https://video.ut0pia.org/videos/watch/db3c8029-580d-41e8-909f-b4059f6a3a77 I deployed an agent to production and the bill was not good. Not because the model was bad, but because it was doing too much. I was using the most expensive models for simple inference calls. The context was filling up. And my tool loops ran longer than they needed to. The agent worked fine, it just cost way more than it should have. This talk covers three small changes I made that dropped my costs without hurting quality. Each one was a few lines of code, and none of them required changing my prompts or switching models. I'll cover things like prompt caching and model routing. I'll show code. Speakers: Erik Hanchett (Amazon Web Services): Erik Hanchett is a Developer Advocate at AWS who helps developers build with frontend, fullstack, and AI/agent technologies through hands-on tutorials, talks, and videos. X/Twitter: https://x.com/erikch LinkedIn: https://www.linkedin.com/in/erikhanchett/ GitHub: https://github.com/erikch Mon, 29 Jun 2026 16:01:13 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/db3c8029-580d-41e8-909f-b4059f6a3a77 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.