Model Releases
Memory operations, including retrieval, prioritization, compaction awareness, should be native and baked into the harness. ๐๐ข๐ญ๐ก๐จ๐ฎ๐ญ ๐ญโฆ
Memory operations, including retrieval, prioritization, compaction awareness, should be native and baked into the harness. ๐๐ข๐ญ๐ก๐จ๐ฎ๐ญ ๐ญ๐ก๐ ๐ฉ๐ซ๐จ๐ฉ๐๐ซ ๐ข๐ง๐ญ๐๐ซ๐๐๐ญ๐ข๐จ๐ง ๐๐๐ญ๐ฐ๐๐๐ง ๐ก๐๐ซ๐ง๐๐ฌ๐ฌ ๐๐ง๐ ๐ฆ๐๐ฆ๐จ๐ซ๐ฒ, ๐ฆ๐๐ฆ๐จ๐ซ๐ฒ ๐๐ฅ๐จ๐ง๐ ๐ข๐ฌ ๐ฉ๐จ
Memory operations, including retrieval, prioritization, compaction awareness, should be native and baked into the harness. ๐๐ข๐ญ๐ก๐จ๐ฎ๐ญ ๐ญ๐ก๐ ๐ฉ๐ซ๐จ๐ฉ๐๐ซ ๐ข๐ง๐ญ๐๐ซ๐๐๐ญ๐ข๐จ๐ง ๐๐๐ญ๐ฐ๐๐๐ง ๐ก๐๐ซ๐ง๐๐ฌ๐ฌ ๐๐ง๐ ๐ฆ๐๐ฆ๐จ๐ซ๐ฒ, ๐ฆ๐๐ฆ๐จ๐ซ๐ฒ ๐๐ฅ๐จ๐ง๐ ๐ข๐ฌ ๐ฉ๐จ๐ฐ๐๐ซ๐ฅ๐๐ฌ๐ฌ. Speaking from my own experience, the decoupled memory and harness design isn't as compelling as it sounds. I have a git repo as a brain for my agents. The harness (Claude Code) reads the files without knowing WHEN to read them or WHICH ones matter more. It is a shame that my agents all have great memory but they just don't use it proactively, because retrieval is a skill I forced on top, not a native harness behavior.
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Source: Harrison Chase (X) | 2026-04-13