https://video.ut0pia.org/videos/watch/62f05102-657e-46d5-a32a-f317140ed84b The biggest gap in production AI agent systems is not the model—it's the harness. After 1,000 hours of orchestrating autonomous fleets under human direction, the pattern is unmistakable: agents that finish complex tasks on the first run routinely fail on subsequent iterations because the surrounding loop lacks persistent memory and contextual guardrails. In this talk, I dissects the key multi-agent primitives required to turn raw models into deterministic teammates. Moving beyond simple API wrappers, we explore how separating your stack into distinct "Agent Orchestrator Managers" and specialized workers prevents low-level implementation bias. Using concrete examples from production systems, we will walk through real-time terminal routing via CMUX, analyze the token-burn tradeoffs between leading models, and look under the hood of high-context consumer applications like WorldAI and Consensus ML. You will walk away with a practical architectural checklist you can drop directly into your own agent infrastructure on Monday morning. Once you're setup you can truly develop at idea velocity ie. natural language to code to automated iteration to evidence produced to human review where human interaction in the middle is pushed to the beginning or end allowing improved parallelization. Speakers: Jeffrey Lee-Chan (Snapchat): Most teams use AI tools wrong — humans still on the critical path. I build parallel multi-agent harnesses so one engineer directs 10–20 coding agents instead of becoming the rate limiter. X/Twitter: https://x.com/jleechan2015 LinkedIn: https://www.linkedin.com/in/jeffrey-lee-chan/ GitHub: https://github.com/jleechanorg Sun, 12 Jul 2026 17:18:28 GMT https://validator.w3.org/feed/docs/rss2.html PeerTube - https://video.ut0pia.org https://video.ut0pia.org/lazy-static/avatars/0287a09a-aae7-4840-9843-b416426e7046.webp https://video.ut0pia.org/videos/watch/62f05102-657e-46d5-a32a-f317140ed84b All rights reserved, unless otherwise specified in the terms specified at https://video.ut0pia.org/about and potential licenses granted by each content's rightholder.