What do you think?
Rate this book
Practical AI Agents for Developers: Building Autonomous Coding Workflows with Claude, Cursor, and Copilot
Your AI assistant stopped being autocomplete. Your workflow never caught up.
In 2026, a coding agent can take a bug report, write a failing test, fix the code, review its own diff, and open a pull request — all while you're at lunch. Most developers are still using these tools like a faster keyboard, and getting burned when an agent quietly rewrites a test instead of fixing the bug.
This book is the missing manual. You'll build a working agent from scratch in forty lines of Python, so you understand the loop instead of trusting it. Then you'll go deep on the three tools that matter — Claude Code in the terminal, Cursor in the IDE, and GitHub Copilot's cloud agent — including the failure modes their documentation doesn't mention. Finally you'll ship production MCP servers, CI review bots, multi-agent pipelines, and the guardrails that keep an enthusiastic agent from becoming an incident report.
What you'll
How the agent loop actually works, and why stop_reason is the whole gameWriting tools an agent picks correctly the first timeManaging context windows so long sessions don't get expensive or amnesiacThe four-part prompt shape that produces consistent resultsWhich tool fits which task — terminal, IDE, or cloud — and why brand loyalty costs you moneyMaking your repository a place agents can succeed inTest-driven agent development, and the lock that prevents silent successBuilding MCP servers that expose your database, tickets, and internal APIsDefending against prompt injection hiding in code comments and issuesShipping a complete issue-to-pull-request agent as your capstone projectEvery chapter ends with a project you can run in twenty minutes.
In 2026, a coding agent can take a bug report, write a failing test, fix the code, review its own diff, and open a pull request — all while you're at lunch. Most developers are still using these tools like a faster keyboard, and getting burned when an agent quietly rewrites a test instead of fixing the bug.
This book is the missing manual. You'll build a working agent from scratch in forty lines of Python, so you understand the loop instead of trusting it. Then you'll go deep on the three tools that matter — Claude Code in the terminal, Cursor in the IDE, and GitHub Copilot's cloud agent — including the failure modes their documentation doesn't mention. Finally you'll ship production MCP servers, CI review bots, multi-agent pipelines, and the guardrails that keep an enthusiastic agent from becoming an incident report.
What you'll
How the agent loop actually works, and why stop_reason is the whole gameWriting tools an agent picks correctly the first timeManaging context windows so long sessions don't get expensive or amnesiacThe four-part prompt shape that produces consistent resultsWhich tool fits which task — terminal, IDE, or cloud — and why brand loyalty costs you moneyMaking your repository a place agents can succeed inTest-driven agent development, and the lock that prevents silent successBuilding MCP servers that expose your database, tickets, and internal APIsDefending against prompt injection hiding in code comments and issuesShipping a complete issue-to-pull-request agent as your capstone projectEvery chapter ends with a project you can run in twenty minutes.
200 pages, Kindle Edition
Published July 29, 2026
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
No one has reviewed this book yet.