DIY AI Code Review

Creating your own AI code review system within a CI pipeline is both cost-effective and customizable, allowing you to bypass expensive commercial platforms. By utilizing Bash scripts and an AI API, you can construct a personalized automated reviewer that analyzes only the modified files in a pull request, thus enhancing efficiency. This DIY approach empowers you to control the analysis scope, customize AI prompts, and manage data security. The process involves selecting the files to be reviewed, sending them to an AI model like OpenAI with tailored prompts, and parsing the AI's structured output to take actionable steps, such as logging results or failing the CI pipeline if too many errors are detected. While this approach requires some initial setup and experimentation, it offers a practical and flexible solution for integrating intelligent automation into your CI workflow, with resources like the tomfern / semaphore-demo-ai-review repository providing a starting point.