Summer camp assistant Hermes Agent to the rescue @NousResearch
Peter Yang
Summer camp assistant Hermes Agent to the rescue @NousResearch
Jed White 💥♻️
Every YC batch is stronger than the last.
We help founders with YC application reviews every batch. The draft applications getting obviously better every cycle.
AI native founders use AI tools to execute faster and smarter.
AI lifts all boats.
YC is just getting started.
Paul Graham: All through YC's history, investors (for obvious reasons) have tried to tell founders that YC wasn't worth it. In 2010 they just said we sucked. Now, since it's obvious we didn't, they've had to change the claim: now it's YC *used* to be great, but has declined from what it was.
Vibe Guessing
Re I absolutely agree that there really is this 10x opportunity for companies to be $40 trillion in market cap and beyond—perhaps Nvidia, Google, and beyond. Really fascinating to consider what that could end up looking like.
Really curious what your view is on what those companies may end up looking like, and if it's all fundamentally about being recursively self-improving, then what the natural kind of world looks like in that regard for there being separate companies, even while the frontier model intelligence keeps getting pressed forward.
In this regard, I thought that the latest No Priors and Latent Space episode @saranormous @eladgil @swyx with Microsoft CEO Satya Nadella @satyanadella was super interesting, including Nadella talking about how basically companies need to have access to frontier intelligence and have a path to hill climb whatever their business is in order to have actual terminal value that isn't zero. And so in that sense, it's framed as, well, this is a necessity to happen rather than just an inevitability.
Even NVIDIA and the chief scientist session with the chief scientist of Google spoke at Nvidia GTC 2026 about the different agents that are needed to build out new kinds of chips. And even today, Anthropic talked about the self-improving loop that they are identifying for AI research.
To close it out, Satya had mentioned in that same episode in the last day or two that Kevin Scott's @kevin_scott point about not just asking about what was hard that is now easy, but what is impossible that is now possible. It would be awesome if you were to write an essay about what that kind of thing looks like. In fact, that might even be a good prompt to ask for, say, the top 50 companies in public markets and top 50 private companies, what is impossible in those businesses that becomes possible and how well positioned is that business versus, say, the next best alternative competitor, or which may include a completely new company.
sarah guo: 1/ 🔥 @NoPriorsPod x @LatentSpacePod chat with @SatyaNadella at @Microsoft Build. He has the sharpest mental models of any public company CEO I've interviewed.
$MSFT is at its heart still a tools company! Big focus on agentic coding, harness & AI evals. Takeaways:👇
MakerThrive
i used @Replit to rebuild the million dollar homepage!
payments -> stripe
auth -> replit
db -> neon
buy a space, promote your company!
500 pixels already sold 🚀👇
https://1milllionpixels.com/
nico laqua
The number one question we got asked during our YC batch by investors was, “why are you doing yc”? We could have raised capital without it very easily. And the answer then was the same as the answer is now, that YC made us a lot more ambitious and made Corgi a much bigger company
Paul Graham: All through YC's history, investors (for obvious reasons) have tried to tell founders that YC wasn't worth it. In 2010 they just said we sucked. Now, since it's obvious we didn't, they've had to change the claim: now it's YC *used* to be great, but has declined from what it was.
hey grok, make me a video of
“literally what happens when you put up tokenmaxxing leaderboards in your company”
4k, set in taiwan, shot on iphone, Flickr, trending on Artstation
Paul Graham
There's a startup in the current YC batch that built an MRI machine in 101 days.
NIMBYs frequently virtue signal by attacking developers but it’s a smoke screen and we shouldn’t listen. Markets are good.
Housing is the defining reason why cost of living is high. If you want better lives for people, you build housing, so housing costs go down.
Ankit Gupta: Bunch of NIMBY losers want to block a big housing opportunity in Davis. I live in this neighborhood and would welcome it.
Having 500 more families living here would make the square even more bustling and vibrant, attract new restaurants, and lower the cost of living for everyone
I spent the whole day today setting up integrations and skills in Codex for my top creator workflows.
Now I'm convinced that you can save at least 50% of your time on any type of knowledge work if you just set up the system upfront.
Note that all my workflows have human checkpoints along the way so I can apply my "taste."
Anyway, it feels extremely liberating to have all this set up. If you want to do the same, just follow these three steps:
1. Reflect on your past week:
- What work did you spend the most time on?
- What work was the most repetitive?
Pick your most painful, manual workflow to start.
2. List out every single step of that manual workflow. Be very detail oriented.
3. Open Codex (or Claude Code) and paste the list of steps from 2 and ask it "What integrations and skills can I build to streamline this with your help?"
AI will guide you the rest of the way.
Peter Yang
I spent the whole day today setting up integrations and skills in Codex for my top creator workflows.
Now I'm convinced that you can save at least 50% of your time on any type of knowledge work if you just set up the system upfront.
Note that all my workflows have human checkpoints along the way so I can apply my "taste."
Anyway, it feels extremely liberating to have all this set up. If you want to do the same, just follow these three steps:
1. Reflect on your past week:
- What work did you spend the most time on?
- What work was the most repetitive?
Pick your most painful, manual workflow to start.
2. List out every single step of that manual workflow. Be very detail oriented.
3. Open Codex (or Claude Code) and paste the list of steps from 2 and ask it "What integrations and skills can I build to streamline this with your help?"
AI will guide you the rest of the way.
Ankit Gupta
new YC-funded decacorn
Y Combinator: Congrats to @kiwicopple, @AntWilson, and the @supabase team on their $500M Series F at a $10B valuation!
Database launches on Supabase have grown 600% in the past year, with more than 60% of new databases launched by AI tools. Nearly 10 million developers build on Supabase
Defense primes build Bugattis. The army is begging for an F-150.
A founder in our batch is building munitions backwards: start at 'what can we stamp out for $20k?' and make the engineers hit it.
Y Combinator: Tenet Industries (@industriestenet) is building low-cost, mass-producible defense systems, starting with strike drones.
Defense primes are still building Bugattis and Ferraris. Tenet is building the F-150 for defense.
Huge milestone here. Firecrawl is making something agents want.
Firecrawl: We've now fetched 8,000,000,000+ pages at Firecrawl 🔥
A few other milestones in 2 short years:
- 1.25M+ developers
- 150K+ companies using us
- 125K+ GitHub stars (top 100 repo)
- 2.5M+ weekly downloads on npm + PyPI.
Thanks for building with us & we're just getting started!
Never go full Steyer
Kane 謝凱堯: The disappointing thing about Steyer is that he ran Farallon Capital quite competently and could have run as the practical competent candidate.
Instead he doubled down on Hasan-Piker-lefty-edgelord messaging and ran a trainwreck of a campaign.
http://x.com/i/article/2062758410375110656
So close to product market fit is still not product market fit
Garry Tan: http://x.com/i/article/2062758410375110656
Two YC decacorns in one day and one of them is building commercial fusion. Polaris hit 150 million degrees C, first privately funded machine to do it. This is the abundance future, built by people who actually ship. https://x.com/agupta/status/2062742126375428192
Ankit Gupta: oh wow a second YC-funded decacorn in the same day that must be some sort of record
Isomorphic
likely that every single person in that game was already familiar with this
Guy: Levels of Mafia/Werewolf/Secret Hitler:
• You play, poorly
• You play, skillfully
• You play, poorly, so that people will think you’re bad at deception out-of-game
• You refuse to play, claiming you don’t engage in deception, even in games/roleplay/acting/if consented
ryo
"Reality: The Final Eval" — 現実タスク完了率こそが最終評価指標（@swyx / Andon Labs）。
複数のAI実装を並列で回していると、実感として正確だと思う。SWE-Benchの数字より「本番で動くか」が判断軸。エージェント設計で最初に決めるのは検証基準、次にモデル選定。
https://www.latent.space/p/andon
Kenneth Roth
It speaks to Trump destructive self-absorption that he is willing to sacrifice progress in medical and scientific research to pursue his far-right political vendettas. https://trib.al/KZcCL2h
💥Susan Dyer Reynolds🗞️
Let’s look at the numbers which @FitzTheReporter left out of his story: San Jose has one city employee for every 112 residents. San Francisco has one city employee for every 21 residents despite having 125,000 fewer residents (and yes San Jose runs the airport, too).
💥Susan Dyer Reynolds🗞️: “‘His only idea is to cut a huge amount of the workforce,’ Thorn said.
Lurie has already issued pink slips to 127 city employees this year.” Only 127? Lurie needs to keep cutting. https://sfstandard.com/2026/06/03/san-francisco-progressives-election-defeat/
GBrain is your company brain
Shann³: how I’m building an agent company inside my agency.
the structure looks like this:
Agency gBrain
→ Orchestrator Hermes Agent
→ Department verticals
→ Specialist agents
→ Scoped sub-agents
gBrain is the company brain.
It gets ingested with the data and experience we
Paul Graham
Sam Altman deserves credit for YC's turn toward hard tech. When he became CEO in 2014 he went out and recruited companies doing stuff like airliners and fusion, and hard tech startups have been some of the best in every batch since.
Paul Graham
I strive to make my writing unsummarizable, in the sense that it has so little fluff left in it that if you take any words out, as summaries by definition do, you lose a lot of interesting ideas.
How to build AI skills that check their own work and improve over time:
1. Give it context
Ask AI: "Create a skill for this [repeated task]. Here are examples of good output so it knows what good looks like."
2. Make it easy to trigger
“Write a clear skill description using this pattern: Use when the user wants to [do this].”
3. Add evals
"Create an evals md with 10 pass/fail checks for common errors in the skill's output."
4. Add memory
"Create a memory md to capture one-sentence learnings from past chats using this skill."
5. Build a skill to edit skills
"Create a skill that cleans up other skills by removing duplicate or stale instructions, vague rules, and AI slop."
📌 Watch my full walkthrough here: https://youtu.be/uT3EQPVIEb0
Peter Yang
How to build AI skills that check their own work and improve over time:
1. Give it context
Ask AI: "Create a skill for this [repeated task]. Here are examples of good output so it knows what good looks like."
2. Make it easy to trigger
“Write a clear skill description using this pattern: Use when the user wants to [do this].”
3. Add evals
"Create an evals md with 10 pass/fail checks for common errors in the skill's output."
4. Add memory
"Create a memory md to capture one-sentence learnings from past chats using this skill."
5. Build a skill to edit skills
"Create a skill that cleans up other skills by removing duplicate or stale instructions, vague rules, and AI slop."
📌 Watch my full walkthrough here: https://youtu.be/uT3EQPVIEb0
Crazy times
Ivan Landabaso: New business creation on stripe is up 2x YoY.
My notes from the @patrickc x @amasad pod:
Ankit Gupta
sadly for SF this might be true.
I just recommended to a founder that “15k for a 2br seems within normal these days”. He’s funded by YC so he can live with it but not a good sign for the ecosystem
villi: San Francisco is booming. But here is the deal, the ability to absorb growth is limited and constrained by housing. So I expect for practical reasons startup formation to spread geographically and yes, the return of remote work to reach and attract talent.
Y Combinator
Back in 2023, Max Junestrand was a college student in Sweden with a McKinsey offer in his back pocket. Instead, he and his two co-founders went all in on legal AI and built @WeAreLegora (YC W24) into one of the fastest-growing enterprise companies in history. In just 18 months, Legora surpassed $100M in ARR.
Today, the company is one of Europe’s most valuable AI startups, recently valued at $5.6B, with nearly 500 employees serving 1,000+ law firms and legal organizations across 50+ markets.
In this fireside with YC's @gustaf at our Stockholm event in April, @MaxJunestrand shares how Legora found its way into legal AI, why it moved so fast after YC, and how it convinced one of the world's most conservative industries to embrace a new way of working. He also digs into fundraising, competing in the age of foundation models, scaling a founder-led culture, and why Legora's ambition goes far beyond legal tech.
00:00 —Max Junestrand, CEO of Legora
03:11 — Starting Out: What Were You Thinking?
04:36 — Risk, McKinsey Offers & Taking the Leap
05:37 — Getting Into YC
07:06 — Arriving With Imposter Syndrome
09:59 — The YC Fundraise Grind
11:31 — Staying Confident Through the No's
12:00 — Building the Next Google From Europe
14:25 — Mini Games & the Product Manifesto
16:28 — $100M ARR, 500 People, Going Global
19:15 — M&A Agents Doing the Actual Work
20:41 — What If OpenAI Does This?
21:27 — Finding Your Moat as Models Get Smarter
Skill issues at big company means small new ones can eat their lunch
Paul Graham: If big companies can't make a net return on their LLM token costs, that doesn't mean it's impossible to. In fact this is exactly what you'd expect to happen with a new technology. Incumbents can't use it well, and are replaced by upstarts who can.
Dominic Pino
"Buy, borrow, die" is a neat theory for wealthy tax avoidance, but research shows that rich people don't actually use it.
@PostOpinions
https://www.washingtonpost.com/opinions/2026/06/05/ruben-gallego-tax-plan-is-premised-myth-buy-borrow-die/
himanshu: quite a piece of a release where they used ~ 20 models in different stages of training
- used 4 models from qwen family
- used 6 models from deepseek family
- used 2 models from minimax family
- used 4 models nvidia's stack
- used 2 models from glm famiy
- used gpt-oss-120B +
Yann LeCun
Re Political appointees vetting science funding?
Trump is doing to science what the Right accused previous administrations of doing.
But in previous administrations, there was no political control of research grant approvals.
Grant proposals were evaluated through peer review: the research community decided which proposals had merit.
Bye-bye Vannevar Bush, hello Trofim Lysenko.
Bye-bye meritocracy, hello political favoritism.
From The Guardian: "A set of sweeping policy changes unveiled by the White House would leave officials appointed by Donald Trump vetting every public grant issued to universities and nongovernmental organizations on the basis of their fidelity to “American values”, as defined by the president, triggering widespread concern."
Nikolay Savinov
Excited to share that I’ve joined OpenAI in London to work on pretraining!
I’ve spent the last few years on pretraining and long-context, and I’ll be helping grow the London team. We’re hiring exceptional researchers, please reach out: london-training-hiring@openai.com
Yann LeCun
Re Some billionaires (or their foundations) do fund certain areas of basic research.
Examples: Simons Foundation, Moore Foundation, Sloan Foundation, Keck Foundation, Schmidt Sciences, and several others.
But most of them are in biomedicine: Howard Hughes Medical Institute, Chan-Zuckerberg Initiative, Wellcome Trust, and many others.
However, this is all small compared with federal funding: around 25% of academic funding is from philanthropy, and over 50% from federal grants. This proportion is much lower in STEM than in biomedicine, and much lower in less prestigious universities.
So historical evidence that fundamental research can be helped, but not entirely funded, by philanthropic billionaires.
bored at the airport so i made this https://killedbygpt.com
Reminder.
JJ: Can we just make @ylecun president of AI and call it a day please?
Vercel is partnering with and integrating Shopify.
Starting with @v0, you can now prompt a Next.js + Shopify store in seconds.
The old tradeoff was “easy monolith” or “costly headless”. No more. Easy @nextjs Shopify storefronts with no scale or sophistication ceiling.
v0: You can now launch production-ready Shopify storefronts without leaving v0.
No setup needed, just install the integration and start prompting.
mark pincus
A junior partner at a top vc told me he was worried i wasnt coachable. I said, i dont see what you can teach me given youve never founded or run a successful company.
Ryan Petersen: During a pitch a prominent VC once told us the market size for global logistics was only $6B.
My CFO’s response: “So you’re saying it’s smaller than the market for USB cables?”
Shann³
spoke at a Hermes Agent event today about going from using a simple chat interface to building your own agent company
the thing everyone was interested in was second brains, company brains, and building the infrastructure your agents run on
I think this is one of the biggest moats in AI right now.
the moat is the data warehouse you build around yourself and your company.
a centralized place for the context, decisions, docs, workflows, preferences, source material, and operating knowledge your agents need to do useful work.
my current stack:
> Gbrain as the data warehouse
> quality gates before data gets ingested
> agents that can read from it and write back to it
> Hermes Agent as the harness layer
> Claude Code CLI, Codex CLI, and OpenRouter for execution and model routing
its tough to build, but the payoff is huge
you stop renting intelligence from tools that own the interface, the memory, and the workflow. and you start owning the system
Shann³: how I’m building an agent company inside my agency.
the structure looks like this:
Agency gBrain
→ Orchestrator Hermes Agent
→ Department verticals
→ Specialist agents
→ Scoped sub-agents
gBrain is the company brain.
It gets ingested with the data and experience we
Y Combinator
We're excited to announce Peter Steinberger as a speaker at Startup School 2026!
@steipete is the creator of OpenClaw, the open-source AI agent that went from a weekend project to the most-starred software repo on GitHub in under 5 months, with 346k+ stars. He's now at OpenAI building the next generation of personal AI agents.
https://ycombinator.com/startupschool
Nicolas Dessaigne
The new moat in the agent era is being the tool agents reach for.
A coding agent doesn’t reinvent a database. It wires up Supabase.
The best devtools companies will make themselves obvious to agents: easy to find, easy to reason about, easy to wire up.
Devtools are entering a golden age, but only for companies that realize they’re selling to agents now, not just humans.
Replit ⠕
Have you tried the new Replit Canvas?
- Create beautiful UI designs with AI
- Generate assets with GPT-Image 2 & Seedance
- Turn your designs into launch-ready apps in minutes
@Replit: Luca built Grid to centralize 12 different Google Drives into one hub.
With Replit, he turned a prompt into an AI-powered empl…
Just interviewed @mvanhorn and I'm so inspired.
I had no idea that he has no CS degree or real engineering background.
Despite that, he has shipped so many awesome projects and contributed to repos like Python and Go.
He does swear by @every's Compound Engineering for making good plans and shipping good code: https://github.com/everyinc/compound-engineering-plugin
📌 Will clean up the interview and share soon on my YouTube: https://www.youtube.com/@PeterYangYT?subscribe
Peter Yang
Just interviewed @mvanhorn and I'm so inspired.
I had no idea that he has no CS degree or real engineering background.
Despite that, he has shipped so many awesome projects and contributed to repos like Python and Go.
He does swear by @every's Compound Engineering for making good plans and shipping good code: https://github.com/everyinc/compound-engineering-plugin
📌 Will clean up the interview and share soon on my YouTube: https://www.youtube.com/@PeterYangYT?subscribe
luca. ∆ИƉЯƐΛ
Delighted to start sharing some of the incredible work that our AI Studio at @Replit has been working on. This is one of many platforms that we have created from scratch for our organization and one of many short series videos that we will be sharing.
I have the greatest job in the world and look forward to sharing more soon. Stay tuned.
Current state of the art silicon processes are optimized for maximum performance per wafer, but if the world is going to be wafer constrained, I wonder if designs could be changed to use fewer layers or otherwise modified to increase wafers-per-year at some cost of compute-per-wafer, netting out positive for compute-per-year.
Latent.Space
🆕 How to Stop Shipping Low-Quality RL Environments (with Examples)
https://latent.space/p/bad-envs
RL env startups are all the rage, but so many are TERRIBLE.
We're proud to feature our latest guest post from @aurielws, who has spent years in every layer of the stack at @GoogleDeepMind, eyeballing thousands of trajectories (👀 @HamelHusain @shreyash) and sitting through hundreds of "data pitches". Here's the biggest culprits you should know.
Y Combinator
Today we're launching Paxel: a free tool that analyzes your Claude, Codex, and Cursor coding sessions and gives you a profile of how you build with AI.
It runs locally inside Docker, and your code never leaves your machine.
Try it at http://paxel.ycombinator.com
Diana
a way to measure vibes
Y Combinator: Today we're launching Paxel: a free tool that analyzes your Claude, Codex, and Cursor coding sessions and gives you a profile of how you build with AI.
It runs locally inside Docker, and your code never leaves your machine.
Try it at http://paxel.ycombinator.com
Jitendra MALIK
I want to offer some unsolicited advice to computer vision researchers jumping into robotics. Don't focus too much on VLMs, VLAs etc. That's fine, but the real action is at the sensorimotor level. Most of the open problems in robotics are in manipulation, which is about hand-object interaction, and contacts and forces are central. Proprioception and tactile sensing are as important as vision. Don't get seduced by cherry-picked demos. You can't do robotics without doing robotics.
Rohit Mittal
This is an amazing idea by YC.
This is the type of innovation needed at the early stage to get the right founders through the door.
YC pioneered the 10 min interview and is still the only one to do it.
Now, with new innovations like these in attracting the right founders, they are going to stay far ahead of the curve.
Y Combinator: Today we're launching Paxel: a free tool that analyzes your Claude, Codex, and Cursor coding sessions and gives you a profile of how you build with AI.
It runs locally inside Docker, and your code never leaves your machine.
Try it at http://paxel.ycombinator.com
Agent filesystem state can now be read, written and mounted independently of Sandbox lifecycle.
We’ve been developing a novel virtual storage infrastructure solution for all our compute products.
Storage that’s decoupled, but attachable to Builds, Functions, Sandboxes & more.
Vercel Developers: Sandbox now supports drives in early access
▪︎ Storage separated from compute
▪︎ Mount on any path with 𝙳𝚛𝚒𝚟𝚎.𝚐𝚎𝚝𝙾𝚛𝙲𝚛𝚎𝚊𝚝𝚎
▪︎ Keep agent memories across sandboxes
Sign up ↓ https://vercel.com/changelog/drives-for-vercel-sandbox-in-private-beta
Sanket
Anyone who is not sure how Paxel works under the hood, here's a simplified diagram.
@ycombinator
Victor M
Before the week ends, let's acknowledge one of the most INSANE week ever for open AI, with 25+ notable open-weight drops across every modality:
🧠 LLMs
→ NVIDIA Nemotron 3 Ultra: 550B hybrid Mamba-MoE, only 55B active, 1M context, MMLU 89.1. NVFP4 variant claims ~5x throughput on Blackwell. First openly-weighted 550B hybrid Mamba-Transformer, closing the gap with frontier closed models.
→ Google Gemma 4 12B: fully open dense any-to-any (text/image/audio/video), 256k context, encoder-free, 140+ languages, AIME 2026 at 77.5. Shipped with a 23-checkpoint QAT wave (mobile ONNX + MLX). Most deployable model of the week.
→ StepFun Step-3.7-Flash: 198B sparse MoE VLM, ~11B active, SWE-Bench PRO 56.3. Apache 2.0.
→ Liquid AI LFM2.5-8B-A1B: edge MoE, just 1.5B active, 128k ctx, MATH500 88.8, MLX-ready. Best on-device option this week.
→ JetBrains Mellum2-12B-A2.5B-Thinking: their first open MoE, near-Qwen3-14B coding at 2.5B active. Apache 2.0.
🎨 Image gen (the surprise of the week)
→ Ideogram 4: their FIRST-EVER open weights. 9.3B flow-matching DiT trained from scratch. #2 overall behind GPT Image 2, top open-weight model on Design Arena + LMArena. Strongest open checkpoint for text-rich images, full stop. It has taste. Still can't believe this is open weights.
🔊 Audio & Speech (a breakout week for open TTS, 4 labs shipped)
→ Boson Higgs Audio v3 4B: 102 languages, 21 emotions, singing/whispering/shouting, sub-second TTFA.
→ RedNote dots.tts: the only fully continuous (no codec) open TTS pipeline, Apache 2.0.
→ Google Magenta RealTime 2: real-time music gen, <200ms latency, text+audio+MIDI. multimodalart ported it to PyTorch within hours with live ZeroGPU demos.
→ NVIDIA Nemotron-3.5 ASR: 600M streaming, 17x more concurrent streams vs Parakeet RNNT 1.1B.
👁️ Vision & VLMs
→ PaddleOCR-VL-1.6: SOTA document parsing at 1B params, Apache 2.0.
→ Baidu NAVA: 6.3B joint audio-video gen, best-in-class A/V sync, Apache 2.0.
🎬 Video, 3D & World Models
→ NVIDIA Cosmos3-Super: 64B omnimodal world model coupling action trajectories with video+audio gen, for Physical AI.
→ JD JoyAI-Echo: up to 5-min multi-shot text-to-video on LTX-2.3.
→ ByteDance Bernini-R + VAST TripoSplat (single-image-to-3D Gaussian splats, MIT).
Claude
We've doubled usage limits in Claude Cowork for the next month.
Delegate bigger, more complex tasks to Claude.
Jason ✨👾SaaStr.Ai✨ Lemkin
Who got the most leads at SaaStr AI Annual this year?
#1 @Replit
#2 @lightfld
#3 @aurasellai
#4 @salesforce
#5 @Rippling
#6 @OpenRouter
#7 @GoogleStartups
#8 @Vivun_Inc
#9 @Lovable
Two obvious themes: Building and Selling
Ankit Gupta
of note: in my group in YC this batch it's 40% hard tech. Going to be sick.
Jared Friedman: People are often surprised how many hard-tech companies YC funds, and for how long we've been doing it. It's been about 10% of the batch since 2014 when Sam became CEO.
i love being (for now) bdfl for aie because i can do cheeky shit like the AGI pills we did in london and also this
Philip Kiely: @swyx @aiDotEngineer Best event in the industry. Excited to see everyone there in 3 weeks!
x.com