A Practical Guide to Building Agents
by OpenAI
34 pages that tell you when NOT to build an agent, then how to structure one that ships.
Overview
A Practical Guide to Building Agents is OpenAI's free 34-page PDF for product and engineering teams shipping their first agent, distilled from customer deployments. It has four substantive sections. What is an agent? draws a hard line: an agent uses an LLM to manage workflow execution and dynamically select tools within defined guardrails, so simple chatbots, single-turn LLM calls and sentiment classifiers are explicitly not agents. When should you build an agent? names three qualifying signals — complex judgement-based decisions, rulesets that have grown unmaintainable, and heavy reliance on unstructured data — and states plainly that if none apply a deterministic solution may suffice. Agent design foundations reduces an agent to three components, model, tools and instructions, and recommends prototyping with the most capable model to establish a baseline, then swapping in smaller models where accuracy holds. Tools are classified as data, action or orchestration, with agents themselves usable as tools. Orchestration covers single-agent loops with prompt templates, then two multi-agent shapes: the manager pattern, where one central agent calls specialists via tool calls, and the decentralized pattern, where peers hand off execution outright. The stated guidance is to maximize a single agent's capability first and split only on complex conditional logic or overlapping tools. Guardrails lists seven types — relevance classifier, safety classifier, PII filter, moderation, tool safeguards with risk ratings, rules-based protections and output validation — as layered defense, plus failure-threshold and high-risk triggers for human escalation. Code examples use the OpenAI Agents SDK, but the patterns are framework-agnostic.
At a Glance
- Topic
- Agentic
- Level
- Beginner
- Format
- Guide
- Cost
- Free
- Duration
- ~45 min read, 34-page PDF
- Provider
- OpenAI
- Hands-on
- No
- Certificate
- None
What You’ll Learn
- ✓Apply a concrete test for whether a workflow actually warrants an agent at all
- ✓Decompose any agent into its three core components: model, tools and instructions
- ✓Choose models by baselining with the strongest, then downgrading where accuracy holds
- ✓Classify tools as data, action or orchestration and define them for reuse across agents
- ✓Choose between single-agent loops, the manager pattern and decentralized handoffs
- ✓Layer seven distinct guardrail types instead of relying on one blanket safety filter
- ✓Set failure thresholds and high-risk action triggers that escalate to a human operator
Highlights
- •Explicitly tells you when not to build an agent, which is rare in vendor-published material
- •Names the two multi-agent patterns precisely — manager versus decentralized handoff — with diagrams
- •Assigns risk ratings to individual tools to drive automated escalation, a concrete safety mechanism
- •Short enough to read in one sitting; reached 253 points on Hacker News
- •Patterns transfer to any framework even though the code examples use the OpenAI Agents SDK
Who It’s For
Best For
- ✓Product and engineering teams scoping their first agent deployment
- ✓Engineers who need shared vocabulary for orchestration patterns and guardrails
- ✓Anyone deciding whether a workflow needs an agent or ordinary deterministic automation
Prerequisites
- •Basic understanding of LLMs and tool or function calling
- •Ability to read short Python examples; no agent framework experience required
FAQ
What is A Practical Guide to Building Agents?
OpenAI's free PDF for product and engineering teams building their first agent, distilled from customer deployments. It defines what counts as an agent, gives a test for when one is warranted, reduces an agent to model, tools and instructions, then covers orchestration patterns and seven guardrail types. Afterwards you can scope an agent project and defend the orchestration and safety choices.
Is A Practical Guide to Building Agents free?
A Practical Guide to Building Agents is free to access.
What level is A Practical Guide to Building Agents for?
A Practical Guide to Building Agents is aimed at a beginner audience. Recommended background: Basic understanding of LLMs and tool or function calling, Ability to read short Python examples; no agent framework experience required.
How long does A Practical Guide to Building Agents take?
Expect roughly ~45 min read, 34-page PDF. Most learners work through it at their own pace.
What will I learn from A Practical Guide to Building Agents?
You'll learn: Apply a concrete test for whether a workflow actually warrants an agent at all; Decompose any agent into its three core components: model, tools and instructions; Choose models by baselining with the strongest, then downgrading where accuracy holds; Classify tools as data, action or orchestration and define them for reuse across agents; Choose between single-agent loops, the manager pattern and decentralized handoffs; Layer seven distinct guardrail types instead of relying on one blanket safety filter; Set failure thresholds and high-risk action triggers that escalate to a human operator.
Topics
Sources
This page was written from 2 sources, 1 on domains other than cdn.openai.com.