Sharing this since it might be relevant to a few people here. There’s a hands-on workshop on September 26 that goes beyond building agents into keeping them reliable once they’re writing into real systems. You work through a deliberately flawed agent platform, redesign its write path for conflicts, retries, and idempotency, fix state and memory management for long running sessions, and build in provenance and tracing so decisions can be reconstructed after deployment. Everything runs on a realistic production style case study, not a toy example, and it ends with a capstone where you review an unfamiliar platform’s readiness yourself. No prior production infra experience needed. Led by Sandipan Bhaumik, Data & AI Technical Lead at Databricks, 18+ years in data engineering and governance. Link if you want to check it out submitted by /u/camerongreen95
Originally posted by u/camerongreen95 on r/ArtificialInteligence