Front end CI/CD in the age of AI (neciudan.dev)

A recent tech article highlights the impact of AI on Continuous Integration (CI) and Continuous Deployment (CD) practices, particularly in frontend development. As AI-generated code and tests become more prevalent, traditional CI processes face increasing inefficiencies, leading to longer wait times for developers. The article emphasizes the need to separate CI from CD, as CI focuses on verifying code correctness before merging, while CD ensures safe deployment to production. It proposes a restructured CI pipeline that only tests affected components based on changes made, rather than running all tests, thereby optimizing the workflow and reducing bottlenecks. Significantly, the article outlines a strategy for implementing this efficient structure by leveraging Git's capabilities to identify changed files and their dependencies. By creating workflows that dynamically assess what has changed and only execute relevant tests, developers can achieve quicker feedback without sacrificing code quality. The approach uses scripts to identify dependencies and run necessary tools like linters and type checkers only on impacted files. This method not only saves time but also addresses the scalability issues as codebases grow. Overall, this shift fosters a more agile development environment, crucial for teams adapting to the AI-driven landscape.