Cool analogy, but there's another possibility: software is uniquely suited for being boosted by LLM-based coding agents. That's not to say LLMs are useless in other domains, but they may not yield as much benefit.

Software creation tools have been worked on for decades to keep fallible human coders out of trouble as much as possible. Starting with compilers that enforce or at least encourage coding style humans can understand. Compilers embody formal definitions of language syntax. Lint and other static analysis technologies contribute by identifying problematic patterns in code. Leak detectors identify memory management problems. Profilers identify performance problems.

Few other endeavors have this much tooling that serendipitously happens to help help LLM-based agents be more useful and less error prone.

A lot of discussion around AI is very high-level and abstract. It helps to dig in and identify the characteristics that actually make a domain more or less amenable to being boosted by AI.

And whole repositories with commit history that provides step by step training on how to code.

AI could probably write decently if every scraped book had all the revisions to create it embedded within or art had every brush stroke documented. As it stands programming is the first to be trained. The rest will take some more time.

I can't speak for everywhere else, but here in the Bay Area (California), pretty much all hospitals use AI for transcription, summarizing, and some other stuff that I'm not fully aware of (I should really listen to what my Nurses say before agreeing to being recorded).

> As an example, take a factory that was built around hyrdo-power like a grain mill. You can't just take an electric motor and drop it in in place of the water wheel.

Your chosen example is rather more fitting for the opposite case. Dropping an electric motor is pretty easy, you just attach it to the other side of the axle. But there is really no point in doing that. The sole benefit for that mill, will be that there is the cheap power from the water. It's also the sole reason for the current position of the mill, for the electric motor, you hence need to add long cables first. The size and operation mode of the mill is also not fit at all for the electric age. There is really no point, you are better of just building a new mill in a completely different location.

But you can do that independently of the old mill, since there is hardly any capital to be taken from the old to the new mill, short of maybe the office supply. So you just build a new mill, completely independently. But there is also no reason to decommission the old at the same time, the only reason is to shut it down when is no longer economically viable. But that also might be at a different point in time than building the new mill.

most lawyers haven't tried fable and astra ultrafast yet.

those who did are rather convinced it's over, for juniors at least.

I'm not an cliometrician, but my impression is that it took about 4 decades for electricity and steam to do much for productivity.

And it was in 1987 that Nobel laureate economist Robert Solow famously said “You can see the computer age everywhere but in the productivity statistics”

I mean, maybe AI will be faster, because it's especially easy to apply compared to generally applicable technologies. There was the Bank of Korea study showing this spring that did show productivity gains with single proprietors--folks who don't have to reorg employees and processes to do something with more abilty or saved time.

But, generally, I don't know that there was an reason to expect that corporate America generally was going to see an AI payoff so soon.

I think the reason is much more simple.

It's very hard to improve something that you don't understand yourself. All the tiny decisions you make as you create a product are informed by the experience you have.

So it's seems obvious to me that a product created by software engineers would be better at software engineering. A programmer knows what a programmer needs.

To improve another industry successfully, you would really need people from that industry to be involved in a deep level in the design of the product.

It is most impactful in tech because tech is almost nothing but languages and more so super expensive languages where one hour of an “authors” time can cost thousands with a supply demand issue so bad workers are imported from across the world.

Artists were already starving. The more physical trades are…physical not language so a plumber still plums. Maybe now they ask gemini instead of google tho.

Areas related most to…language are the most impact by large language models? The one that i think is just as impacted is education because it is also almost all language driven.

I see zero sign of any of the new mills coming around. Steel, crops, farming, none of it has changed and what little has is from…the software side or…language.

The SV world really over indexes on how much software can do.

"the tech sector is the most software defined"

AIs don't just make code they make words, images, and sounds. Hasn't worked in those markets either.

There are some things that current generation LLMs are extremely good at. They also suck for a lot of reasons and appear to be prohibitively expensive to train as "general" models.

hey are amazing tools, but every time I see a task that LLMs helped me complete in 30% less time, I see 5 more tasks that took me 30-50% longer to complete because of errors, lies, mistakes, hallucinations, context limits.

Do not tell me I'm holding it wrong.