OpenAI has quietly released a substantial new resource for developers looking to build AI agents. The 32-page document, titled ‘Practical Guide to Building Agents,’ outlines a methodical approach to creating systems that can independently accomplish tasks with minimal human intervention.
Key Components of AI Agents
The guide identifies three foundational pillars for building AI agents:
- Models: Choosing the right language models to balance accuracy, latency, and cost.
- Tools: Defining reusable, well-documented tools for data retrieval and action.
- Instructions: Crafting clear, unambiguous instructions that break tasks into discrete steps and anticipate edge cases.
Orchestration Patterns and Security
OpenAI recommends starting with single-agent systems and evolving to multi-agent designs as complexity demands. The guide details both manager patterns, where a central orchestrator delegates to specialized agents, and decentralized patterns, where agents hand off control directly to other agents as needed.
Security is a significant focus, with a section on implementing guardrails as layered defense mechanisms. These include relevance classifiers to keep agents on-topic and tool safeguards to assess risk before actions are executed. Human intervention remains a critical safeguard, especially for high-risk actions or when agents repeatedly fail to accomplish tasks.
Practical Implementation
The guide provides a practical, code-first approach using OpenAI’s Agents SDK. It demonstrates how to build both single and multi-agent systems with relatively few lines of code, offering concrete implementation examples rather than theoretical architectures.
As large language models become more adept at reasoning, multimodal understanding, and tool use, AI agents are emerging as a critical interface for accessing this technology. This guide distills lessons learned from real-world deployments of AI agents into actionable best practices for developers.
