We're a distributed team of applied AI engineers, split across two locations, and every one of us leads a project while working on several more. Multi-threaded is our normal, not a bad week - and the ground moves hourly: repositories change, business facts change, and on a single repo two engineers will run experiments and close tasks before lunch. At that speed the hard part is no longer writing the qoek - AI does plenty of that. It's that context goes stale in hours. The moment a person, or more dangerously their AI agent, starts from an out-of-date picture of the world, it confidently builds something that duplicates or contradicts what a teammate just shipped. Speed stops compounding and starts colliding. So the real job became herding context: keeping every engineer and their mutiple agents aligned on the same facts and the same rules at any given moment. We had to make that alignment automatic. This talk is about why that quietly became our bottleneck and what we built to solve it.
Sr. Manager - Applied AI, Echostart. AI Leader. LLM researcher. Inventor on 19+ AIML Patents & Applications.
