Fitting the OODA Loop to AI Agents: A Practical Framework for Iterative Optimization
DanielLockyer · x · 2026-11-04
Daniel Lockyer shares the framework he relies on for grinding down system performance: the OODA loop — Observe the current state, Orient on what's broken or slow, Decide what to do, Action the changes, then loop. He quotes Nate Berkopec's agent-oriented variant: define what you're building, inventory the approvals/permissions/secrets you need, write down your definition of done, run /goal to execute until done, then /retro to figure out what can be automated.
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