbase.com to learn more