Recently I discovered spec-driven development, and it actually changed how I code with AI tools. Before this I was mostly doing the usual “prompt -get code - fix things - repeat” workflow. It worked, but once the project started growing the AI would sometimes lose context or generate messy changes across files. With spec-driven development, the idea is simple , I write a clear specification (like features ,inputs and outputs ,expected behavior ,edge cases) first, then let the AI generate the implementation from that. Now the code seems more structured and i have less debugging to do i implemented it using traycer Curious if others here are using this approach or sticking with normal prompting. submitted by /u/StatusPhilosopher258
Originally posted by u/StatusPhilosopher258 on r/ArtificialInteligence
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