I have been experimenting with hands off keyboard agent-driven implementations of non trivial tasks, and I'm finding that the same pattern you're outlining prov

I have been experimenting with hands off keyboard agent-driven implementations of non trivial tasks, and I'm finding that the same pattern you're outlining proves to be very useful: Explore, summarize, plan, handoff. That info distillation loop seems to be quite effective at keeping agents on task. I've been considering adding memories between agents, but haven't thought of a good data model yet. The problem with something like memories is I've observed that when context gets polluted agents get confused. Especially these distilled models like minimax and kimi. So the challenge is ensuring that only "relevant" memories are pulled into context for a given task.