Building Effective AI Agents \ Anthropic
Discover how Anthropic approaches the development of reliable AI agents. Learn about our research on agent capabilities, safety considerations, and technical framework for building trustworthy AI.
Over the past year, we've worked with dozens of teams building large language model (LLM) agents across industries. Consistently, the most successful implementations weren't using complex frameworks or specialized libraries. Instead, they were building with simple, composable patterns. In this post, we share what we’ve learned from working with our customers and building agents ourselves, and give practical advice for developers on building effective agents. What are agents? "Agent" can be defined in several ways. Some customers define agents as fully autonomous systems that operate independen
saved by
- Amir
- Ratan Kaliani
- Emma Guo
- Maanav Khaitan
- Ayush Shukla
- Agnim Agarwal
- Aliyah Sausan
- Senthilnathan Thirumurugan
related reading
- Building Effective AI Agents \ Anthropicanthropic.com
- LLM Powered Autonomous Agents | Lil'Loglilianweng.github.io
- Effective context engineering for AI agents \ Anthropicanthropic.com
- Demystifying evals for AI agents \ Anthropicanthropic.com
- Agent Evaluation: A Detailed Guidecameronrwolfe.substack.com
- Building reliable AI agents · parth sareenparthsareen.com
- Designing agentic loopssimonwillison.net
- What are agents? 🤔 · Hugging Facehuggingface.co
- Agentic Evals Pyramidrwilinski.ai
- Ichigo (@iiiichigo_chan) on Xx.com
- What is an Agent? | Devinwindsurf.com
- Don’t Build Multi-Agents | Cognitioncognition.ai