Saved by Raul Coutinho-Garrido and
Building Effective AI Agents
A practical guide to building agents
Guide to building AI agents using large language models, covering agent definition, use case selection, design components, single/multi-agent orchestration, tool integration, instruction setup, safety guardrails, and deployment best practices.
cdn.openai.comWe conclude with key principles for writing high-quality tools we’ve identified along the way:
- Choosing the right tools to implement (and not to implement)
- Namespacing tools to define clear boundaries in functionality
- Returning meaningful context from tools back to agents
- Optimizing tool responses for token efficiency
- Prompt-engineering tool
anthropic.com • Writing Effective Tools for Agents — With Agents
What makes these agents good at going deep?
The core algorithm is actually the same - it’s an LLM running in a loop calling tools. The difference compared to the naive agent that is easy to build is:
The core algorithm is actually the same - it’s an LLM running in a loop calling tools. The difference compared to the naive agent that is easy to build is:
- A detailed system prompt
- Planning tool
- Sub agents
- File system