https://video.ut0pia.org/videos/watch/9e0fe57d-2fe2-48c9-b40b-a2e51e3dbcee Same prompt. Same agent. Same model. Without a context engine: 2.5 hours, 20.9 million tokens, multiple rounds of human correction, and code that compiled but would have broken the entire system if it shipped. With one: 25 minutes, 10.8 million tokens, and a senior engineer who gave one nitpick and approved the merge. Brandon Walsenuk from Unblocked makes the case that the problem is not access but understanding. More MCPs give agents pipes to information. A million token context window just sits there. Naive RAG stops at the first result it finds, a phenomenon called satisfaction of search borrowed from radiology. What actually changes is a context engine that reasons across your codebase, Slack history, PR patterns, and org structure to build a research packet before the agent starts writing, so it arrives knowing your factory patterns, your fallback infrastructure, and what the CTO said was wrong in that thread three months ago. Tue, 26 May 2026 16:04:51 GMT https://validator.w3.org/feed/docs/rss2.html PeerTube - https://peerate.fr https://peerate.fr/lazy-static/avatars/d7b83a50-fe89-4e9f-8234-2a5bb1c39ab5.jpg https://video.ut0pia.org/videos/watch/9e0fe57d-2fe2-48c9-b40b-a2e51e3dbcee All rights reserved, unless otherwise specified in the terms specified at https://peerate.fr/about and potential licenses granted by each content's rightholder.