Building LLM-Powered Applications: From Prototype to Production
Moving an LLM application from a demo to production requires careful attention to latency, cost, reliability, and safety. This guide covers the production essentials.
A demo is not an operating system
Production LLM applications need more than prompt quality. They need retrieval strategy, model routing, structured outputs, evaluation datasets, fallback behavior, and clear ownership for incidents and improvements.
Measure quality continuously
Evaluation should cover factuality, instruction following, safety, latency, and cost. Automated tests catch regressions before releases, while human review helps tune edge cases that matter to the business.
Design for change
Models, APIs, and user expectations evolve quickly. Keep prompts versioned, isolate provider-specific code, log decisions carefully, and create feedback loops that let the system improve safely.