How to trust what ships when you didn’t write the code

AI has accelerated code generation, but the true challenge lies in ensuring trust and reliability in AI-generated code before deployment. Trust is crucial because, without it, speed becomes irrelevant if the output is flawed. Developers previously understood every line of code they wrote, but with AI agents now generating code, new concerns arise about security risks, functionality, and downstream effects. Transparency is fundamental to building trust, requiring visibility into AI-generated changes through deploy previews, logs, and audit trails. Human-in-the-loop workflows maintain accountability by involving developers in the decision-making process, ensuring code is safe to ship. Platforms like Netlify emphasize transparency and control, allowing developers to see and test changes, thus maintaining the final say in deployment. As AI agents continue to contribute more code, the emphasis is on building trust through end-to-end transparency to turn AI-generated code into a reliable asset for production.