Most AI workflows optimize for output.
This optimizes for how you think before, during, and after a session:
β focus brief injected at session start (what problem, what I believe, what's undecided, 30-day goal)
β thinking nudge detects bare questions and prompts you to state your position first
β blind spot analysis surfaces unchallenged assumptions before session ends
β weekly reflection pulls your session history to ask "what pattern keeps recurring?"
β 3 context modes: thinking-partner, implementation, review each phase maps to a hook event - orient (SessionStart), think (UserPromptSubmit), challenge (Stop), reflect (CLI). fully composable.
Also: LACP is now public + installable via homebrew.
brew tap 0xNyk/lacp && brew install lacp
github.com/0xNyk/lacp/relβ¦
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