https://video.ut0pia.org/videos/watch/c59724ac-603f-4fa7-803d-7cc9ddaebe01 A rage click, a 2am error spike, a customer Slack message — today each sits until a developer notices, triages, tickets, and writes a fix. PostHog is building a pipeline that collapses that chain: signal arrives, a background agent groups it with related errors and session replays, researches the codebase, and opens a PR. You wake up to green PRs instead of dashboards. Three lessons from building it: off the shelf embedding models cluster signals by structural similarity rather than meaning, so errors land next to errors and Slack messages land next to Slack messages — the fix is to embed LLM generated queries rather than the signals themselves. Specificity determines whether the agent produces a useful PR or just fixes something at random; error tracking is immediately actionable, Slack and session replay usually are not. And start with agents even when it looks expensive — run the same problem through an agent 100 times, find the patterns, then collapse the expensive step into a one shot call. Speaker info: https://x.com/joshsny -https://www.linkedin.com/in/joshsny/ Wed, 10 Jun 2026 21:17:41 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/c59724ac-603f-4fa7-803d-7cc9ddaebe01 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.