Prompt Engineering

Prompt engineering is the discipline of deliberately designing, structuring, and refining prompts so a model produces reliable, useful output — not by luck, but by construction. Where a casual user types whatever comes to mind, a prompt engineer treats the prompt as an artifact: versioned, tested, and improved against real failure cases. It spans everything from wording and structure to choosing techniques like few-shot examples or chain-of-thought for a given task.

For a developer, this matters because prompting is usually the cheapest, fastest lever you have. Before you reach for fine-tuning, RAG pipelines, or a bigger model, a better prompt often closes most of the quality gap — at zero training cost and with instant iteration. It is also where product behavior lives: the difference between an assistant that hallucinates confidently and one that says “I don’t know” is frequently a few well-placed sentences.

Throughout this module you will build a working toolkit: writing specific instructions, supplying context, showing examples, constraining format, and layering system prompts and roles on top. You will apply it in real code — prompts stored as templates in your repo, interpolated with user data, run through an eval harness before deploying. Treat every prompt like a function signature: define inputs, define expected outputs, and test the contract.