December 2025
Intermediate to advanced
320 pages
8h 7m
English
In Chapter 4, we went deep on what it takes to turn a rigid structured LLM workflow into an agent and why you might want to mix the two. But to be honest, getting agents to “just work” in production is rarely about picking the right framework, crafting the right tool description or MCP server, or cranking out more code. The magic lies in how you shape agents’ behavior by using prompting, smarter workflows, and (sometimes) even more agents to split up the work.
In this chapter, we’ll zoom in on what moves the needle when you want agents to reliably follow rules, align with real-world policies, or just stop making up answers. We’ll see how prompt engineering and clever ...
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