billion-context: agent plugin compresses context for month-long sessions
The interesting move is giving the model agency over its own memory: compression happens only when the model judges old turns are disposable, which reduces the accuracy loss typical of aggressive auto-summarisation. Developers building long-horizon agents or coding assistants that run for weeks on 100K-token models can drop it in as a proxy layer rather than rewriting prompts. The GitHub release makes it directly testable against naive summarisation baselines.
