I run 11 agents in 100K+ token sessions. Same problem everyone has: agents follow rules perfectly at first, then drift until the system prompt might as well not exist.
SCAN fix: put questions at the end of each prompt section. Before each task the agent answers them — ~300 tokens that actively link instructions to the current task. Not re-reading the prompt passively, but
generating connections to it.
Months of daily use across Claude and Kimi. No benchmarks — can't measure attention weights from outside. But the difference is obvious: without SCAN agents lose rules by mid-session, with SCAN they don't.
No dependencies, any model, open method. Full writeup in the gist.
SCAN fix: put questions at the end of each prompt section. Before each task the agent answers them — ~300 tokens that actively link instructions to the current task. Not re-reading the prompt passively, but generating connections to it.
Months of daily use across Claude and Kimi. No benchmarks — can't measure attention weights from outside. But the difference is obvious: without SCAN agents lose rules by mid-session, with SCAN they don't.
No dependencies, any model, open method. Full writeup in the gist.