https://video.ut0pia.org/videos/watch/566ad9c2-8daf-458f-80c5-549f71998f8d Cloud ETL failures often require engineers to manually inspect logs, diagnose schema or data-quality issues, select a repair, rerun the job, and validate recovery. This talk presents an RL-guided pipeline health agent that automates this workflow through deterministic anomaly detection, interpretable Q-learning, bounded remediation actions, and an external safety layer. The system detects schema drift, null-rate spikes, type changes, and runtime failures, then selects actions such as retry, schema coercion, rollback, quarantine, or escalation. Evaluation across 30 controlled synthetic runs demonstrates minutes-scale recovery for successfully resolved cases while highlighting the importance of deterministic rules and safety guardrails. Speakers: Anna Marie Benzon: Anna Marie Benzon is a World Economic Forum–recognized technology leader, startup founder, and PhD researcher in AI with 9+ years of experience building AI-powered products and scaling multidisciplinary teams. LinkedIn: https://www.linkedin.com/in/anna-marie-benzon GitHub: https://github.com/ambenzon27 Mon, 29 Jun 2026 15:58:03 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/566ad9c2-8daf-458f-80c5-549f71998f8d 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.