Writing Prompts That Survive Contact With Users

A prompt is a program written in natural language, and the first version never survives real input. This course covers the practical prompt engineering for production — versioning, adversarial inputs, the few-shot set that earns its place, and the eval that tells you when a change regressed — that distinguishes a demo from a feature you can ship and keep.

Why this gap matters now

Demand signals we detected:

prompt-fragility complaints up 210%
jailbreak/regression incidents recurring
sparse content on prompt engineering for production vs demos

What you'll learn

Treat the prompt as versioned code — An unversioned prompt means every change is an unobserved regression, and when the feature breaks next week nobody can find what changed.
Few-shot earns its place, it doesn't pad it — Few-shot examples are the most expensive tokens in your prompt and the most often cargo-culted.
Plan for the input you didn't expect — Real users send inputs the demo never imagined: empty strings, pasted documents, other-language text, and deliberate adversarial phrasings.
The regression eval that guards every change — Every prompt change — a phrasing tweak, a new example, a model swap — can regress a class of inputs that worked before.