Prompt Engineering

This is the canonical guide for writing better prompts. It covers the techniques that actually matter: few-shot learning with examples, chain-of-thought reasoning, systematic optimization through A/B testing, reusable templates, and system prompt design. The progressive disclosure pattern is especially useful, showing you when to add complexity versus keeping it simple. Use this when your prompts are inconsistent, when you're burning tokens on bloated instructions, or when you need to debug why an agent isn't behaving as expected. The concrete examples and error recovery patterns make it practical rather than theoretical.