For the moment, researching multi-agent orchestration. At first glance, your work looks among the best in class of published work I've seen. Particularly interested to understand the memory/communication/search model you're using, as it sounds like you've trying to think well past the GasTown/Beads/Claude-Code-Swarms concepts.
Very kind of you to say. Our whole vision is that agents can produce way better results, compounding their intelligence, when they lean on shared memory.
I'm curious to see how it feels for you when you run it. I'm happy to help however I can.
I'm using "RAM" loosely, meaning working memory here. In practice, it's a key-value store with pub/sub stored on our shared memory layer, Ensue. Agents write structured state to keys like proofs/{id}/goals/{goal_id}, others subscribe via SSE. Also has embedding-based semantic search, so agents can find tactics from similar past goals.
