Live data from Hacker News

AI adoption and Solow's productivity paradox

fortune.com

111–120 of 783 posts

Re: AI adoption and Solow's productivity paradox

#111
The slow part as a senior engineer has never been actually writing the code. It has been:

- reviews for code

- asking stakeholders opinions

- SDLC latency (things taking forever to test)

- tickets

- documentations/diagrams

- presentations

Many of these require review. The review hell doesn't magically stop at Open source projects. These things happen internally too.

Re: AI adoption and Solow's productivity paradox

#112

The thing with a lot of white collar work is that the thinking/talking is often the majority of the work… unlike coding, where thinking is (or, used to be, pre-agent) a smaller percentage of the time consumed. Writing the software, which is essentially working through how to implement the thought, used to take a much larger percentage of the overall time consumed from thought to completion. Other white collar busines…

I’m confused what kind of software engineer jobs there are that don’t involve meeting with people, “aligning expectations”, getting consensus, making slides/decks to communicate that, thinking about market positioning, etc? If you weren’t doing much of that before, I struggled to think of how you were doing much engineering at all, save some more niche extremely technical roles where many of those questions were alre…

It seems that to some number of folks, "engineering" means "writing code."

Re: AI adoption and Solow's productivity paradox

#113
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.

And that book sort of vaguely hints around at all these jobs that are surely bullshit but won’t identify them concretely. Not recognizing the essential role of sales seemed to be a common mistake.

What counts as “concretely”? And I don’t recall it calling sales bullshit.

It identified advertising as part of the category that it classed as heavily-bullshit-jobs for reason of being zero-sum—your competitor spends more, so you spent more to avoid falling behind, standard red queen’s race. (Another in this category was the military, which is kinda the classic case of this—see also, the Missile Gap, the dreadnought arms race, et c.) But not sales, IIRC.

Re: AI adoption and Solow's productivity paradox

#114

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…

Curious why you like Conductor. I’m trying it out, but since I primarily live in the CLI, I might not see much value in it.

Re: AI adoption and Solow's productivity paradox

#116
post #46

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…

How viable are the $20/month subscriptions for actual work and are they loss making for Anthropic? I've heard both of people needing to get higher tiers to get anything done in Claude Code and also that the subscriptions are (heavily?) subsidized by Anthropic, so the "just another $20 SaaS" argument doesn't sound too good.

Merely for the viability part: I use the $20/mo plan now, but only as a part-time independent dev. I will hit rate-limits with Opus on any moderately complex app.

If I am on a roll, I will flip on Extra Usage. I prototyped a fully functional and useful niche app in ~6 total hours and $20 of extra usage, and it's solid enough and proved enough value to continue investing in and eventually ship to the App store.

Without Claude I likely wouldn't have gotten to the finished prototype version to use in the real world.

For Indy dev, I think LLMs are a new source of solutions. This app is too niche to justify building and marketing without LLM assistance. It likely won't earn more than $25k/year but good enough!

Re: AI adoption and Solow's productivity paradox

#117

The thing with a lot of white collar work is that the thinking/talking is often the majority of the work… unlike coding, where thinking is (or, used to be, pre-agent) a smaller percentage of the time consumed. Writing the software, which is essentially working through how to implement the thought, used to take a much larger percentage of the overall time consumed from thought to completion. Other white collar busines…

Thinking is always the hardest part and the bottleneck for me. It doesn’t capture everyone’s experience when you say thinking is the smaller part of programming. I don’t even believe a regular person is capable of producing good quality code without thinking 2x the amount they are coding

Agree. I remember in school in the 1980s reading that a good programmer can write about 10 lines of code a day (citing The Mythical Man-Month) and I thought "that's ridiculous, I can write hundreds of lines a day" but didn't understand that's including all the time understanding requirements, thinking about design, testing, debugging, etc. Writing the code is a small portion of what a software engineer does.

Re: AI adoption and Solow's productivity paradox

#118

The people who will be most productive with AI will be the entreprompteurs who whip up entire products and go to market faster than ever before, iterating at dangerous speeds. Lean Startup methodology on pure steroids basically. Unfortunately I think most of the stuff they make will be shit, but they will build it very productively.

Software doesn't need to be good to be successful; it only needs to solve a problem and be better than the competition. I predict a golden age for experienced developers! There will be an uncountable number of poorly designed apps with scaling issues. And many of them will be funded.

Meh, no. In a future where any app could be prompted, the only thing you’d get funding for is if you had managed to go viral and secure some large audience.

This is not good. When all that matters is how viral your app is, people no longer compete on features and quality of life.

Re: AI adoption and Solow's productivity paradox

#119

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…

Is your backlog and/or your velocity increasing, decreasing, or the same? That's really the ultimate question.

Re: AI adoption and Solow's productivity paradox

#120
post #30
post #9

My compsci brain suggests large orgs are a distributed system running on faulty hardware (humans) with high network latency (communication). The individual people (CPUs) are plenty fast, we just waste time in meetings, or waiting for approval, or a lot of tasks can't be parallelized, etc. Before upgrading, you need to know if you're I/O Bound vs CPU Bound.

operationally, i think new startups have a big advantage on setting up to be agent-first, and they might not be as good as the old human first stuff, but theyll be much cheaper and nimble for model improvements

[deleted]
Post reply on HN