LLMOps — Large Language Model Operations
Definition: The operational discipline of deploying, monitoring, and improving LLMs in production — prompts, evals, guardrails, costs, and drift. MLOps for the LLM era, where the model is rented and the moat is the workflow around it.
Example
Without LLMOps, every prompt change was a coin flip — once we added evals and cost tracking, shipping model updates stopped being a Friday-night gamble.
When you'll hear it
LLMOps shows up most often in AI strategy reviews, model evaluation discussions, and product roadmap meetings. When someone uses it, they're usually referring to large language model operations — and they expect the room to already know what that means.
FAQs
What does LLMOps stand for?
LLMOps stands for Large Language Model Operations.
What does LLMOps mean in AI and machine-learning?
The operational discipline of deploying, monitoring, and improving LLMs in production — prompts, evals, guardrails, costs, and drift. MLOps for the LLM era, where the model is rented and the moat is the workflow around it.
Where will I hear LLMOps used at work?
LLMOps comes up most often in AI strategy reviews, model evaluation discussions, and product roadmap meetings. It's used as shorthand for large language model operations, so people assume you already know the term.