Unlock the power of LLM-powered systems with our practical guide to building intelligent agents. This podcast delves into the foundations of agent design, exploring what exactly an agent is – a system that independently accomplishes tasks on your behalf. We examine when building an agent is the right choice, focusing on workflows with complex decision-making, difficult-to-maintain rules, and heavy reliance on unstructured data.

Discover the core components of an agent: the Large Language Model (LLM) for reasoning and decision-making, the various tools for interacting with external systems, and the crucial instructions and guardrails that define agent behaviour. We explore strategies for selecting the right models and defining effective tools. Learn best practices for configuring clear and concise instructions to ensure smooth workflow execution.

We also guide you through different orchestration patterns, from single-agent systems to more complex multi-agent systems, including the manager pattern and the decentralized pattern. Understand the importance of an incremental approach to building agents. Finally, we discuss the critical role of guardrails in ensuring your agents operate safely and predictably by addressing data privacy and reputational risks. We cover various types of guardrails, including relevance classifiers, safety classifiers, PII filters, and rules-based protections. We also highlight the importance of planning for human intervention as a crucial safeguard.

Whether you're part of a product or engineering team exploring the world of autonomous systems, this podcast provides the foundational knowledge and actionable best practices to confidently start building your first agent.