Most AI systems don't fail because of the model-they fail because they aren't systems.They're stitched-together prompts: good for demos, too fragile for reality.
They work once, then drift. Outputs change. Tools misfire. Agents loop. You patch and retry-until you're no longer writing prompts, but controlling behavior.
This book is about that shift.Written by Amrita Panjwani, a senior data scientist with over a decade of experience, it focuses on the real challenge: building AI agents that work-consistently and at scale.
Today, the focus is on models. But models aren't the solution. Design is: structured reasoningcontrolled tool useuseful memorystable workflowsWithout this, even the best model fails.This book starts from first principles. No shortcuts. You'll understand how agents behave, why they fail, and how to fix them.
You'll learn to design consistent agents, debug with clarity, control tool usage, and structure decisions.Built from real systems, this book tackles what actually breaks: loops, inconsistent outputs, unreliable tools, fragile workflows.If you're working with LLMs, you're already in a shift: Prompt-driven → System-driven.
Success is no longer about better prompts-it's about better architecture.This book is for data scientists, engineers, and developers tired of systems that fail to work.You'll build systems that handle variation, make controlled decisions, use tools with intent, and deliver consistent results.
