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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. veunes+wX[view] [source] 2026-02-02 10:05:59
>>danpal+vd
All of this speedrun hits a wall at the context window. As long as the project fits into 200k tokens, you’re flying. The moment it outgrows that, productivity doesn’t drop by 20% - it drops to zero. You start spending hours explaining to the agent what you changed in another file that it has already forgotten. Large organizations win in the long run precisely because they rely on processes that don’t depend on the memory of a single brain - even an electronic one
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3. TaupeR+Dm1[view] [source] 2026-02-02 13:31:48
>>veunes+wX
This reads as if written by someone who has never used these tools before. No one ever tries to "fit" the entire project into a single context window. Successfully using coding LLMs involves context management (some of which is now done by the models themselves) so that you can isolate the issues you're currently working on, and get enough context to work effectively. Working on enormous codebases over the past two months, I have never had to remind the model what it changed in another file, because 1) it has access to git and can easily see what has changed, and 2) I work with the model to break down projects into pieces that can be worked on sequentially. And keep in mind, this the worst this technology will ever be - it will only get larger context windows and better memory from here.
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