Developing AI Agents with OpenAI AgentKit
Build, deploy and govern agents with OpenAI AgentKit — Agent Builder, tool calling, guardrails and evals.
Most developers start with a prompt. It works for a simple question, but as soon as a real workflow appears — refunds, approvals, triage — the prompt alone falls apart.
The solution: An agent is like an employee. It stays in the loop, makes decisions step by step, calls tools when needed, and continues until the work is truly done.
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What's inside
14 sections- 1 Table of Contents
- 2 Introduction — From Prompts to Agents
- 3 AgentKit Definition and Core Components
- 4 MCP — Model Context Protocol
- 5 Building the First Agent with Agent Builder
- 6 Tool Calling — Detect → Act → Respond
- 7 Deployment — ChatKit vs ChatGPT Apps
- 8 Reliability — Tracing, Debugging and Tuning
- 9 Guardrails — See, Do, Say
- 10 Governance and Security at Scale
- 11 Evals — Automated Quality Testing
- 12 Reference Tables
- 13 Complete Architecture — Diagrams
- 14 Conclusion — The Era of AI Operators
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