This podcast provides a practical guide to building agents, defining them as systems that use large language models (LLMs) to independently execute complex, multi-step workflows using various tools and explicit instructions. It outlines criteria for determining when an agent is the right solution, particularly for tasks involving complex decision-making, difficult-to-maintain rules, or heavy reliance on unstructured data. The guide also covers essential components, including selecting appropriate models, defining tools for external interaction, and crafting clear instructions. It explores different orchestration patterns, starting with single-agent systems before moving to more complex multi-agent approaches like manager and decentralized patterns, emphasizing the importance of starting incrementally. Finally, the text highlights the critical role of guardrails for safety and reliability, discussing various types of protections and the need for planning human intervention when agents encounter challenges or high-risk scenarios.

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