AI OperationsComing
LLMOps & Production Operations
LLMOps is the operational discipline of running language-model systems in production — the layer between a working prototype and a service real users depend on. It covers observability and tracing for non-deterministic systems, evaluation pipelines that run in CI so a prompt change cannot silently regress, cost and latency management, prompt and model version control, and safe rollout strategies (canaries, fallbacks, and rate limits). As organisations move from one-off demos to fleets of agents, the people who can keep those systems reliable, cheap, and observable become the difference between a pilot and a product.
What you'll learn
- Instrument a non-deterministic LLM system with tracing and observability so you can actually debug a bad answer in production
- Build CI evaluation pipelines (regression suites, LLM-as-judge, golden sets) that gate every prompt and model change
- Manage cost and latency at scale — caching, model routing, batching, and rate limiting — without degrading quality
- Operate safe rollouts: prompt/model versioning, canary releases, fallbacks, and incident response for AI systems
Want something you can start today? The catalog lists every track that is open right now.
Explore the catalog