When I'm optimizing some part of a codebase, I end up in the same loop. Try a thing. Benchmark. Keep what helps. Discard what doesn't. Repeat until the result is good enough, or until I get bored.
It works but it also eats half a day or more and ties up my attention while it runs.
AI doesn't get bored.
v0.11.0 ships the loop. Give Shaka an objective and it spawns an isolated git worktree, hands your terminal to your provider's TUI so a setup agent prepares everything with you watching, then runs the loop in the worktree until you stop it. Each accepted iteration commits, so the log is the record.
Inspired by Karpathy's autoresearch and davebcn87's pi extension.
`shaka optimize start "<your objective>"`
v0.11.0
🤖 github.com/jgmontoya/shaka
It works but it also eats half a day or more and ties up my attention while it runs.
AI doesn't get bored.
v0.11.0 ships the loop. Give Shaka an objective and it spawns an isolated git worktree, hands your terminal to your provider's TUI so a setup agent prepares everything with you watching, then runs the loop in the worktree until you stop it. Each accepted iteration commits, so the log is the record.
Inspired by Karpathy's autoresearch and davebcn87's pi extension.
`shaka optimize start "<your objective>"`
v0.11.0
🤖 github.com/jgmontoya/shaka
274❤️4🖤1🧡1
