Prompting That Survives Production
Move past clever one-off prompts. Structure instructions, constrain outputs, and evaluate like you mean it.
A prompt that works once in ChatGPT is not a product feature. Production prompting is about constraints, structure, and measurement.
Write for the model, not for yourself
Be explicit about:
- Role and goal
- Allowed tools / sources
- Output format (JSON schema when possible)
- What not to do
Ambiguity is free in demos and expensive in production.
Prefer structure over poetry
Task: Summarize the support ticket.
Audience: Internal ops.
Format: JSON with keys severity, summary, next_action.
Rules: Do not invent account details. If unknown, use null.
Clear beats clever.
Eval early
Keep a golden set of 20–50 real examples. Score:
- Format validity
- Factual grounding
- Refusal correctness
If you cannot measure it, you cannot ship it safely.
Version your prompts
Treat prompts like code: review them, version them, and roll them back when quality drops.