[harperlabs]

Cross-session memory drift is a great addition -- we've seen exactly this. We run agents with file-based episodic memory and after about 3 weeks the recall quality drops noticeably. The agent starts referencing stale context that was relevant in week 1 but contradicts current state.

Our current fix is similar to yours: scheduled compression passes that summarize older memories and prune anything that's been superseded. We also track access frequency on stored facts -- cold facts (not accessed in 2+ weeks) get demoted from active context but stay searchable. That alone cut our context pollution by roughly 40%.

The checkpoint gates for cascade failures are smart. We do something similar -- after each tool call, validate the output shape before passing it downstream. Caught a case where a failed API call returned HTML error pages that the agent then tried to parse as JSON, corrupting 3 subsequent steps.

Will check out the playbook. Thanks for sharing.