# ChatGPT prompt patterns cheatsheet (the 10 patterns that ship)

**Source:** https://promtable.com/cheatsheet/chatgpt-prompt-patterns

> Ten production-tested ChatGPT prompt patterns: role + objective, structured output, persona conditioning, step-back, output gating, anti-template, refusal calibration, evaluation rubric, scratchpad, exemplar.

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Ten production-tested ChatGPT prompt patterns: role + objective, structured output, persona conditioning, step-back, output gating, anti-template, refusal calibration, evaluation rubric, scratchpad, exemplar.

**Tool:** ChatGPT (GPT-4o / GPT-5)

## Core patterns

| Item | Description | Example |
|---|---|---|
| `Role + objective` | First line of system prompt names the role; second line names the win condition. | `You are a senior security engineer. Goal: spot every credential leak in the diff.` |
| `Structured output` | Force JSON or labelled fields. Use response_format or json_schema. | `{"verdict":"...", "issues":[...]}` |
| `Step-back` | Ask the model to articulate the question category before answering. | `Before answering, classify the question as factual / opinion / advice.` |
| `Output gating` | Tell the model to answer 'INSUFFICIENT' when context is too thin instead of guessing. | `If the document doesn't contain the answer, return INSUFFICIENT.` |

## Steering patterns

| Item | Description | Example |
|---|---|---|
| `Persona conditioning` | Define audience, not just role. 'For a junior dev' produces different output than 'for a CTO'. | `Write for a junior dev who has never used Docker.` |
| `Anti-template` | Tell the model what NOT to do. Beats vague positive instructions. | `Do not write 'In conclusion'. Do not use the word 'leverage'.` |
| `Refusal calibration` | Allow the model to refuse with a structured reason. | `If the request is unsafe, reply {"refuse":true, "reason":"..."}.` |

## Evaluation patterns

| Item | Description | Example |
|---|---|---|
| `Rubric in prompt` | Include the scoring rubric in the prompt for evals. | `Score 1-5 on: accuracy, completeness, tone. Return JSON.` |
| `Scratchpad` | Reserve <scratch>...</scratch> for chain of thought; instruct the model to put only the final answer in <answer>. | `Use <scratch> for reasoning. Final reply in <answer>.` |
| `Exemplar pinning` | Pin a single high-quality exemplar with rationale at the top of the user turn. | `Example of a great output: ... Why it's great: it follows the rubric exactly.` |

## FAQ

### Do I need few-shot examples for GPT-4o?

Often no for common tasks. For strict format or domain-specific tone, yes — 2-5 well-chosen examples beat any prose instruction.

### Should I tell GPT-4o to 'think step by step'?

For GPT-4o and GPT-5 non-reasoning, yes — it measurably improves multi-step tasks. For o-series reasoning models, no — they think internally.

### Is JSON mode reliable in 2026?

Yes when paired with json_schema. Without a schema, JSON mode guarantees syntax but not field semantics.

## Related

- [/glossary/system-prompt](https://promtable.com/glossary/system-prompt)
- [/glossary/few-shot-prompting](https://promtable.com/glossary/few-shot-prompting)
- [/glossary/json-mode](https://promtable.com/glossary/json-mode)
- [/compare/claude-vs-gpt-4o](https://promtable.com/compare/claude-vs-gpt-4o)

*Last updated: 2026-06-01*
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Original page: https://promtable.com/cheatsheet/chatgpt-prompt-patterns
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