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LLMOps

MethodologyRole

LLMOps is a discipline derived from MLOps, dedicated to the specifics of operating LLM-based applications in production: managing prompts like code, continuous evaluation, observability of model calls, token cost manage…

LLMOps is a discipline derived from MLOps, dedicated to the specifics of operating LLM-based applications in production: managing prompts like code, continuous evaluation, observability of model calls, token cost management, monitoring hallucinations and drift, deploying versioned prompts or models.

It covers cross-cutting tooling: prompt versioning (Promptfoo, PromptLayer), evaluation (Braintrust, Humanloop, LangSmith), observability (Langfuse, Helicone, Arize), secrets management and rate limiting - plus the full RAG stack (vector databases, ingestion, retrieval).

It is one of the hottest topics in 2026: shipping a POC is easy; operating an LLM at scale and securely is still the real challenge.

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