seb
188 posts

seb
@sebmichaelsep
llm inference @perplexity_ai https://t.co/lbqxf87Ugz

We’re launching @JudgmentLabs today and announcing $32M in funding. As AI agents take on more of the work that creates economic value, they generate massive amounts of production data: the clearest record of how they behave with users, software, and the real world. Judgment builds infrastructure for improving AI agents from production data.


In Rust, how the borrow-checker shapes your API inputs and outputs ..
The general design principle is to choose signatures that minimize ownership churn while keeping call sites clean and safe.
Accepting input
• Borrow when you only read: `fn parse(src: &str)`
• Borrow mutably when you mutate in place: `fn fill(buf: &mut [u8])`
• Own when you need to keep it: `fn spawn(task: String)`
• Generic borrow (most ergonomic at call sites): `impl AsRef

🔥 Today we’re excited to announce new funding for `grep` (at a $1.3B valuation) to continue building the foundation of agent observability and text search infrastructure. grep began as a humble UNIX utility in 1973. Since then, it’s evolved—through recursive innovation and the rise of ripgrep—into a core platform for developers, sysadmins, and agents. Our tools now power engineering and AI teams across @OpenAI, @Anthropic, @Meta, @Cloudflare, @Replit, @NASA, and thousands more. Over the decades we’ve iterated from grep to `egrep` to `ripgrep`. Our goal has always been to figure out what intelligent agents of the future need to see, filter, and extract—and then build the tools that make that possible. While our journey is still just beginning, we also want to take a moment to reflect on how the space (and our role in it) has evolved. You can read our reflections and details on this funding milestone here: gnu.org/software/grep/… We also share more about the funding that will power our future there. Thank you to @IVP, @Benchmark, @Sequoia, @CapitalG, and the open-source community for their belief in the enduring power of regex. What excites us most today is what’s next: grep 5.0 with AI-assisted pattern synthesis ripgrep Cloud, bringing distributed search to agent clusters pgrepGPT, an agent-native process discovery layer And new no-code integrations for autonomous observability pipelines We’re in the midst of a transformation in computation itself. grep and ripgrep will remain at the core—helping humans and agents alike find what matters, faster.






recently i started telling candidates right in the first interview that greptile offers no work-life-balance, typical workdays start at 9am and end at 11pm, often later, and we work saturdays, sometimes also sundays. i emphasize the environment is high stress, and there is no tolerance for poor work. it felt wrong to do this at first but i’m convinced now that the transparency is good, and i’d much rather people know this from the get go rather than find out on their first day. curious if other people do this and if there’s some obvious pitfall i’m missing.

dia is the exact opposite of how an ai product should be built. the ai should feel like magic to use and deeply integrated into every aspect of the product. dia’s ai feels like a cheap after thought, tacked on to the search and side bar because the vcs asked them to.











