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AI adoption and Solow's productivity paradox

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81–90 of 783 posts

Re: AI adoption and Solow's productivity paradox

#81
It's weird being on here and seeing so much naysaying, because I see a radical change already happening in software development. The future is here, it's just not equally distributed.

In the past 6 months, I've gone from Copilot to Cursor to Conductor. It's really the shift to Conductor that convinced me that I crossed into a new reality of software work. It is now possible to code at a scale dramatically higher than before.

This has not yet translated into shipping at far higher magnitude. There are still big friction points and bottlenecks. Some will need to be resolved with technology, others will need organizational solutions.

But this is crystal clear to me: there is a clear path to companies getting software value to the end customer much more rapidly.

I would compare the ongoing revolution to the advent of the Web for software delivery. When features didn't have to be scheduled for release in physical shipments, it unlocked radically different approaches to product development, most clearly illustrated in The Agile Manifesto. You could also do real-time experiments to optimize product outcomes.

I'm not here to say that this is all going to be OK. It won't be for a lot of people. Some companies are going to make tremendous mistakes and generate tremendous waste. Many of the concerns around GenAI are deadly,serious.

But I also have zero doubt that the companies that most effectively embrace the new possibilities are going to run circles around their competition.

It's a weird feeling when people argue against me in this, because I've seen too much. It's like arguing with flat-earthers. I've never personally circumnavigated Antarctica, but me being wrong would invalidate so many facts my frame of reality depends on.

To me, the question isn't about the capabilities of the technology. It's whether we actually want the future it unlocks. That's the discussion I wish we were having. Even if it's hard for me to see what choice there is. Capitalism and geopolitical competition are incredible forces to reckon with, and AI is being driven hard by both.

Re: AI adoption and Solow's productivity paradox

#83

Earlier quoted context omitted.

The comparison seems flawed in terms of cost. A Claude subscription is 20 bucks per worker if using personal accounts billed to the company, which is not very far from common office tools like slack. Onboarding a worker to Claude or ChatGPT is ridiculously easy compared to teaching a 1970’s manual office worker to use an early computer. Larger implementations like automating customer service might be more costly, but…

Like Uber/Airbnb in early days, this is heavily subsidized.

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Re: AI adoption and Solow's productivity paradox

#84

Earlier quoted context omitted.

when the work involves navigating a bunch of rules with very ambiguous syntax, AI will automate them to the point computers automated rules based systems with very precise syntax in the 1990s https://hazel.ai/tax-planning this software (which i am not related to or promoting) is better at investment planning and tax planning than over 90% of RIAs in the US. It will automate RIA to the point that trading software auto…

You could have beaten the returns of most financial professionals over the last several years by just parking your money in the S&P 500, and yet plenty of people are still making a lucrative career out of underperforming it. In some fields, “being better and cheaper” does not always spell victory.

you are right on beating money managers. when I said investment planning, I meant planning the size and tax structures for investments. this software automates all of the technical work that goes on inside financial planning firms, which is done by tens of thousands of white collar professionals in US/UK/EU, et c. it will then lead to price competitiveness.

more expensive silly companies will exist, but the cheap ones get the scale. SP500 index funds have over 1 trillion in the top 3 providers. cathy wood has like 6-7 billion.

BNYMellon is the custodian of $50 trillion of investment assets. robinhood has $324bn.

silly companies get the headlines though

Re: AI adoption and Solow's productivity paradox

#85
As we approach the singularity things will be more noisy and things will make less and less sense as rapid change can look like chaos from inside the system. I recommend folks just take a deep breath, and just take a look around you. Regardless on your stance if the singularity is real, if AI will revolutionize everything or not, just forget all that noise. just look around you and ask yourself if things are seeming more or less chaotic, are you able to predict better or worse on what is going to happen? how far can your predictions land you now versus lets say 10 or 20 years ago? Conflicting signals is exactly how all of this looks. one account is saying its the end of the world another is saying nothing ever changes and everything is the same as it always was....

Re: AI adoption and Solow's productivity paradox

#86
I think the 'AI productivity gap' is mostly a state management problem. Even with great models, you burn so much time just manually syncing context between different agents or chat sessions.

Until the handoff tax is lower than the cost of just doing it yourself, the ROI isn't going to be there for most engineering workflows.

Re: AI adoption and Solow's productivity paradox

#87

Earlier quoted context omitted.

100% All of the people who are floored by AI capabilities right now are software engineers, and everyone who's extremely skeptical basically has any other office job. On investigating their primary AI interaction surface, it's Microsoft Co-Pilot, which has to be the absolute shittiest implementation of any AI system so far. As a progress-driven person, it's just super disappointing to see how few people are benefitin…

I'm a SWE who's been using coding agents daily for the last 6 months and I'm still skeptical. For my team at least, the productivity boost is difficult to quantify objectively. Our products and services have still tons of issues that AI isn't going to solve magically. It's pretty clear that AI is allowing to move faster for some tasks, but it's also detrimental for other things. We're going to learn how to use these…

In a team of one at work I see clear benefits, but having worked in many different team sizes for most of my career I can see how it quickly would go down, especially if you care about quality. And even with the latest models it’s a constant battle against legacy training data, which has gotten worse over time. ”I have to spend 45 minutes explaining why a one minute AI generated PR is bad code” was how an old colleague summarized it.

Re: AI adoption and Solow's productivity paradox

#88

Earlier quoted context omitted.

I'm a SWE who's been using coding agents daily for the last 6 months and I'm still skeptical. For my team at least, the productivity boost is difficult to quantify objectively. Our products and services have still tons of issues that AI isn't going to solve magically. It's pretty clear that AI is allowing to move faster for some tasks, but it's also detrimental for other things. We're going to learn how to use these…

> I'm a SWE who's been using coding agents daily for the last 6 months and I'm still skeptical. What improvements have you noticed over that time? It seems like the models coming out in the last several weeks are dramatically superior to those mid-last year. Does that match your experience?

Not the grandparent, but I've used most of the OpenAI models that have been released in the last year. Out of all of them, o3 was the best at the programming tasks I do. I liked it a lot more than I like GPT 5.2 Thinking/Pro. Overall, I'm not at all convinced that models are making forward progress in general.

Re: AI adoption and Solow's productivity paradox

#89

Just to be clear, the article is NOT criticizing this. To the contrary, it's presenting it as expected , thanks to Solow's productivity paradox [1]. Which is that information technology similarly (and seemingly shockingly) didn't produce any net economic gains in the 1970's or 1980's despite all the computerization. It wasn't until the mid-to-late 1990's that information technology finally started to show clear benef…

I don’t think LLMs are similar to computers in terms of productivity boost

Re: AI adoption and Solow's productivity paradox

#90
post #64

Earlier quoted context omitted.

The comparison seems flawed in terms of cost. A Claude subscription is 20 bucks per worker if using personal accounts billed to the company, which is not very far from common office tools like slack. Onboarding a worker to Claude or ChatGPT is ridiculously easy compared to teaching a 1970’s manual office worker to use an early computer. Larger implementations like automating customer service might be more costly, but…

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.

The thesis of Bullshit Jobs is almost universally rejected by economists, FYI. There’s not much of value to obtain from the book.
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