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[return to "Two kinds of AI users are emerging"]
1. danpal+vd[view] [source] 2026-02-02 01:44:03
>>martin+(OP)
I've noticed a huge gap between AI use on greenfield projects and brownfield projects. The first day of working on a greenfield project I can accomplish a week of work. But the second day I can accomplish a few days of work. By the end of the first week I'm getting a 20% productivity gain.

I think AI is just allowing everyone to speed-run the innovator's dilemma. Anyone can create a small version of anything, while big orgs will struggle to move quickly as before.

The interesting bit is going to be whether we see AI being used in maturing those small systems into big complex ones that account for the edge cases, meet all the requirements, scale as needed, etc. That's hard for humans to do, and particularly while still moving. I've not see any of this from AI yet outside of either a) very directed small changes to large complex systems, or b) plugins/extensions/etc along a well define set of rails.

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2. K0balt+uy[view] [source] 2026-02-02 05:23:10
>>danpal+vd
It seems to be fantastic up to about 5k loc and then it starts to need a lot more guidance, careful supervision, skepticism, and aggressive context management. If you’re careful, it only goes completely off the rails once in a while and the damage is only a lost hour or two.

Overall, still a 4x production gain overall though, so I’m not complaining for $20 a month. It’s especially good at managing complicated aspects of c so I can focus on the bigger picture rather than the symbol contortions.

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3. ginger+NL[view] [source] 2026-02-02 07:58:43
>>K0balt+uy
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?
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4. K0balt+491[view] [source] 2026-02-02 11:58:43
>>ginger+NL
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.

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