miniblog.

I've been impressed with code written by Fable in my testing: Difftastic: found small optimisations in a hot loop I'd already profiled extensively. Helped me prototype Dijkstra to A* too (hard to find a good heuristic). Garden: Found some real bugs in my simplistic typechecker.

LLVM's lit tool for testing files is the most successful testing DSL I've ever seen. It's used a decent number of projects outside of LLVM. By contrast I don't see many folks using e.g. Cucumber these days.

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.