Yes, I see the same thing. My working thesis is that if I can keep the codebase modular and clear seperations, so I keep the entire context, while claude code only need to focus on one module at a time, I can keep up the speed and quality. But if I try and give it tasks that cover the entire codebase it will have issues, no matter how you manage context and give directions. And again, this is not suprising, humans do the same, they need to break the task apart into smaller piecers. Have you found the same?
Yes. Spot on. The good thing is that it makes better code if modularity is strict as well.
I’m finding that I am breaking projects down into clear separations of concerns and designing inviolate API walls between modules, where before I might have reached into the code with less clearly defined internal vs external functions.
Exercising solid boundaries and being maniacal about the API surface is also really liberating personally, less cognitive load, less stress, easier tests, easier debugging.
Of course none of this is new, but now we can do it and get -more- done in a day than if we don’t. Building in technical debt no longer raises productivity, it lowers it.
If you are a competent engineer, ai can drastically improve both code quality and productivity, but you have to be capable of cognitively framing the project in advance (which can also be accelerated with ai). You need to work as an architect more than a coder.
