From OpenSpec to AIDLC: How I Improved My Team's AI Code Quality

No new commands to learn, just pick it up and use it By this August, our team had been writing code with AI for more than half a year. The biggest thing I noticed during this time was that our development speed went up, but code quality stayed pretty rough. Development often took just half a day, but hunting down bugs could take several days. So recently I spent more than a month restructuring our team's AI coding workflow. I replaced OpenSpec with the AIDLC workflow, using a more detailed software development process and stronger team collaboration. Code quality finally jumped up a lot. In today's article, I want to tell you how we did it. This article was originally published on my personal blog, Data Leads Future , where you can find the source code at the bottom of the original post . I'll also keep updating content there and am happy to answer any questions you might have. Introduction AI coding has been around for more than a year now. People's focus in this field has slowly shifted from which model works better and how much it boosts efficiency, to how we can make sure the code AI generates is actually good quality. I recently noticed something. On social media, people talk more and more about questions like "how do I actually make sure my AI coding output has good quality" and "who should be responsible for code AI writes." If you asked me six months ago, I would have said the best answer to this question was SDD (Spec Driven Development). Based on rule frameworks like SpecKit and OpenSpec, you first talk things through in a question-and-answer style to nail down the requirements and implementation rules. Then you feed the spec files to the LLM as a prompt, and the LLM writes code strictly following those specs. This seemed like the best way to do AI coding. I even wrote a few articles about tips for using OpenSpec. It wasn't until I rolled out my method to the whole development team that I realized something. SDD works pretty well for small projects. But on