auxten

As I've mentioned in many of my @chdb_io related talks, turning an embedded database into a distributed database is undeniably a very difficult process. Conversely, taking a distributed database engine and refactoring it into a similarly production-ready embedded database is relatively much easier.

No GIL, Real Gains: Porting a C++ Python Extension to Free-Threaded Python 3.14 @PyData Amsterdam 2026 youtu.be/soBWS_SlqJc?si…

Can someone tell me how I'm supposed to use the $250 cloud environment credit that Claude Code gives you?

Most of my projects are developed locally. I've got a lot of set-up debugging environments locally, along with various environment variables, keys, emulators, and large test data that can't be committed to Git (like a bunch of parquet files). I really can't figure out how to make use of those $250 tokens.

How is everyone else using them? Any inspiration or ideas would be appreciated.

My Claude Code session hasn't written code in weeks. It's a director: every task goes to a local CLI worker in tmux, tracked by an on-disk ledger.

New: who gets the task and at what effort is decided by @typesafeai Jev — a decision model, not an LLM. 6 typed answers, ~1s.

Tomorrow at the AI Native Workplace Summit, I'll be sharing how we use AI for @chdb_io day-to-day tasks and development work.