@himanshutwtxs: loop engineering only holds up if the loop can remember. here's the part that decides it: -> the context window resets …
Summary
Explains that effective loop engineering for AI agents requires an external durable store to persist memory across iterations, preventing context rot and enabling agent learning over thousands of runs.
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Cached at: 06/18/26, 04:19 PM
loop engineering only holds up if the loop can remember. here’s the part that decides it:
-> the context window resets to a fixed set of files every iteration, so the in-window memory is disposable
-> what has to survive lives outside the window: lean anchor files (VISION, PROMPT, MEMORY, SKILL.md) reset each pass, and a durable external store that persists across all of them
-> the loop recalls from the store before each pass and writes the outcome after, so run 47 reads what runs 1 through 46 learned
-> skip the store and it drifts, repeats finished work, and re-ingests its own early mistakes as truth. context rot hits around 20-30 turns and a loop runs thousands
the loop gives an agent persistence across time, memory is what keeps it from forgetting
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