https://video.ut0pia.org/videos/watch/ca8bcace-ffdf-476d-a7a3-56a9ff20ab12 AI agents are rapidly evolving from copilots into autonomous systems capable of reasoning, invoking tools, coordinating workflows, and interacting with production infrastructure. But most platforms today were designed for deterministic microservices — not long-running, non-deterministic systems powered by LLMs. This creates a massive infrastructure gap. In this talk, I’ll share lessons from building large-scale agentic and elastic compute infrastructure powering production AI workloads. We’ll explore the emerging “control plane” required for reliable AI agents: orchestration, observability, retries, evaluation, safety guardrails, workload isolation, memory coordination, and operational control loops. Topics include: Why most AI agents fail outside demos, Building deterministic systems around stochastic models, Observability for autonomous AI workflows, Failure handling and retry storms in agent systems, Human oversight and safety guardrails, Elastic GPU infrastructure for agentic workloads, Reliability patterns for production AI systems, The shift from “prompt engineering” to “systems engineering”, Attendees will leave with practical architectural patterns for building resilient AI infrastructure capable of supporting autonomous systems safely and efficiently in production. Speakers: Nishant Gupta (Meta Superintelligence Labs): Nishant Gupta is a Software Engineering Tech Lead at Meta Superintelligence Labs building the training and inference AI infrastructure. LinkedIn: https://www.linkedin.com/in/nishantgupta-ai/ GitHub: https://github.com/nishantgpt-lab Mon, 29 Jun 2026 15:52:27 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/ca8bcace-ffdf-476d-a7a3-56a9ff20ab12 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.