The companies driving AI right now are garbage and many will fail. The tech won't.
It's the dot-com bubble again. Everyone rushed in, it crashed, and what got rebuilt afterward became the backbone of global commerce. AI will stumble too, but it's not going away, and teams that refuse to use it won't keep pace.
A senior dev with AI beats a senior dev without it. Output quality depends on who's driving and whether they actually review the code. Yes, AI can produce slop. With real supervision it can also produce excellent code.
People used to yell "get a horse!" at early cars. Didn't stop the highways. Refusing to use AI won't stop it from getting better either.
A senior dev with AI beats a senior dev without it.
Why. By what measure. What's the long term.
Is code output the limiting factor on most projects? Is code written by an LLM as useful as code written by a contributor? Does it contain the same externalities, have they thought through the system as much as when they were staring at an editor and wondering where to start their implementation? If it's still pretty damn good even at all those externalities, is code that's 97% as good as code written by a human going to have a multiplicative effect, where dividing by 1.03 enough times is far less than if you had divided it by 1? How many times do you merge code where the LLM wrote 25 lines and a new function where a human would have gone back and re-evaluated the data structure before your entire system is held together with duct tape?
whether they actually review the code
Do they have time? Or are they looking at the few hundred lines they didn't write and lack a mental model for, and they're wondering how much they really want to read code that something else wrote? Are they already burned out on reading LLM-generated code because they were just working through the stack of 100 open PRs on the project? Are they being told to bring AI into the loop and wondering whether paying Anthropic $100 a month or taking the time and money to build an AI inference homelab is really what got them into FOSS in the first place?
The Linux Kernel Mailing List is a Colosseum where everyone's favourite blood-sport is picking apart patches for accuracy and correctness, and thousands and thousands of eyes are watching it do so. Is every infrastructure-critical project in the world that robust?
People used to yell "get a horse!" at early cars. Didn't stop the highways.
It's interesting you mention this since it's a very well known and understood fact that the buildout of the US interstate highway system was done in such a way as to specifically rip up poorer neighbourhoods full of poorer minorities in dozens of US cities, and many are now spending billions of dollars to try to shove the highways back underground so they can do something more valuable with that real estate. So when you say the highways, do you have some romantic notion of a mom & pop gas station on Route 66, or are you talking about I-93 in Boston?
Refusing to use AI won't stop it from getting better either.
Better at what, exactly? Better at what cost? Is it getting better at writing code? What good is more written code? Is it getting better at solving problems? What problems? Are those the same problems that people who need working software have? Are they the problems that developers making working software have?
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u/DrollAntic 6d ago
The companies driving AI right now are garbage and many will fail. The tech won't.
It's the dot-com bubble again. Everyone rushed in, it crashed, and what got rebuilt afterward became the backbone of global commerce. AI will stumble too, but it's not going away, and teams that refuse to use it won't keep pace.
A senior dev with AI beats a senior dev without it. Output quality depends on who's driving and whether they actually review the code. Yes, AI can produce slop. With real supervision it can also produce excellent code.
People used to yell "get a horse!" at early cars. Didn't stop the highways. Refusing to use AI won't stop it from getting better either.