Building upon the foundational LangChain elements like models, prompts, and output parsers, this chapter focuses on constructing more complex workflows. We will first examine Chains, which allow you to link multiple LangChain components together sequentially to perform multi-step tasks.

Subsequently, we introduce Agents. Agents utilize an LLM as a reasoning engine to determine sequences of actions, often involving external tools like search or calculation. You will learn how to build custom chains, understand the agent execution cycle, integrate tools, create a basic agent, and apply techniques for debugging these more intricate structures. Practical exercises will guide you through implementing these advanced concepts.