CoS @heyivoai prev VC @UncorkCap @BessemerVP @Pearvc cs @Princeton always 💃🏻🏀📚

Joined March 2019
🎬 Most podcasts focus on founders or execs who’ve already “made it.” But the early hires also have some of the most fascinating and overlooked stories. So I’m running a small experiment: conversations w/ friends who joined rocketship companies early open.spotify.com/episode/4IS…
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Sarah Du retweeted
Excited to finally share that @phinity_ai is now out of stealth! We're announcing our seed fundraise and that we’ve reached 8-figures in annualized run rate. We’re already working with some of the largest foundation model labs. Our mission is to build fully autonomous chip design so AI can help us search beyond the limits of human engineering and discover computational systems we would never find on our own. We’re fortunate to have the support of @uncorkcap, which led our $5.2M seed round, with participation from @Moxxie including @JeffDean, following our pre-seed led by @pearvc! It’s been an amazing few months, and I couldn’t be more grateful for the opportunity to build the future of chip design with such a talented team. You can read more about what we’re building and why in our full announcement. phinity.ai/blog/introducing-… We’re hiring across all disciplines - if you’re interested in working with us, please reach out to me or @aadi_nash.
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Ep. 7 of Early Access - ft. Alex, first PM @ Nooks, backed by @kleinerperkins @lachygroom We chat which zero to 1 products worked & didn't work, and building AI for an inherently human field (sales) 🎧 here: open.spotify.com/episode/5Ip…
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Latest ep of Early Access, where I chat with early employees at fast growing startups. This month - Kaitlyn Henry, CoS @motherduck & formerly @dbt_labs. We cover how to build effective exec teams, how she defines success in the CoS role, & more 🎧open.spotify.com/episode/7JH…
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Introducing Ivo Benchmarks. Benchmarks reviews and redlines agreements by drawing upon your company's entire history of contract negotiations. We developed Benchmarks by working closely with some of the world's leading companies. They have literally millions of contracts, but no feedback loop for improving their negotiations based on what they've agreed to in the past. What they need is institutional memory for their negotiations. We're excited to support that by making Benchmarks generally available. The Ivo team is working on a lot of really cool things right now. Much more coming soon!
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Venture firms rebrand for all kinds of reasons. Sometimes it's genuine evolution - the identity finally catches up with who the firm has become. Sometimes it's camouflage - a way of looking like a different kind of firm than the one the last few years revealed. And sometimes it's just that the old website was embarrassing and someone finally had enough. Ours is mostly the first, none of the second, and just a touch of the last :) Today we're launching a new brand and a redesigned website. The logo is refreshed. The palette is cleaner. The typography is sharper. And the site actually reflects how we think in 2026. Read more: uncorkcapital.com/blog/a-new…
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Sarah Du retweeted
Sarah has contributed an immense amount to Braintrust — if you want some insights into what it takes to scale a company through product market fit, this convo is worth listening to.
Sarah^2 🤓 loved chatting about everything from @braintrust to investing & operating to our favorite slack emojis. Thanks for having me @_Sarah_Du !!
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Sarah^2 🤓 loved chatting about everything from @braintrust to investing & operating to our favorite slack emojis. Thanks for having me @_Sarah_Du !!
Each month, I sit down w/ early employees at breakout companies to understand why they joined, what they do, and what they’ve learned. This month’s guest: @sarahzengy, Chief of Staff @braintrust! 🎧here: open.spotify.com/episode/0ho…
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AI got great at reading documents. But reading was never the hard part. The hard part: turning extracted data into a running operation. Today we shipped Forge. It closes that gap. Describe your operation. Drop your data. Deploy. 🧵
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Claude is going for the girls ✨ My IG and TikTok feeds have been flooded with sponsored Claude videos from one demographic of creator - artsy girls who can't code. I saw so many of them that I decided to start saving them down (excerpts ⬇️). There's definitely a pattern!
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A few random notes from claude coding quite a bit last few weeks. Coding workflow. Given the latest lift in LLM coding capability, like many others I rapidly went from about 80% manual+autocomplete coding and 20% agents in November to 80% agent coding and 20% edits+touchups in December. i.e. I really am mostly programming in English now, a bit sheepishly telling the LLM what code to write... in words. It hurts the ego a bit but the power to operate over software in large "code actions" is just too net useful, especially once you adapt to it, configure it, learn to use it, and wrap your head around what it can and cannot do. This is easily the biggest change to my basic coding workflow in ~2 decades of programming and it happened over the course of a few weeks. I'd expect something similar to be happening to well into double digit percent of engineers out there, while the awareness of it in the general population feels well into low single digit percent. IDEs/agent swarms/fallability. Both the "no need for IDE anymore" hype and the "agent swarm" hype is imo too much for right now. The models definitely still make mistakes and if you have any code you actually care about I would watch them like a hawk, in a nice large IDE on the side. The mistakes have changed a lot - they are not simple syntax errors anymore, they are subtle conceptual errors that a slightly sloppy, hasty junior dev might do. The most common category is that the models make wrong assumptions on your behalf and just run along with them without checking. They also don't manage their confusion, they don't seek clarifications, they don't surface inconsistencies, they don't present tradeoffs, they don't push back when they should, and they are still a little too sycophantic. Things get better in plan mode, but there is some need for a lightweight inline plan mode. They also really like to overcomplicate code and APIs, they bloat abstractions, they don't clean up dead code after themselves, etc. They will implement an inefficient, bloated, brittle construction over 1000 lines of code and it's up to you to be like "umm couldn't you just do this instead?" and they will be like "of course!" and immediately cut it down to 100 lines. They still sometimes change/remove comments and code they don't like or don't sufficiently understand as side effects, even if it is orthogonal to the task at hand. All of this happens despite a few simple attempts to fix it via instructions in CLAUDE . md. Despite all these issues, it is still a net huge improvement and it's very difficult to imagine going back to manual coding. TLDR everyone has their developing flow, my current is a small few CC sessions on the left in ghostty windows/tabs and an IDE on the right for viewing the code + manual edits. Tenacity. It's so interesting to watch an agent relentlessly work at something. They never get tired, they never get demoralized, they just keep going and trying things where a person would have given up long ago to fight another day. It's a "feel the AGI" moment to watch it struggle with something for a long time just to come out victorious 30 minutes later. You realize that stamina is a core bottleneck to work and that with LLMs in hand it has been dramatically increased. Speedups. It's not clear how to measure the "speedup" of LLM assistance. Certainly I feel net way faster at what I was going to do, but the main effect is that I do a lot more than I was going to do because 1) I can code up all kinds of things that just wouldn't have been worth coding before and 2) I can approach code that I couldn't work on before because of knowledge/skill issue. So certainly it's speedup, but it's possibly a lot more an expansion. Leverage. LLMs are exceptionally good at looping until they meet specific goals and this is where most of the "feel the AGI" magic is to be found. Don't tell it what to do, give it success criteria and watch it go. Get it to write tests first and then pass them. Put it in the loop with a browser MCP. Write the naive algorithm that is very likely correct first, then ask it to optimize it while preserving correctness. Change your approach from imperative to declarative to get the agents looping longer and gain leverage. Fun. I didn't anticipate that with agents programming feels *more* fun because a lot of the fill in the blanks drudgery is removed and what remains is the creative part. I also feel less blocked/stuck (which is not fun) and I experience a lot more courage because there's almost always a way to work hand in hand with it to make some positive progress. I have seen the opposite sentiment from other people too; LLM coding will split up engineers based on those who primarily liked coding and those who primarily liked building. Atrophy. I've already noticed that I am slowly starting to atrophy my ability to write code manually. Generation (writing code) and discrimination (reading code) are different capabilities in the brain. Largely due to all the little mostly syntactic details involved in programming, you can review code just fine even if you struggle to write it. Slopacolypse. I am bracing for 2026 as the year of the slopacolypse across all of github, substack, arxiv, X/instagram, and generally all digital media. We're also going to see a lot more AI hype productivity theater (is that even possible?), on the side of actual, real improvements. Questions. A few of the questions on my mind: - What happens to the "10X engineer" - the ratio of productivity between the mean and the max engineer? It's quite possible that this grows *a lot*. - Armed with LLMs, do generalists increasingly outperform specialists? LLMs are a lot better at fill in the blanks (the micro) than grand strategy (the macro). - What does LLM coding feel like in the future? Is it like playing StarCraft? Playing Factorio? Playing music? - How much of society is bottlenecked by digital knowledge work? TLDR Where does this leave us? LLM agent capabilities (Claude & Codex especially) have crossed some kind of threshold of coherence around December 2025 and caused a phase shift in software engineering and closely related. The intelligence part suddenly feels quite a bit ahead of all the rest of it - integrations (tools, knowledge), the necessity for new organizational workflows, processes, diffusion more generally. 2026 is going to be a high energy year as the industry metabolizes the new capability.
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Another year, another prediction piece! 5 trends I’m excited about in 2026: 🌓 Hybrid AI (LLMs + deterministic systems) becoming the default 🖼️ Multimodal AI getting operational 🛣️ Consolidation at the infrastructure layer (cont.)
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finding a cs job so hard in this market we got people going to the nba instead 😭
Maxime Raynaud graduated from Stanford with a DOUBLE MAJOR in Mathematics & Computer Science four months ago… Last night, he made his NBA Debut for the Sacramento Kings.
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Sarah Du retweeted
building a bank from first principles or something like that
Replying to @_Sarah_Du @maiale
Dropping ep. 3 of Early Access - where we talk to early employees at rocketship companies! ft. @charliejliao, @column's 1st bizOps hire. 🎧 Listen here: open.spotify.com/episode/6dO…
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Uncork's Plus funds - separate from our seed funds - are designed to allow us to double down on our breakout portfolio companies. However, very occasionally, we have the opportunity to invest in a new name when we have a special relationship with the team. Our partner @amy led Gamma's seed round at Accel and we're delighted for Uncork to now be a part of their journey 🚀
Excited to share that @GammaApp has raised a $68M Series B at a $2.1B valuation, led by @sarahdingwang @a16z with participation from @uncorkcap! It’s been a privilege to have been part of the Gamma story since leading their seed round with $0 in revenue and a handful of users in 2021.
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