Automating Code Review with AI Agents

Reviewing pull requests can be a time-consuming bottleneck for any development team. What if you could leverage artificial intelligence to handle the initial pass of code analysis automatically? This course teaches you how to build and integrate LLM-based agents directly into your development workflow. You will learn to construct effective prompts, provide necessary code context, and automate the feedback loop on pull requests, saving valuable time while maintaining high code standards. In this course, you will learn to: Understand the foundational concepts of Large Language Models and AI agents; Design effective prompts tailored for code analysis, bug detection, and style adherence; Manage code context and token limits when sending large diffs to an AI model; Integrate automated AI feedback directly into standard continuous integration workflows; and Apply best practices for balancing automated AI reviews with human oversight. The course begins with essential AI terminology and the basics of how language models process code. From there, you will move through step-by-step written tutorials on structuring prompts, handling repository data, and securely connecting AI tools to your version control system. This course is designed for developers, engineering leads, and technical professionals who are beginners to AI automation. No prior experience with artificial intelligence or complex machine learning is required. Start reading today to streamline your code review process with modern AI tools.