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AI adoption and Solow's productivity paradox

fortune.com

271–280 of 783 posts

Re: AI adoption and Solow's productivity paradox

#271
I think the article is very premature. Lots of companies are slow to adapt. And while there are a lot of early adopters, there are way more people still not really adapting what they do.

There are some real changes in day to day software development. Programmers seem to be spending a lot of time prompting LLMs these days. Some more than others. But the trend is pretty hard to deny at this point. That snowballed in just 6-7 months from mostly working in IDEs to mostly working in Agentic coding tools. Codex was barely usable before the summer (I'm biased to that since that is what I use but it wasn't that far behind Claude Code). Their cli tool got a lot more usable in autumn and by Christmas I was using it more and more. The Desktop app release and the new model releases only three weeks ago really spiked my usage. Claude Code was a bit earlier but saw a similar massive increase in utility and usability.

It is still early days. This report cannot possibly take into account these massive improvements that hav been playing out over essentially just the last few months. This time last year, Agentic coding was barely usable. You had isolated early adopters of Claude Code, Cursor, and similar tools. Compare to what we have now, these tools weren't very good.

In the business world things are delayed much more. We programmers have the advantage that many/most of our tools are highly scriptable (by design) and easy to figure out for LLMs. As soon as AI coders figured out how to patch tool calling into LLMs there was this massive leap in utility as LLMs suddenly gained feedback loops based on existing tools that it could suddenly just use.

This has not happened yet for the vast majority of business tools. There are lots of permission and security issues. Proprietary tools that are hard to integrate with. Even things like wordprocessors, spreadsheets, presentation tools, and email/calendar tools remain poorly integrated. You can really see Apple, MS, and Google struggle with this. They are all taking baby steps here but the state of the art is still "copy this blob of text in your tool". Forget about it respecting your document theme, or structure. Agentic tool usage is not widely spread outside the software engineering community yet.

The net result is that the business world still has a lot of drudgery in the form of people manually copying data around between UIs that are mostly not accessible to agentic tools yet. Also many users aren't that tool savvy to begin with. It's unreasonable to expect people like that to be impacted a lot by AI this early in the game. There's a lot of this stuff that is in scope for automating with agentic tools. Most of it is a lot less hard than the type of stuff programmers already deal with in their lives.

Most of the effects this will have on the industry will play out over the next few years. We've seen nothing yet. Especially bigger companies will do so very conservatively. They are mostly incapable of rapid change. Just look at how slow the big trillion dollar companies are themselves with eating their own dog food. And they literally invented and bootstrapped most of this stuff. The rest of the industry is worse at this.

The good news is that the main challenges at this point are non technical: organizational lag, security practices, low level API/UI plumbing to facilitate agentic tool usage, etc. None of this stuff requires further leaps in AI model quality. But doing the actual work to make this happen is not a fast process. From proof of concept to reality is a slow process. Five years would be exceptionally fast. That might actually happen given the massive impact this stuff might have.

Re: AI adoption and Solow's productivity paradox

#272

Earlier quoted context omitted.

> And I don’t recall it calling sales bullshit. It says stuff like why can’t a customer just order from an online form? The employee who helps them doesn’t do anything except make them feel better. Must be a bullshit job. It talks specifically about my employees filling internal roles like this. > advertising I understand the arms race argument, but it’s really hard to see what an alternative looks like. People can s…

It's an important function in a capitalist economy. Socialist economies are like "adblock for your life". That said, some advertising can be useful to inform consumers that a good exists, but convincing them they need it by synthesizing desires or fighting off competitors? Useless and socially detrimental.

Plus, a core part of what qualifies as a bullshit job is that the person doing it feels that it's a bullshit job. The book is a half-serious anthropological essay, not an economic treaty.

Re: AI adoption and Solow's productivity paradox

#273
post #267

Earlier quoted context omitted.

The future of work is fewer human team members and way more AI assistants. I think companies will need fewer engineers but there will be more companies. Now: 100 companies who employ 1,000 engineers each What we are transitioning to: 1000 companies who employ 10 engineers each What will happen in the future: 10,000 companies who employ 1 engineer each Same number of engineers. We are about to enter an era of explosiv…

That means the system will collapse in the future. Now from bunch of people some good programmers are made. Rest go into marketing, sales, agile or other not really technical roles. When the initial crowd will be gone there will be no experienced users of AI. Crappy inexperienced developer will make more crap without prior experience and ability to judge the design decisions. Basically no seniors without juniors.

This implies that writing code by hand will remain the best way to create software.

The seniors today who have got to senior status by writing code manually will be different than seniors of tomorrow, who got to senior status using AI tools.

Maybe people will become more of generalists rather than specialists.

Re: AI adoption and Solow's productivity paradox

#275
post #37

The article suggests that AI-related productivity gains could follow a J-curve. An initial decline, as initially happened with IT, followed by an exponential surge. They admit this is heavily dependent on the real value AI provides. However, there's another factor. The J-curve for IT happened in a different era. No matter when you jumped on the bandwagon, things just kept getting faster, easier, and cheaper. Moore's…

But there already is cheaper competition? Open models may be behind, but only ~6 months for every new generation.

Re: AI adoption and Solow's productivity paradox

#277

It's not just technology, it's very hard to detect the effect of inventions in general on productivity. There was a paper pointing out that the invention of the steam engine was basically invisible in the productivity statistics: https://www.frbsf.org/wp-content/uploads/crafts.pdf

The first steam engine was invented by a Turk and he used it solely to make kebab spin. Never thought about using it for anything else.

Re: AI adoption and Solow's productivity paradox

#278
Large firms are extremely bureaucratic organizations largely isolated from the market by their monopolistic positions. Internal pressures rule over external ones, and thus, inefficiency abounds. AI undeniably is a productive tool, but large companies aren't really primarily concerned with productivity.

Re: AI adoption and Solow's productivity paradox

#279

Earlier quoted context omitted.

Nobody questions that Anthropic makes revenue from a $20 subscription. The opposite would be very strange.

Yeah it's the caching that's doing the work for them though honestly. So many cached queries saving the GPUs from hard hits.

How is caching implemented in this scenario? I find it unlikely that two developers are going to ask the same exact question, so at a minimum some work has to be done to figure out “someone’s asked this before, fetch the response out of the cache.” But then the problem is that most questions are peppered with specific context that has to be represented in the response, so there’s really no way to cache that.

Re: AI adoption and Solow's productivity paradox

#280
post #261
post #64

Earlier quoted context omitted.

What if LLMs are optimizing the average office worker's productivity but the work itself simply has no discernable economic value? This is argued at length in Grebber's Bullshit Jobs essay and book.

We made an under-the-radar optimization in a data flow in my company. A given task is now much more freshData-assisted that it used to. Was a LLM used during that optimization? Yes. Who will correlate the sudden productivity improvement with our optimization of the data flow with the availability of a LLM to do such optimizations fast enough that no project+consultants+management is needed ? No one. Just like no one…

But you would see more houses, or housing build costs/bids fall.

This is where the whole "show me what you built with AI" meme comes from, and currently there's no substitute for SWEs. Maybe next year or next next year, but mostly the usage is generating boring stuff like internal tool frontends, tests, etc. That's not nothing, but because actually writing the code was at best 20% of the time cost anyway, the gains aren't huge, and won't be until AI gets into the other parts of the SDLC (or the SDLC changes).

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