OrionAI Build logo orionai.build

The 8 Prompt Patterns That Survived My Last 6 Months

By OrionAI Build Editorial · Published 2026-05-10 · // guide

Six months in production. Patterns that didn't churn out and the ones that did.

1. Role anchoring

Open the prompt with a clear, specific role. Not "you are a helpful assistant" — that's table stakes. "You are a B2B SaaS support agent for {company}; you triage tickets and route to humans when uncertain." The anchor narrows behaviour. Wider anchors drift. Narrower anchors hold.

2. Structured I/O

Always output JSON when downstream code consumes the output. Always validate. When the model outputs malformed JSON, return a "your last output was not valid JSON, try again" turn — don't try-catch and silently fail.

3. Refusal scaffold

Explicitly authorise refusal. List the cases where the model should say "I don't know" or "I can't do that." Default model behaviour skews toward answering; you have to opt in to refusal.

4. Few-shot rotation

Few-shot examples in the prompt drift with traffic. Rotate them based on what's actually showing up in production. I refresh the example set weekly from the previous week's hardest cases.

5. Output validators

For every structured output, write a validator that checks:

If any validator fails, return the failure to the model and ask it to fix. Don't ship invalid output.

6. Retry-with-correction

When the model fails, return the failure as data and let it self-correct. "Your output had this error: X. Please fix and respond again." This is reliably better than re-prompting from scratch.

7. Lazy elaboration

Don't pre-fill detail you won't use. If the user asks "yes or no?" the agent should answer "yes" or "no" — not a paragraph. Pattern: explicitly tell the model to elaborate only if asked.

8. Privilege walls

Architectural, not prompt-based. The agent that reads user content must not be the same agent (or have the same tool privileges as) the agent that takes destructive actions. Prompt-injection defenses that live entirely inside the prompt fail eventually.

What didn't survive

Model APIs — vetted picks
GPU & compute — vetted picks
Dev tools — vetted picks