This results in an executable specification: give it to an AI coding agent like Ensemble, and it will execute the specification autonomously, creating a new version of the code. This works perfectly when I create new versions of Ensemble by executing "The Art of Building AI Coding Agents". I've never seen a more successful specification.
You have to build the spec as you build the code. The processes cannot be separated. I do the usual up-front design conversation with the AI, and then ask it to write just the TL;DR and exercises sections of the next chapter. After that, I pair-program with the AI to implement it, following the TL;DR, writing notes as we go to clarify what was unclear, steering the AI in real time towards my design.
Once the new code passes all the exercise graders, only then do I ask the AI to read the notes, voice.md file, and write the body of the chapter. Then, I have it launch a student to see if it can write the code purely from the chapter and graders.
At the end of this process, I'm the expert, and I don't even need to review the code.
Code is simply the result of executing the right specification. Just another artifact of the compiler.
Stop vibe-coding. Become the expert by pair-programming with the AI as you build to code, and then build the specs from what you did to build the code. Don’t document the code to build. Document the process, lessons learned, and why you built it this way. You can’t do that up-front.
If you don’t know how to pair-program with the AI, well, you can always try running Ensemble, and listening to the AI as it works. It won’t call tools until you’ve listened to every word the AI says, and the AI isn’t allowed to silently call tools.
I know this is hard for all of you folks with good vision. Get over it. Just do it.
It would be very helpful to show a demo of how you're using Ensemble to build an app, say a business app and what is the final result. I'm not sure this is what I imagine it is but it appears interesting concept. I'll remind myself to try it next week but if I saw a demo that would be a more definite attempt at it. Are you planning to publish any demos?
I’m interested. Why does it work so well for you? What were your considerations while developing this approach? And how do you envision that this would work in a bigger team, that has a ‘regular’ ticket-based approach to software dev?
You have to build the spec as you build the code. The processes cannot be separated. I do the usual up-front design conversation with the AI, and then ask it to write just the TL;DR and exercises sections of the next chapter. After that, I pair-program with the AI to implement it, following the TL;DR, writing notes as we go to clarify what was unclear, steering the AI in real time towards my design.
Once the new code passes all the exercise graders, only then do I ask the AI to read the notes, voice.md file, and write the body of the chapter. Then, I have it launch a student to see if it can write the code purely from the chapter and graders.
At the end of this process, I'm the expert, and I don't even need to review the code.
Code is simply the result of executing the right specification. Just another artifact of the compiler.
Stop vibe-coding. Become the expert by pair-programming with the AI as you build to code, and then build the specs from what you did to build the code. Don’t document the code to build. Document the process, lessons learned, and why you built it this way. You can’t do that up-front.
If you don’t know how to pair-program with the AI, well, you can always try running Ensemble, and listening to the AI as it works. It won’t call tools until you’ve listened to every word the AI says, and the AI isn’t allowed to silently call tools.
I know this is hard for all of you folks with good vision. Get over it. Just do it.
Really?