AI Codex
Prompt EngineeringDevelopersOperators

Prompt Optimization

Systematically testing and improving prompts based on results — treating prompts like code that needs iteration, not one-time writing. This means running the same prompt against test cases, measuring how often it gives the right answer, changing something, running it again, and comparing. The difference between a prompt that works 60% of the time and one that works 90% of the time is usually a few rounds of this kind of deliberate testing.

In practice

Your Claude-powered classifier is 78% accurate. You systematically rewrite the prompt — testing different instruction phrasings, adding examples, adjusting tone — and test each version on 100 labeled examples. After six iterations, you're at 91%. That iterative improvement process is prompt optimization.

Related concepts

Where Prompt Optimization shows up

1 article