My RLM agent can effortlessly process ~80k lines of service logs from CloudWatch
in a single go. that's worth like 8 million tokens.
The cool part is, after 53 steps, it had spent only 32k "active" tokens* (not through the full 8MM yet atp, more like half).
That's nothing for Claude Fable 5 (rip), and weeell within effective context window, so its very "context-efficient".
It can go VERY far and I dont even have to handhold it or anything, i'm not worrying about context running out or compactions either.
I'm saying I kicked this thing off, almost without any context, and it was able to infer the service architecture based on logs alone, and spot issues my team didn't.
In this particular case it was able to narrow down on a specific slice and find a couple issues that flew under the team's radar (AgentCore's throttles, Slack's usernotfound)
Very handy.
I'll release this as OSS soon (my first release on llm tooling!)