Claude Code and Intelligent Software Engineering

What happens when an AI that can edit your code, run commands, and open pull requests gets it wrong?

Most guides to AI coding stop at writing code faster. This one covers what comes after: testing it, securing it, shipping it, and keeping it running, with you in control at every step.

Claude Code and Intelligent Software Engineering takes one real application from an empty repository to a monitored, secured, deployed system. You follow a single project, Lighton Solution, through all ten chapters, so each skill builds on the last the way real engineering work does.

Inside, you will learn how to:

• Set up Claude Code with VS Code, Git, CLAUDE.md project instructions, permissions, and checkpoints
• Inspect unfamiliar codebases, plan multi-file features, refactor, and debug with confidence
• Build specialized agents and subagents for coding, testing, and code review
• Automate repeated tasks with skills and hooks, and connect GitHub and other tools through MCP
• Generate unit and API tests, and build quality gates that catch regressions before release
• Create CI/CD pipelines with GitHub Actions and AI-assisted pull request reviews
• Package apps with Docker, provision AWS infrastructure with Terraform, and deploy on Kubernetes
• Defend against prompt injection, protect secrets, limit agent permissions, and keep audit trails
• Monitor production with structured logging, health checks, metrics, and traces, then recover with controlled rollbacks

What sets this book apart

One rule runs through every chapter: a suggestion is not a verified result. You will learn to give agents narrow jobs, restrict what they can touch, check their work with automated evidence, and require human approval for anything that matters. The goal is speed without giving up reliability, security, or control.

Every chapter ends with practical exercises, so you can repeat each step on your own repository instead of just reading along. The examples use Python, FastAPI, PostgreSQL, and pytest, so the focus stays on the workflow rather than on unusual tools.

Who it's for

Developers, backend and DevOps engineers, technical leads, and students who know basic Python, the command line, and Git, and want to use AI assistance in real projects without losing oversight.

Stop treating AI as a shortcut and start using it as part of a disciplined engineering process. Click "Buy Now" and build, test, secure, and deploy your next application with Claude Code.