This handbook discusses how to build AI agents for software developers.
Building effective agents by Anthropic
This Anthropic article explains approaches to building reliable AI agents, including capabilities and safety considerations.
About Building effective agents by Anthropic
Published December 19, 2024, this Anthropic engineering article shares observations from working with teams building large language model agents. It defines agentic systems and distinguishes workflows, where LLMs and tools are orchestrated through predefined code paths, from agents, where LLMs dynamically direct their own processes and tool usage.
It describes building blocks such as an augmented LLM with retrieval, tools and memory, patterns including prompt chaining with intermediate checks, and considerations for using frameworks or LLM APIs directly. It notes that much of the tooling landscape described has changed since December 2024 and points to newer material on Claude Managed Agents. It also states that agentic systems often trade latency and cost for task performance.
Key features
- Defines workflows versus agents architectural distinction
- Explains augmented LLM with retrieval, tools, and memory
- Describes prompt chaining with intermediate programmatic checks
- Outlines when to use simple calls over agents
- Lists frameworks including Claude Agent SDK and others
- References Model Context Protocol for third-party tool integration
Best for: Developers building applications with large language models who need guidance on workflows and agents.
Good for
- Based on work with dozens of teams building LLM agents
- Focuses on simple, composable patterns rather than complex frameworks
- Points to cookbook with sample implementations
Watch out for
- Notes that tooling landscape has changed since December 2024
- States agentic systems often trade latency and cost for performance
Building effective agents by Anthropic at a glance
- Category
- Education & Learning › AI Learning & Guides
- Type
- Website
- Pricing
- Not confirmed. Check the site
- Platforms
- Web
- Open source
- Not stated
- Language
- English
- Good for
- Developers
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
Building effective agents by Anthropic alternatives
Tools and sites you could use instead, ranked by how closely they match.
This page outlines research on large language model-based multi-agent systems.
Made With ML offers lessons on designing, developing, deploying, and improving production machine learning applications.
Chip Huyen writes about AI system design and bringing AI applications into production.
This repository contains more than 50 tutorials and implementations for generative AI agent techniques.
This Lil’Log article explains prompt engineering methods for steering autoregressive language models.
Popular in AI Learning & Guides
Well-known listings from the same topic.
NN Visualnn-visual.comTutorialSearchtutorialsearch.ioTutor AItutorai.meAnimated AIanimatedai.github.ioR-bloggersr-bloggers.comShikenshiken.ai
Building effective agents by Anthropic FAQ
What is the difference between workflows and agents in the article?
Workflows orchestrate LLMs and tools through predefined code paths, while agents let LLMs dynamically direct their own processes and tool usage.
When should I avoid building an agentic system?
The article recommends finding the simplest solution possible, noting that optimizing single LLM calls with retrieval and in-context examples is usually enough.
Does the article recommend using an agent framework?
It suggests starting by using LLM APIs directly and, if using a framework, ensuring you understand the underlying code.
Is something wrong or out of date?
Tell us and an editor will check it.
Own this website?
Claim this listing
Claim the listing and suggest updates yourself. An editor checks every claim first.