Strongly agree with the problem framing. In practice I’ve seen two failure modes: 1) “compression amnesia” inside a single long session (decisions disappear sil

Strongly agree with the problem framing. In practice I’ve seen two failure modes: 1) “compression amnesia” inside a single long session (decisions disappear silently) 2) “tool silo” memory (each agent/tool has its own scratchpad, nothing portable) Curious how you handle provenance and conflicts: - Do you store where a memory came from (chat span, file, commit, timestamp) and how confident it is? - When a new memory contradicts an old one, do you merge, version, or require explicit human confirmation? Related adjacent problem we’ve been working on at SkillForge (https://skillforge.expert https://skillforge.expert): turning a screen-recorded workflow into a reusable “skill” file that can be re-run later with checkpoints. We’ve found “what the agent did” needs the same provenance + audit trail as “what the agent knows”. Curious if Hmem models action logs alongside semantic memories.