BIG NEWS: I'm thrilled to announce that Arkaea Media Group has acquired Decoding Bio, one of the leading media brands in biotechnology. This is our first acquisition and a continuation of our thesis to build media for the most consequential industries in the world. Decoding Bio was founded by @ameekapadia, @pablolubroth, @KetanYerneni, @patricksmalone, and @morgancheatham and built into the definitive voice covering the intersection of AI and biology. The opportunity in biotech media is concentrated in one place: the intersection of AI and biology. This is where the future of the industry is being built. AI is rewriting how drugs get discovered, how trials get designed, how proteins get engineered. Frontier AI labs are racing into pharma. Pharma is responding with nine and ten-figure commitments. A new generation of companies is being built by founders who grew up on both sides, and they're moving faster than the legacy industry can absorb. The media covering this shift is broken. Legacy biotech publications miss the AI story. Tech publications don't take biology seriously. The intersection between them is where critical work is happening. Decoding Bio is the only brand covering it with real credibility. To Amee, Pablo, Ketan, Patrick, and Morgan: thank you for building such an incredible brand and for choosing to build the next chapter with us. The best is ahead.

I have interviewed 1,000s of the world's best founders over the past decade. Few have impressed me like @ShivdevRao at @AbridgeHQ. He navigated a brutal 5-year wilderness before exploding into one of the most dominant forces in vertical AI. Today, Abridge is a $5.3BN powerhouse. I sat down with Shiv to unpack exactly how he did it and condensed my notes below: 🚀 6 Lessons on Building a $5.3B Vertical AI Juggernaut 1. Survive Long Enough for Market Timing to Catch Up: Abridge spent 5 years in the "wilderness" before hitting a tidal wave of adoption. When you have an absolute true north thesis, your primary job in the early days is simple: stay standing and don’t die. You must be alive when the sky finally opens up. 2. Pivot the Product, Never the Core Thesis: Shiv was willing to pivot on features, go-to-market strategies, and business models. But he refused to budge on his core thesis that healthcare is ultimately powered by the spoken human signal. Die on the hill of your thesis; adapt everything else. 3. Target the Concentration of Scale Early: A massive trap for healthcare and enterprise founders is staying down-market too long for "fast feedback loops". In the US, the vast majority of clinicians are concentrated within large, integrated delivery networks. Time your "YOLO shot" to go up-market the moment the market inflects. Single biggest advice to founders on when to go up market @bhalligan @dharmesh? 4. Own Your Stack to Protect Your P&L and UX: While many AI startups rely entirely on frontier systems, 40% of Abridge's model outputs are generated by in-house models. Milliseconds matter in high-stakes enterprise workflows. Building your own models gives you insane performance gains, lower latency, and ultimate control over your P&L. When should you vs should you not build your own model @matanSF @MaxJunestrand @antonosika? 5. Don't Fight Foundation Models—Counter-Position Instead If you try to fight the frontier model giants directly, you've already lost. You win by going millions of miles deep into regulated industries with proprietary datasets and workflows they can't easily replicate. Find ways to coexist and leverage their tailwinds. Reminds me of what @bradlightcap said on his 20VC. 6. Move Toward the "Flat Company" Era: With the explosion of AI agents and advanced tooling, the traditional management layer is compressing. Shiv’s latest idealistic shift is building a hyper-flat organization: fewer managers, and highly leverageable "Super ICs" who can move in lockstep and cover massive surface area. (link in comments)

.@BreyerCap is leading the $13M seed financing of ParcelBio, a company developing a new class of durable mRNA medicines. mRNA has transformed vaccines but has not yet produced a class of chronic, disease-modifying medicines. the reason is durability. ParcelBio's APEX platform is the first we have evaluated that delivers high peak expression, sustained duration, and tunability inside a linear, manufacturable architecture. we are grateful to back @DWeinberg305 and Chris Carlson, two exceptional scientists developing the platform they are uniquely positioned to build. APEX preclinical data debuts at #ASGCT on May 14. thank you to @RLCscienceboss of @endpts for sharing the story! we will share our full thesis post tomorrow. @jimihendrixlive @bretbostwick

the biotech industry has spent five years negotiating a "trilemma" in RNA across peak expression, durability, and manufacturability: pick two. this week, we announce @BreyerCap's newest investment in ParcelBio. APEX is the first platform we have seen that delivers all three. @bretbostwick, @jimihendrixlive, and i detail our thesis here:

Exclusive: ParcelBio is launching with $13M to develop longer-lasting mRNA therapies, starting with an in vivo CAR-T program. endpoints.news/former-orbita…

counterintuitively, the steepest gains from AI in medicine will land in the specialties we describe today as "more art than science." the data-rich fields only look like the frontier because they are easiest to see.