holy sh*t. Karpathy's second brain pattern runs on Grok Bot now: stop explaining your life to AI from zero every chat, keep a wiki that writes itself three bots in one group chat, each with its own memory: the reader takes every link, PDF and voice note you drop and never edits it the librarian rewrites every wiki page that source touches, usually 10 to 15 of them the checker wakes up on a nightly routine and hunts contradictions, stale claims and pages nothing links to → you ask a question: the answer gets filed back as a page, so the brain grows from use, not only from reading → a new source contradicts an old page: the checker tags you instead of quietly overwriting it → a page goes 30 days without a fresh source: it gets marked unconfirmed a second brain can sound sure while remembering the wrong thing Reader collects. Librarian writes. Checker doubts. every page has to show: > the claim > the source it came from > the date it was last confirmed paste this into Grok Bot: "Build me a second brain with three bots in one group chat. Keep my sources untouched in raw/, maintain wiki/ yourself, file good answers back as pages and run a nightly check for contradictions. Show me the structure first. Do not create anything until I confirm" start with one topic you actually work on, not your whole life full setup below

1/ SQLite is fast. Until everyone writes at once. Turso 0.8.0 is out: the performance release. Under concurrent writes, up to 500x lower tail latency and 7x higher write throughput than SQLite. 🧵

The "whiteboard defense:" I should be able to pull you aside at any moment and ask you to explain any customer-facing system you've shipped. You should be able to clearly explain how it works and defend the decisions you made. This is my benchmark for responsible AI usage. I don't expect line-level familiarity with the code. I don't care if you remember the exact function name or implementation detail. You may not even know it. I don't care. But if I ask "why did you do X instead of Y?", "what happens if this actor behaves maliciously?", "what data structure did you use here and why?", or "where does this fail?" you should be able to answer confidently. For PoCs, demos, experiments, whatever: I don't care. Generate 100% of it and understand none of it. Speed over quality every time in those specific scenarios. But if you're shipping customer-facing work, you can't be shipping things you don't understand at a high level.

DuckLake: The Lakehouse That's Just SQL & Parquet [Talk Python to Me, Ep. 562] How many files does your query read before it reads any data? On some data lakes, you go through JSON and metadata files first, just to learn which Parquet files matter. #DuckLake asks one SQL question instead. The metadata lives in a real database. The data stays in plain Parquet. That's the entire format. With Quack as the catalog, DuckLake handles 200 transactions a second under heavy contention. No other open table format comes close. In this episode of @TalkPython, host @mkennedy talks with @holanda_pe, lead developer for DuckLake at DuckLabs, and Guillermo Sanchez Dionis, who works on both DuckLake and the new Quack protocol – together they discuss all the details of DuckLake, Quack, and more. Watch the episode here or listen wherever you get your podcasts: duckdb.org/library/ducklake-…

this is how I picture it in my head 😅😅😅 xitter.cf/ClementDelangue/status…

🚀 Introducing Gemini-SQL2, our breakthrough text-to-SQL capability powered by Gemini 3.1 Pro! We've achieved state-of-the-art results on the highly competitive BIRD benchmark, translating natural language into execution-ready SQL queries. 🧵👇