Large language models are moving from pilots to production. Here's what organizations are learning about deploying them at enterprise scale.
The Hallucination Problem in Production
The solutions that work in production are architectural: retrieval-augmented generation that grounds model responses in verified sources, confidence thresholds that route low-confidence responses to human review, and output validation that checks responses against known facts before they reach users.
The Total Cost of LLM Operations
LLM inference costs are falling rapidly, but at enterprise scale they add up. Thoughtful cost management — right-sizing models to the task, caching common queries, optimizing prompt length — is now a standard part of production LLM architecture.