Prompt Engineering That Scales

A prompt that works in a demo often breaks in production. Here are three habits that keep prompts reliable.

1. Separate instructions from data

Keep the instruction stable and inject the data around it. Mixing them invites injection and drift.

2. Make the output shape explicit

Ask for a schema, then validate it. If the model must return JSON, say so — and reject anything that doesn't parse.

3. Test prompts like code

Given: a support email
Expect: { category, urgency, summary }

Run a suite of examples on every change. A prompt is code; treat it that way.

Reliability comes from constraints, not cleverness.