Original Summary

If you've built anything with AI, you probably know this moment. The demo works on Saturday. By feature four, every new prompt breaks something that used to work. I used to blame the model. It's almost never the model. The real problem: nothing ever wrote down what the product actually is. No requirements, no spec, no definition of done. So every prompt is a fresh guess at what you meant, and each guess quietly undoes an earlier decision. Guesses don't add up to a system. Senior engineers have always started from the spec. Most of us building with AI skip it, because no tool makes us do it. What fixed it for us (works with any tool, even a plain doc): Write the product down before the next prompt. One page: who uses it, what they do, and what the app must never do. Turn each feature into user stories with acceptance criteria. Not "add login", but "when a guest logs in, they land on the Rooms page; a wrong password shows an error and keeps the email filled in." Make every change prove it still passes. Write tests from the same criteria, and run all of them after every AI change, not just the new ones. Keep the spec as the source of truth. When the code and the spec disagree, fix one on purpose. Never let a prompt decide silently. It feels slow for a day. It saves weeks, because "done" is defined before any code is written. Disclosure: I'm the founder of Codalio, and we built a tool around exactly this. You describe a product in plain English, and it writes the PRD and the spec (user flows, data model, acceptance criteria), then builds against it and tests every criterion. It carries 90 to 98% of the build, and a human still takes the last mile. We launched on Product Hunt today, and honest feedback is the most useful thing you could give us, good or bad: https://www.producthunt.com/products/codalio?utm_source=reddit&utm_medium=social Free PRD on your own idea if you want to try the approach: codalio.com/?ref=reddit Happy to answer anything about the method, even if you never touch our tool.   submitted by   /u/CodalioMVPBuilder [link]   [comments]

  • 情报分类：商业与市场研究
  • 分类依据：内容涉及商业、投资或市场动态
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/10/6 16:25:03