How I Apply Spec-Driven AI Coding
LLMs code better when they focus on a single task at hand instead of trying to solve multiple issues on your codebase at once. Carl Rannaberg recently introduced a plan-based AI coding workflow in his article, "My current AI coding workflow", where LLMs first use a planner phase to create a task plan for the new feature you are developing, and then an executor phase goes through the plan to generate code task by task. I used the method for a while and liked it a lot.
Now, there is a new kid on the block, Kiro.dev from AWS, that goes even further by allowing the planner mode to first create the requirements spec, then the design, and only after that, the tasks list. As I'm still on Kiro's waitlist, I applied the methodology as a unified workflow for all the coding assistants at my disposal: Cursor, Claude, and Gemini.
I've put the framework up on GitHub as https://github.com/andreskull/spec-driven-ai-coding