AI writes Python code fast, but someone still has to decide if that code is correct, safe, and ready to ship. This course gives Python developers a clear process for reviewing AI-generated code and a practical way to automate that review with Claude Code. You will work with real generated code, find the problems it hides, and fix your workflow around them.

You start with how AI coding tools evolved from autocomplete to AI agents, what today's models can and cannot do, and how the developer's role changes because of that. Then you move to hands-on evaluation: correctness and logic, error handling and input validation, missing scenarios and edge cases, test coverage, quality and performance. Each checkpoint is shown on real AI-generated Python code, so you know exactly what to look for. In the final part you stop reviewing everything by hand. You learn what can be automated in AI code review, build your own code review skill, use Claude Code commands, write review rules with good and bad examples, and guide reviews with a CLAUDE.md file. Throughout the course, you'll explore: AI Evolution and the Developer's Role: See how AI coding tools moved from autocomplete to AI agents, and where your judgment still matters most. Common Challenges of AI-Generated Code: Learn the typical failures of generated Python code, from wrong logic to missing safeguards, before they reach production. Evaluation Checkpoints: Use a repeatable set of checkpoints to verify correctness, logic, error handling, and input validation in AI-generated Python code. Edge Cases, Tests and Performance: Find missing scenarios and weak test coverage, then check quality and performance of the generated code. Reviewing Requirements with Others: Watch how AI-generated requirements are discussed with a reviewer, so you can defend or correct them in a real team. Automated Code Review with Claude Code: Create your own code review skill, explore community skills, and run reviews with Claude Code commands. Review Rules and CLAUDE.md: Define review rules with good and bad examples and use CLAUDE.md to keep AI reviews consistent across a project. By the end of the course, you will review AI-generated Python code with confidence and run a large part of that review automatically, so you spend your time on the decisions that really need a developer.