#Lifecycle

Articles about Lifecycle — exploring patterns, best practices, and real-world implementations in production systems.

1 post tagged with lifecycle. ← All posts

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Pratik Dhanave · ·5 min read

The LLMOps Lifecycle — The Loop an LLM App Lives In

Post 1 argued an LLM application is never "done." This post gives that idea a shape: the LLMOps lifecycle, the repeating loop of develop → evaluate → deploy → observe → improve that a production LLM system lives inside. Seeing the whole loop at once is what turns a pile of practices — prompt management, evals, guardrails, monitoring — into a coherent operating model, and it's the map for the rest of the series.

The LLMOps lifecycle — develop, evaluate, deploy, observe, improve — as a loop an LLM app lives inside, not a line it runs once. Why evaluation is a first-class stage appearing twice, why production feedback flows backward, and why the loop turns whether you act or not.

#LLMOps#Lifecycle#AI Engineering#Production#LLMs#Evaluation

All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.