LLMs diverge, not converge. They slightly increase entropy if not controlled. While you can have DRY skills and use AI to organize AI (in loops(tm) like Boris does) but eventually if you don’t understand the code, you are taking yourself out of the loop. And not just the job security that’s on the line, it’s the increasing cost for AI to babysit AI. If you or your “loops” (or paperclip, Hermes, gastown, or next in class agents of agents that runs your entire company) let it gradually sneak in slop-debt, the cost to fix it later will become prohibitive. (You can always just rewrite it, but as the race for “feature complete” and “zero backlog” continues, rewriting an ever growing set of new daily table stakes will become an economical moat)
TLDR: Keeping your codebase human readable and reason-about-able is not just helping humans to stay relevant. It will save costs for LLMs to maintain it.
> They slightly increase entropy if not controlled.
If you use AI at the very start of a project, replace slightly with greatly. AI loves to write abstractions and indirection and add complexity wherever it can. And it does so really, really, really badly. AI is great at writing procedural code, but it's a world class shit-for-brains at architecture. It has no taste, no restraint, no appreciation of simplicity.
And it wouldn't be so bad, except it's ALSO a complete toaster when it comes to naming things.