Adam Menges

Stealth is not a long-term strategy. Aaron Harris built YC's Series A program and has helped founders raise billions. He argues that by Series A, building in secret means you're missing critical information on where investors are actually excited. Great founders decide if they truly need capital, run live-market reads, then jump into their fundraise when the wave is cresting.

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🚀 YC Founders: Where the Next Breakouts Are Coming From Y Combinator isn’t just an accelerator—it’s the factory floor for scrappy ideas that turn into real companies. We ran the latest Specter export across all cohorts (with a zoom on W25/SP25/S25) and mapped #origins, #universities, #past_employers, and what teams are building now. Here’s the gist: 🌍 Geo shift (by origin proxy: education + language) • #US ~50% → 45% in 2025, • #Asia ~30% → 35% in 2025, • #Europe ~12% → ~15% in 2025, • #LATAM / #Africa ~8% → ~5% in 2025. → TL;DR: Globalization is up (especially Asia), while the US still pulls talent with ecosystem gravity 🇺🇸 🎓 Top universities (recent cohorts) • 2025 lead cluster: Stanford University (top), then Georgia Institute of Technology, Rice University, The University of Texas at Dallas, University of Cambridge, The University of Texas at Austin, University of Oxford, University of California, Princeton University. • 2023 lead cluster: University of California system (top), then Harvard University, University of Waterloo, Georgia Tech, Duke University, Berkeley, Massachusetts Institute of Technology, Stanford, #Virginia, #McGill. → TL;DR: Heavy CS/Eng + selective MBA pipelines; more international spread than a few years ago. 🏢 Top past employers (all cohorts, past roles only) Google, Meta, Amazon, Microsoft, #Palantir lead the pipeline, followed by #Stripe, #Uber, Apple, Tesla. Research/consulting routes show up via Stanford/MIT/Harvard (RA/research roles) and BCG. → TL;DR: The modal YC founder is an engineer/product builder with FAANG/infra experience or research pedigree. 🏗️ What they’re building (2025 vs 2023) • #B2B dominates (2025 65% vs 2023 68%), but the content shifts. • #Industrials jumps (~2% → 9%)—robotics, hard-tech, ops. • #Fintech cools (9.5% → ~5.6%), #Healthcare eases (10.3% → 7.7%). • #Consumer steady (~6–7%), #Education doubles but small (1.2% → 2.6%). → TL;DR: #AI isn’t a category anymore—it’s the default layer inside B2B/Industrials. 🧭 Patterns we keep seeing (“YC material”) • Ship early, ship often: real products live before YC (open-source, side projects, indie SaaS). • Deep technical core: CS/Math/EE tracks + hands-on systems work. • Big-tech apprenticeships: Google/Meta/Microsoft/Amazon/Palantir-sized training grounds. • International mobility: study/work hops (Asia ⇄ US/Europe) are common. • Complementary founder stacks: Eng + GTM or Eng + Ops pairings win admission and traction. 🏆 Icons HitPay / JumpWire (YC W22) / Supabase / Perplexity / Replicate / Agentnoon / Marr Labs / Moonset Health (YC F24) / Misprint, Inc. TL;DR: YC is looking for technical builders who’ve already shipped, with a growing share from Asia and Europe, a talent pipeline through big-tech + research, and a product mix where AI is baked into B2B and hard-tech. 👇 Full breakdown + downloadable dataset in the comments #YCombinator #Startups #AI #B2B #Robotics #VentureCapital #SpecterData

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Phosphor Capital, founded by two-time YC alum Kulveer Taggar, has raised $34M across two funds to back startups emerging from the Y Combinator ecosystem. With 200+ YC companies already in the portfolio—including Circleback and Gumloop—Phosphor is doubling down on early-stage AI and software bets. Backed by Garry Tan, the firm brings founder-first energy to YC’s next wave of breakout startups. https://lnkd.in/eMP9scxT #VentureCapital #YCAlumni #AIStartups #EarlyStageFunding #FounderLed #SeedFunding #YCombinator

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One of the fastest ways to unlock PMF is by testing faster. At Transcend, every founder in our Fellowship runs weekly experiments using our custom-built PMF Experiment Tracker. We believe that every edtech founders’ #1 priority should be to find product-market fit and they should do this by running lean & rapid weekly experiments. This PMF Experiment Tracker is one of our most-used tools among fellows. By running and tracking experiments, you stop guessing and start testing your way to PMF. It's one of the most-used tools among Transcend Fellows. 💥 It helps you: ➡️ Pinpoint where you are on the PMF ladder (Pain → Magic → Growth → Retention) ➡️ Design weekly experiments around real growth bottlenecks (demo rates, signups, referrals) ➡️ Track key metrics, analyze what worked, and decide what to double down on ➡️ Learn from real world examples of experiments run by Transcend Fellows building for edtech audiences in K-12, Higher Ed, and Corporate Learning, to name a few. This isn’t just a fancy template. It’s the real sheet Transcend Fellows use to get clearer on their customer, tighter on their pitch, and sharper on what moves the needle. Want a copy? 💬 Drop a comment below and we’ll send it your way within 24 hours! (Includes an example tab to help you hit the ground running) We’ll only be sharing this with folks who drop a comment by May 25.

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Don't Build a Better Wheat Farm" - Why Defensibility Stakes Are Higher in Deep Tech Just published a new piece on my "Ignore the Confusion" blog, building on thoughtful insights from Eric Ver Ploeg at Tunitas Ventures about startup defensibility. Eric's core thesis: Too many startups pitch like wheat farmers - "huge TAM, slow incumbents, growing market, domain expertise" - but fail to think through long-term defensibility until it's too late. From a deep tech perspective, the stakes are even higher: ** Unlike software, deep tech founders must commit to defensibility strategies from day one - their funding depends on it ** Patent vs. trade secret decisions are often difficult to reverse and shape your entire competitive strategy ** Even "picks and shovels" providers (the tools that make industries more efficient) become commodities without proper moats The key insight that resonates: Defensibility can't be retrofitted. Whether you're building software or deep tech, your moat must be architected into the business model from the start. Thanks to Eric Ver Ploeg for sharing these insights on startup strategy and letting me build on his framework from a deep tech lens. Read the full post: https://lnkd.in/dEj_iF-Q #DeepTech #StartupStrategy #Defensibility #VentureCapital #Innovation

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1 in 4 companies in YC's latest cohort are building voice agents. 🤯 2025 taught us a lot about where voice AI is actually heading, and which numbers separate signal from noise. We spoke with customers, collaborators and research teams to identify the numbers that defined 2025's shift and what it signals for 2026. Swipe for the 9 that matter 👉 Featuring insights from Jure Sotosek (ParakeetAI), Vikram Singh (Mixhalo), Samantha Rosendorff (boost.ai), T-Bot 👾 (VoiceAIspace.com 👾) and Ahmed Omar (Sully.ai). Full piece: https://lnkd.in/exvnse_H #VoiceAI #Voiceagents #EnterpriseAI

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Elie Schoppik has spent his career at the intersection of education and engineering. He built early ed-tech tools that helped people actually retain knowledge, founded a Bay Area coding bootcamp that trained thousands of developers through practice and feedback, and now leads Technical Education at Anthropic. Despite all that experience, Elie says most teams are using AI wrong: they’re treating it like an all-knowing oracle instead of a tutor. This is why Elie designs prompts, examples, and workflows that treat AI as a teacher, instead of a shortcut. In our conversation, we discuss: • Why relying on AI for “fast answers” erodes judgment and verification • How to turn prompts into guided lessons • Why context engineering is the most underrated skill in 2025 • Practical exercises any team can run tomorrow to raise AI fluency • What leaders should steal from Anthropic’s approach to technical education  Episode is live now — full conversation linked in the comments.

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Introducing Di Qi, Legora’s first Forward Deployed Engineer. Di’s built products from zero twice as a YC founder. She’s led teams, shipped complex systems and navigated ambiguity at speed. Now, she’s embedding directly with law firms – identifying high impact solutions and shaping how our platform evolves as it scales. Her story is a glimpse into where legal tech is headed - and who’s shaping it: https://lnkd.in/e_yH_HVW

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There is so much magic for scientists locked away in LLMs. But unlocking it requires a rare blend of scientific and engineering expertise. That’s why I’m thrilled that Nicholas Larus-Stone and Sphinx Bio are joining Benchling. I’ve gotten to know Nicholas over the last few months. We share a vision for what AI agents can do for scientists – and an obsession with turning that potential into real, everyday value. Together, we’re building agents that automate toil and answer complex questions. See what we’re building: https://lnkd.in/gtDHZpnt

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