The durable techniques that make any model give you sharper, more reliable output — with worked before/after examples.
AI & PromptsPDF · 14 pages· v1.0
4.5A focused playbook of the prompt-engineering techniques that actually move the needle, explained with concrete before-and-after examples so you can see why each one works. No tricks that break next month — these are the durable principles that apply across models and versions. It's for anyone who uses LLMs for real work and wants consistent, high-quality output instead of rolling the dice each time: developers building features on top of models, writers, analysts, and operators automating tasks. The playbook covers the high-leverage moves: being specific about role and output format, giving examples (few-shot), asking the model to reason before answering, decomposing hard tasks, controlling tone and length, using delimiters to separate instructions from data, and giving the model an escape hatch so it admits uncertainty instead of inventing answers. Each technique includes a weak prompt, a strong prompt, and a one-line explanation of the difference. It also covers what to do when a prompt won't behave: a systematic debugging process rather than random tweaking. After reading, you'll be able to diagnose why a prompt is underperforming, apply the right technique deliberately, and write prompts that hold up in production. Delivered as a single Markdown file you can keep as a reference.
These are the durable principles (clarity, examples, structure, reasoning, escape hatches) that have held across model generations, not version-specific hacks. As models improve you often need *less* prompting, but the diagnostic skills still apply.
Both. The principles are the same whether you're typing into a chat box or building a feature; the examples cover everyday and programmatic use.
A list gives you fish; this teaches the patterns so you can write your own and fix prompts that aren't working.
It focuses on text prompting principles, which transfer broadly. Image-specific patterns are covered in our separate image-generation guide.
Read the full refund policy and trust & safety terms.