The harness is 561k LOC, which is much larger than anticipated.
It seems to show how systems can be built on top of raw LLMs after studying their characteristics.
- Prunes context windows.
- Uses “dreaming” to clean up long-term context.
- KAIROS prunes after 24 hours of inactivity.
- Is not simply a query-response architecture.
- It is a loop designed around context-window management.
- Before the LLM gets any input, a meta-prompt is injected into a state machine.