Resources · Code recipes
OpenAI Cookbook
Practical examples for prompts, tool use, agents, structured output, evaluation and production AI workflows.
What it is
A useful starting point—not another unexplained bookmark.
The OpenAI Cookbook is a collection of practical examples that moves beyond basic API calls. It is most useful when you already know the feature you want and need a reference implementation or testing pattern.
Useful for
When to use it
- Finding working implementation examples
- Learning tool calling and structured outputs
- Adding evaluation to an AI workflow
What you will find
Inside the resource
- Runnable examples
- Agent and tool-use patterns
- Prompt and evaluation recipes
- Production-oriented implementation guidance
Quick start
How I would use it
- 01
Search by the feature
Look for the capability you need, such as structured output, retrieval, tools or evaluation.
- 02
Read the assumptions
Check the model, SDK version, required services and expected input before copying code.
- 03
Build the smallest example
Run the core pattern with test data before connecting it to your real database or customers.
- 04
Add your own checks
Measure correctness, latency and cost with examples from your actual product.
Ready?
Continue to OpenAI
Keep exploring
Where to go next
Next step
Want to use one of these in a real product?
Tell me the user problem. I will help you choose the resource and the safest first integration.