AI Agents Made Simple

By the author of RAG Made Simple and Agent Memory Made Simple, whose open-source AI curricula have earned more than 85,000 GitHub stars.Most agent projects fail because they built the wrong thing, not because they built it badly.

The demo worked once. Then real users arrived, and the agent looped on a broken tool, followed instructions hidden inside an email, and ran up a bill several times the forecast. AI Agents Made Simple is a decision guide to building agents that survive that week. 28 chapters, 148 custom illustrations, and no code.

Every chapter takes one pattern and answers four questions: how it works, what breaks, what it costs, and when it is overkill. Each one ends with a verdict and the simpler thing to try first, and shows where the pattern lives inside the coding agent you already use.

Inside this book:

Before you build - whether you need an agent at all, the agent loop with the vocabulary stripped away, and the workflows to try firstGiving the model hands - tool calling and tool design, retrieval as a tool, the web and the screen, running code, MCP and A2A, and skills loaded on demandMaking it reliable - context engineering, evals and error analysis, tracing, prompt injection and guardrails, human approval, and what an agent really costsPlanning and reasoning - reason-act loops, effort levels, plan-then-execute, skeptical reviewers, and thinking budgetsState, memory, and many agents - long-running work across sessions, memory in one chapter, when to go multi-agent, orchestrators and workers, and handoffsShipping - background and scheduled agents, deployment, a coding agent taken apart, and how agents failWho this book is for: developers and technical product managers who build agents, are about to, or have to decide whether one should be built at all. You need no machine learning background, only to have called a model from code or watched a coding agent work.

Built not to go stale. The book names no framework, SDK, model or vendor, and quotes no prices or benchmark scores. It teaches the concepts underneath, as engineers practice them today, so the next framework you meet will have parts you can already name. It joins the Super AI Engineering Series, alongside the Amazon bestseller RAG Made Simple and Agent Memory Made Simple.