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AI adoption and Solow's productivity paradox

fortune.com

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Re: AI adoption and Solow's productivity paradox

#211

Post by alephnerd »

mrtksn wrote: post #207
alephnerd wrote: post #183

Earlier quoted context omitted.

> I asked it because I am building something similar since some tome and I thought its over they were faster than me If you have been working on a usecase similar to OpenClaw for sometime now I'd actually say you are in a great position to start raising now . Being first to market is not a significant moat in most cases. Few people want to invest in the first company in a category - it's too risky. If there are a cou…

Do you think that it is a good idea to release it first on iOS, announce on HN and Producthunt? How would you do? On my app the tech is based on running agent generated code on JavaScriptCore to do things like OpenClaw, I’m wrapping the JS engine with the missing functionality like networking, file access and database access so I believe I will not have a problem with releasing it on Apple AppStore as I use their nat…

Who's your persona? How are you pricing and packaging? Who is your buyer? Are you D2C? Consumer? Replacing EAs? Replacing Project Managers? ...

You need to answer these questions in order to decide whether a Show HN makes sense versus a much more targeted launch.

If you do not know how to answer these questions you need to find a cofounder asap. Technology is commodified. GTM, sales, and packaging is what turns technology into products. Building and selling and fundraising as 1 person is a one-way ticket to burnout, which only makes you and your product less attractive.

I also highly recommend chatting with your network to understand common types of problems. Once you've identified a couple classes of problems and personas for whom your story resonates, then you can decide what approach to take.

Best of luck!

Re: AI adoption and Solow's productivity paradox

#212

Post by overgard »

sebmellen wrote: post #80
8note wrote: post #55

Earlier quoted context omitted.

> 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. huh? maybe im in the minority, but the thinking:coding has always been 80:20 spend a ton of time thinking and drawing, then write…

Yeah, ratios vary depending on how productive you are with code. For me it was 50:50 and is now 80:20, but only because I was a relatively unproductive coder (struggled with language feature memorization, etc.) and a much more productive thinker/architect.

"Struggling with language feature memorization" is what we call "unemployed", not "relatively unproductive".

Re: AI adoption and Solow's productivity paradox

#213

Post by autoexec »

calvinmorrison wrote: post #66
crazygringo wrote: post #21

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…

> it's helping lots of people, but it's also costing an extraordinary amount of money Is it fair to say that wall street is betting America's collective pensions on AI...

They're betting a lot more than that, but since all their chips are externalities they don't care.

Re: AI adoption and Solow's productivity paradox

#214

Post by g-mork »

lqstuart wrote: post #184

I was in the “AI is grossly overhyped” camp because I work on large distributed deep learning training jobs and AI is indeed worthless for those, and will likely always be worthless since the APIs change constantly and the iteration loop is too cumbersome to constantly resubmit broken jobs to a training cluster. Then I started working on some basic grpc/fullstack crap that I absolutely do not care about, at all, but…

this weirdly skirts my own experience yet somehow still read like sarcasm hehe. I think if we just return to calling it intelligent autocomplete expectations for productivity gain would be better established.

trying to hacksmash Claude into outputting something it simply can't just produces endless mess. or getting into a fight pointing out issues with what it's doing and it just piles on extra layer upon layer of gunk. but meanwhile if you ask it to boilerplate an entire SaaS around the hard part, it's done in about 15 seconds.

of course this says nothing about the costs of long term maintainability, and I think everyone by now recognises what that's going to look like

Re: AI adoption and Solow's productivity paradox

#215

Post by transcriptase »

throwawaysleep wrote: post #18
SilverElfin wrote: post #14

These surveys don’t make sense. Ask the forward thinking companies and they’ll say the opposite. The flood of anti AI productivity articles almost feel like they’re meant to lull the population into not seeing what’s about to happen to employment.

Eh, try using Microsoft Copilot in Word or PowerPoint. It is worthless. If your experience with AI was a Microsoft product, you would think it was a scam too.

It’s comical that Microsoft inserted Copilot buttons throughout all of their productivity suite, and none of them are able to do the bare minimum that you would hope for.

“Oh cool, copilot is in excel! I’m going to ask it a question about the data in the spreadsheet that it’s literally appearing beside natively in-app, or for help with a formula!”

“Wait what, it’s saying it can’t see anything or read from the currently displayed worksheet? Why is it inside the application then? Why would I want an outdated version of ChatGPT with no useful context or ability to read/do anything inside all my Office applications?”

Re: AI adoption and Solow's productivity paradox

#216

Post by autoexec »

yalogin wrote: post #127

Every technology, whether it improved existing systems and productivity or not, created new wealth by creating new services and experiences. So that is what needs to happen with this wave as well.

If nothing else AI is making great strides in surveillance. It makes mistakes, but that only matters when there's accountability, and now it can make them at scales that were unthinkable before. Most of us are not going to enjoy the new experiences AI brings us, but a small number of people are already making a lot of money selling new services to government and law enforcement.

Re: AI adoption and Solow's productivity paradox

#217

Post by lukaslalinsky »

There was a recent post where someone said AI allows them to start and finish projects. And I find that exactly true. AI agents are helpful for starting proof of concepts. And for doing finishing fixes to an established codebase. For a lot of the work in the middle, I can be still useful, but the developer is more important there.

Re: AI adoption and Solow's productivity paradox

#218

Post by tabs_or_spaces »

My experience has been

* If I don't know how to do something, llms can get me started really fast. Basically it distills the time taken to research something to a small amount.

* if I know something well, I find myself trying to guide the llm to make the best decisions. I haven't reached the state of completely letting go and trusting the llm yet, because the llm doesn't make good long term decisions

* when working alone, I see the biggest productivity boost in ai and where I can get things done.

* when working in a team, llms are not useful at all and can sometimes be a bottleneck. Not everyone uses llms the same, sharing context as a team is way harder than it should be. People don't want to collaborate. People can't communicate properly.

* so for me, solo engineers or really small teams benefit the most from llms. Larger teams and organizations will struggle because there's simply too much human overheads to overcome. This is currently matching what I'm seeing in posts these days

Re: AI adoption and Solow's productivity paradox

#219

Post by wiseowise »

mrtksn wrote: post #165
whynotminot wrote: post #143

Earlier quoted context omitted.

It’s also pretty wild to me how people still don’t really even know how to use it. On hacker news, a very tech literate place, I see people thinking modern AI models can’t generate working code. The other day in real life I was talking to a friend of mine about ChatGPT. They didn’t know you needed to turn on “thinking” to get higher quality results. This is a technical person who has worked at Amazon. You can’t expec…

In a WhatsApp group full of doctors, managers, journalist and engineers (including software) in age of 30-60 I asked if anyone heard of openclaw and only 3 people heard of it from influencers, none used it. But from my social feed the impression was that it is taking over the world:) I asked it because I am building something similar since some tome and I thought its over they were faster than me but as it appears th…

> I asked if anyone heard of twitter vaporware and only 3 people heard of it from influencers, none used it.

Shocking results, I say!

Re: AI adoption and Solow's productivity paradox

#220

Post by busterarm »

nradov wrote: post #133
abraxas wrote: 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.

Bullshit Jobs is one of those "just so" stories that seems truthy but doesn't stand up to any critical evaluation. Companies are obviously not hesitant to lay off unproductive workers. While in large enterprises there is some level of empire building where managers hire more workers than necessary just to inflate their own importance, in the long run those businesses fall to leaner competitors.

It's only after decades of experience and hindsight that you realize that a lot of the important work we spend our time on has extremely limited long-term value.

Maybe you're lucky enough to be doing cutting edge research or do something that really seriously impacts human beings, but I've done plenty of "mission critical right fucking now" work that a week from now (or even hours from now, when I worked for a content marketing business) is beyond irrelevant. It's an amazing thing watching marketing types set money on fire burning super expensive developer time (but salaried, so they discount the cost to zero) just to make their campaigns like 2-3% more efficient.

I've intentionally sat on plenty of projects that somebody was pushing really hard for because they thought it was the absolute right necessary thing at the time and the stakeholder realized was pointless/worthless after a good long shit and shower. This one move has saved literally man years of work to be done and IMO is the #1 most important skill people need to learn ("when to just do nothing").

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