How Do You Know Your AI Is Actually Good? A Guide to LLM Evaluation

By Allela · AI Engineering · 9 min read You’ve built something. A chatbot, a document assistant, a code reviewer, a customer support agent. You’ve tested it yourself, shown it to a few people, and it seems… good? The answers feel right. The tone is on point. Nothing obviously embarrassing has slipped through. So you ship it. Three weeks later, a user screenshots your AI confidently telling them that your product has a feature it doesn’t have. Another user complains it keeps going in circles. A third says it gave completely different answers to the same question on two different days. Welcome to the most underrated problem in AI engineering: you never defined what “good” actually meant. Evaluation — evals, in the industry shorthand — is the discipline of measuring AI quality systematically. Not vibes. Not spot checks. Actual measurement. And it’s the difference between an AI product that scales with confidence and one that silently degrades the moment you stop paying attention. The Unco