What Is LLM Engineering?

LLM Engineering is the technical work of building, adapting, and deploying applications powered by large language models, spanning prompt design, retrieval systems, fine tuning, and production monitoring.

Most enterprise use cases don't need a custom trained model; the real engineering decision is choosing between prompt engineering, retrieval augmented generation, and fine tuning, each with different cost, latency, and accuracy trade offs, and increasingly using more than one together. Getting that decision wrong wastes budget on the more expensive options where a simpler approach would have worked, or settles for an approach that can't reach the accuracy a use case genuinely needs.

We start LLM engagements by establishing whether prompt engineering and retrieval augmented generation are sufficient before considering fine tuning, since the latter carries meaningfully more cost and ongoing maintenance. Where fine tuning is justified, typically for consistent output formatting, domain specific terminology, or reliability requirements prompting can't guarantee, we use parameter efficient methods that keep costs manageable, and build in evaluation and monitoring from the outset, since a fine tuned model's performance drifts as real world usage moves away from its original training data.