Overview
OpenAI Prompt Engineering Docs API Reference describes techniques, examples, and API guidance for designing effective prompts and integrating them with the OpenAI Responses and other API features to produce reliable model outputs.
Key Features:
- Detailed examples for the Responses API, including message roles, instructions, and code snippets
- Structured outputs support (JSON/structured data), reusable prompt templates, and prompt caching guidance
- Best practices for model selection, few-shot learning, context management, and prompting GPT and reasoning models
Use Cases:
- Generating natural language, code, or structured JSON responses from prompts
- Building multi-turn conversational agents with developer/user role control and instruction pinning
- Retrieval-augmented generation and including external context or documents in prompts
Benefits:
- More consistent, higher-quality model outputs through proven prompt strategies
- Reduced cost and latency via prompt caching and model-choice guidance
- Improved reliability and repeatability with reusable prompts, pinned model snapshots, and eval-driven iteration