Early access · v0.9 · updated quarterly

Everyone has seen the demo. This book is about what comes after.

Building Agentic Systems — A Practical Guide to AI System Engineering · Yuri Syuganov

Get early access Read a sample from $19 · suggested $29 · every update free
    ┌─────────────────┐
┌──▶│     reason      │
│   └────────┬────────┘
│            ▼
│   ┌─────────────────┐
│   │       act       │
│   └────────┬────────┘
│            ▼
│   ┌─────────────────┐
└───│     observe     │
    └─────────────────┘

Agents fail in ways traditional software doesn’t: silently, expensively, and with great confidence. Building Agentic Systems is an engineer’s guide to closing the gap between a promising prototype and a system you can trust with real work.

  • The agent loop, tool contracts, and structured outputs that make model behavior testable
  • State, memory, and context budgets that survive long-running work
  • Multi-agent orchestration without multiplying failure modes
  • Reliability, cost, observability, and security — the production disciplines, adapted
  • The operator practice: running AI-assisted projects day to day, with humans in the loop

26 chapters · 437 pages in print

What’s inside

PART I

Foundations: What Agents Actually Are

Past the “autonomous agent” myth to what you’re actually building — and the reason–act–observe loop underneath every agent that works.

PART II

Core Building Blocks

Structured outputs and contracts, tools and function calling, execution models, state, and memory — through your first end-to-end agent.

PART III

Multi-Agent Systems

From one agent to many: orchestration patterns, parallel execution and conflict resolution, and human-in-the-loop design that isn’t a rubber stamp.

PART IV

Making It Production-Grade

Reliability engineering, observability and debugging, cost engineering, evaluation and testing, security and governance.

PART V

Advanced Patterns and Real Systems

Long-running resumable workflows, repo-aware agents, the AI project operator, and designing agent systems for teams.

PART VI

Context and Outlook

Frameworks — when to use them and when not to — and the evolving landscape.

A living book

The field this book covers moves quarterly, and the book moves with it. Model names, prices, and context windows are re-checked against provider documentation at every release — and every update is free for as long as the book exists. You buy the book once; it stays current.

All twenty-six chapters are written — this is a complete draft, not a partial one. What stands between 0.9 and 1.0 is a final verification pass over the fastest-moving facts. Early-access readers get 1.0 and every quarterly refresh after it, free.

current  v0.9 · July 2026
next     v1.0 · verification pass

Built with the workflow it teaches

This book is written, reviewed, and maintained with the agentic system described in its own chapters: a human operator setting direction and reviewing every change, AI agents doing delegated work under version control. When the mid-2026 model lineup replaced the one the examples were first written against, parallel review agents swept all twenty-six chapters against the live API reference — and a human reviewed the diff. The machinery in Part V produced the pages you’ll be reading.

About the author

Yuri Syuganov is a software engineer who builds and operates AI-assisted development systems — the multi-project agentic workflow described in this book runs his own work every day. He is also the author of The Modern QA Engineer Skillset, a 26-book series on software quality, and writes at modernQAcourse.com.