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Comment by visarga | Hacker News Reader

You usually don't know what you want upfront, in real life it is a stream of specification and steering.

Yes, agree. It's a learning process. I tend to find when I build systems that at some point you need to stop analysis and just start building things to explore the problem. As you do, you prototype, refactor and possibly throw out ideas in favour of understanding the problem and discovery the real solution.

The code becomes a reflection of that.

I'm interested in your experiences of capturing specifications and user discussion on whether this captures the end intentions? Or whether it keeps you focused on earlier dead end directions?

I think agents are pretty capable of reading a log when given the explicit task of extracting the latest version of what the user wants. In general, they work well for direct tasks like this. They don't forget and do something else the way they do when they are deep into development work or debugging.

Besides intent, I also mine signs of "user friction," which I use as input for the agent to come up with new tests. What I complain about is one of the signals driving testing.

Yes, agree very capable of consuming large amounts of information

I'd be interested to see what happens:

- to token counts after a year of so of changes, as the specification list grows?

- how it goes with concurrent changes in teams?

Plus whether asking AI to add good commenting to the code could achieve the same thing?

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