Rube is a universal MCP server that connects large language models to 500+ apps and manages massive context seamlessly. But the real story isn’t just what Rube does — it’s what we learned while building it. This talk dives into the engineering challenges behind production-ready multi-agent systems: managing large contexts efficiently, designing reliable tool schemas, routing user requests across hundreds of integrations, adding memory without bloating state, optimizing execution speed, and getting LLMs to “call the right tool at the right time.”

Through successes, failures, and plenty of debugging scars, you’ll learn practical strategies for building intelligent, scalable systems that push beyond toy demos. If you’re experimenting with MCP, LLM apps, or multi-agent orchestration, these lessons from the trenches will save you weeks of trial-and-error — and maybe inspire a new direction for your own projects.