Building Effective LLM Agents: Patterns and Practices

This Anthropic publication offers practical guidance on constructing effective AI agents using large language models. It advocates for simple, composable patterns over complex frameworks, highlighting that the most successful agent implementations avoid unnecessary abstraction. The document clarifies the distinction between workflows (predefined code paths) and agents (dynamically self-directed systems). It explores various building blocks and workflow patterns, such as prompt chaining and routing, before discussing fully autonomous agents. Emphasizing a user-centric approach to tool design, the piece advises starting with direct API usage and prioritizing clarity and simplicity in agent architecture for reliable and maintainable systems.