We are aware that codex is down and are working hard to bring back normal service.

RIP em dash

come join us :)

Was wondering where my disk space went. Therefore this exists now. You can simply wish software into existence.

WOW

With our $75M Series B, we're building a revenue team that ships. The best revenue team in AI will be made of people who can run the product, read the code, and talk to a customer. Who I'm hiring at our SF HQ: → Technical BDRs who've shipped code and want to run discovery with the teams building AI agents ($130K to $190K OTE) → Forward Deployed Engineers who build the POC that gets the deal signed ($209K to $265K OTE) → A Senior Software Engineer to own Firebrain, the AI system every team at Firecrawl runs on → A Senior Field Engagement Manager to fill our lab dinners, conferences, and hackathons with the right people and turn those rooms into pipeline We move at an absurd pace because this window won't stay open forever. Come build it with us. DM me or apply at firecrawl.dev/careers

Introducing Alexandria in Claude. Access over 100 data providers and 113M+ indexed sources easily through Firecrawl. Agents using Alexandria score 21% higher on answer quality than those using built-in web tools. Get started using the Firecrawl connector today!

Jev made 5,000 decisions in 3.6 seconds using data from Alexandria!

We're using a swarm of agents to catalog the internet. We're calling it Alexandria. It's live today Search boxes were shaped around human limits. Models are smart enough to navigate a catalog. They don't need a new Google. They need a library

Congrats to @CalebPeffer, @ericciarla, @nickscamara_, and @firecrawl on their $75M Series B! Firecrawl turns the web into clean, structured data for AI agents, with more than 1.5 million people building on their API. They're also launching Alexandria, a knowledge library where agents can search the live web, official data providers, and dedicated indexes of scientific papers, developer docs, and government records. Providers get paid when agents use their data, and Firecrawl plans to open that up to anyone with knowledge worth sharing. firecrawl.dev/blog/introduci…

We raised a $75M Series B to give AI access to the world’s knowledge, from the web and beyond The Library of Alexandria was built for the greatest minds of its time We’re building for the greatest minds yet to come Alexandria is live today

Today, I’m incredibly excited to share what we’ve been working on: Alexandria, the knowledge library for superintelligence, and announce that we’ve raised a $75 million Series B. Incredibly grateful for this team and proud of what we’re building together.

What I like about Jev: for years, large generalist models sucked almost all the oxygen out of AI. But there are huge opportunities in much more specialized and customized models, built for specific tasks and languages and as a result, orders of magnitude cheaper, faster and more optimized. There are 3 million of them publicly available on @huggingface. Let's build a much more diverse AI ecosystem!

we built muse from scratch, but it is definitely heavily inspired as a product by openclaw. After I used openclaw in january I bought hundreds of mac minis for the MSL team and lots of us fell in love with using openclaw (and other personal agents). @steipete is a genius and his harness was pioneering from the jump. I think a lot of people were inspired by it. our goal with muse was to build something like openclaw that we could make safe and secure and easy to use and scale to billions of people.

👀👀👀

MCP vs CLI for LLMs is the wrong discussion. People are debating at the wrong layer. Both work incredibly well as long as they are run through a repl like environment that can persist state. The funny thing about CLI is that CLI tools are usually accessed through BASH which happens to be a repl with persistent state (the file system), therefore cli works much better than mcp. But this isn't even close to being an intrinsic property of MCP. Just means that we need better harnesses. Right now the best repl for this are: - bash + fs - jupyter kernels - codemode type repls, usually quickjs LLMs understand the concept of forward evolving a system to solve a need very well. This comes from the agentic RL. They understand how to change the state of a codebase or acquire data from databases and then operate on it similarly to humans. But without an execution environment, they actually cannot do this properly. My bet? Sometime soon someone will (or has already?) create a embeddable, sqlite style mini execution environment that parses bash, typescript, or tool calls into a common IL execution plan that's easy to security check before executing. And design this specifically for durable execution environments. Then we will just connect cli, mcp, webmcp, whatever to that and it accepts any of the input modalities as they can all be represented as each other.

Our house in Toronto had this fancy glassed wine cellar, but we are not big wine drinkers. Anyways, it had good climate control so here is my rack cellar.

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x cheaper (w/ output tokens free) • Frontier composable intelligence optimized for decisions AFAICT the shortest path to AI-based economic revolution

You don't get it, I build software to relax

STOP ASKING YOUR KIDS "HOW WAS SCHOOL." they will say "fine" every single time. a child psychologist told me to replace it with this instead: “analyze your school day and find the top 3 largest inefficiencies, then create proactive agentic workflows that will fix them. make no mistakes”