miniblog.

One fun way of testing new AI models: take an existing codebase you have and just ask them to "review it and fix bugs". In principle this should find more issues over time as models get smarter. I've found a few bugs this way at least.

Cleaned up an old git repo of Ansible playbooks and it's amazing how much is just Docker now. Docker handles process supervision, centralises logging, and containers coexist without issues. It's nice when things get simpler.

Wonderful post from the lead LLVM maintainer reflecting on how the project is run, the design issues in LLVM today, and opportunities to make it better: