A dark, dotted background diagram showing a simple agent workflow loop. At the top center is a cylindrical shape labeled “queue”. A curved arrow goes from the right side of the diagram into the queue, labeled “enqueue”. From the bottom of the queue, a downward arrow labeled “pop” leads to a rectangular box labeled “agent loop”. From the agent loop, two paths branch downward. On the left, a downward arrow labeled “do work” leads to a rectangular box labeled “environment”. On the right, a diagonal arrow labeled “another project” leads to a large rectangular box labeled: “tool: enqueue_work(desc: str)” From this tool box, a curved arrow loops back upward and connects back into the “queue” at the top, completing the cycle. The overall structure depicts an agent loop that pops tasks from a queue, does work in an environment, or enqueues additional work back into the queue via a tool call.
UPDATE: It appears i wasn't clear about what i did
1. CRON is inefficient
2. RLM (Recursive Language Models) are extraordinarily powerful
3. Every recursive algo can be implemented as a queue
4. I gave the agent a queue
alexzhang13.github.io/blog/2025/rlm/
![Sully [Testing]](https://cdn.bsky.app/img/avatar/plain/did:plc:3snjcwcx3sn53erpobuhrfx4/bafkreidef5zmhpnnypaht37kpmihxs64bdnecbwip3na637wnanxv7mneu@jpeg)
