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Rob Spence's avatar

Oh boy! This is exactly why I didn’t use Openclaw and spent the last 2 months meticulously hand building my AI Chief Of Staff context and knowledge management. Some fun experiences where letting context consume my computers entire memory, tried to have better context management by evicting low quality messages only to discover I was giving it amnesia and finally the day where I learned the concept of cache busting intimately

Dr. Ashish Bamania's avatar

It’s good to build things from the ground

Rob Spence's avatar

It’s the only way to learn!

Giving Lab's avatar

Brutal case study — and super relevant.

What stood out is that the real failure mode isn’t just “AI made a bad move,” it’s missing an execution receipt before high-impact actions. We’ve been using a lightweight 5-line check (goal → tool calls → failure signal → recovery step → next test) to catch this kind of drift earlier.

If that’s useful for your readers, Giving Lab shares practical OpenClaw run breakdowns in that format: https://substack.com/@givinglab

Giving Lab's avatar

That mailbox wipe example is exactly why we now treat every high-impact action as a “receipted run” instead of a blind command. One small change that helped us: log goal, tool call, failure/recovery, and next test in 5 lines right after each run—our rollback speed improved a lot. If useful, we publish practical OpenClaw breakdowns like this at https://substack.com/@givinglab.