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AI adoption and Solow's productivity paradox

• virgildotcodes 8mo ago
  https://archive.is/L70Ha https://archive.is/L70Ha
• DaedalusII 8mo ago
  If you include microsoft copilot trials in fortune 500s, absolutely. A lot of major listed companies are still oblivious to the functionality of AI, their senior management don't even use it out of laziness
  • jeron 8mo ago
    it turns out it's really hard to get a man to fish with a pole when you don't teach them how to use the reel
    • throwawaysleep 8mo ago
      Or give them a stick with twine and a plastic fork as a hook, as is the case with Copilot.
    • Banditoz 8mo ago
      If AGI is coming, won't there just be autofishers and no one will ever have to fish again, completely devaluing one's fishing knowledge and the effort put in to learn it?
      • moregrist 8mo ago
        It’s not a great analogy but... “Autofishers” are large boats with nets that bring in fish in vast quantities that you then buy at a wholesale market, a supermarket a bit later, or they flash freeze and sell it to you over the next 6-9 months. Yet there’s still a thriving industry selling fishing gear. Because people like to fish. And because you can rarely buy fish as fresh as what you catch yourself. Again, it’s not a great analogy, but I dunno. I doubt AGI, if it does come, will end up working the way people think it will.
      • tsukurimashou 8mo ago
        > If AGI is coming spoiler, it's not
        • citrin_ru 8mo ago
          Evey now model is better than a previous one. When and why it is going to stop? Current models are limited by DC capacity which is rapidly expanded. Genuinely curious, I don't know the answer.
    • conductr 8mo ago
      In regards to copilot, they’ve also been led on a fishing expedition to the middle of a desert
    • onorton 8mo ago
      I'm not sure if this was the intention of the analogy, but fishing poles don't have reels.
  • chaos_emergent 8mo ago
    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 benefiting from the productive gains of these systems.
    • dboreham 8mo ago
      This isn't my experience. I see many non-software people using AI regularly. What you may be seeing is more: organizations with no incentive to do things better never did anything to do things better. AI is no different. They were never doing things better with pencil and paper.
    • DaedalusII 8mo ago
      I think anthropic will succeed immensely here because when integrated with Microsoft365 and especially Excel it basically does what co-pilot said it would do. The moment of realisation happen for a lot of normoid business people when they see claude make a DCF spreadsheet or search emails claude is also smart because it visually shows the user as it resizes the columns, changes colours, etc. Seeing the computer do things makes the normoid SEE the AI despite it being much slower
      • sheeshkebab 8mo ago
        No one wants a chatbot “integrated” with excel and office365 crap, it’s clippy 2.0 bullshit. Replace excel and office stuff with ai model entirely then people will pay attention.
        • DaedalusII 8mo ago
          that only works if you can oneshot. but nobody can oneshot. iterating over work in excel and seeing it update correctly is exactly what people want. If they get it working in MSWord it will pick up even faster. If the average office worker can get the benefit of AI by installing an add-on into the same office software they have been using since 2000 (the entire professional career of anyone under the age of 45), then they will do so. its also really easy to sell to companies because they dont have to redesign their teams or software stack, or even train people that much. the board can easily agree to budget $20 a head for claude pro the other thing normies like is they can put in huge legacy spreadsheets and find all the errors Microsoft365 has 400 million paid seats
  • bccdee 8mo ago
    There's a lot of rote work in software development that's well-suited to LLM automation, but I think a lot of us overestimate the actual usefulness of a chatbot to the average white-collar worker. What's the point of making Copilot compose an email when your prompt would be longer than the email itself? You can tell ChatGPT to make you a slide deck, but slide decks are already super simple to make. You can use an LLM as a search engine, but we already have search engines. People sometimes talk about using a chatbot to brainstorm, but that seems redundant when you could simply think, free from the burden of explaining yourself to a chatbot. LLMs are impressive and flexible tools, but people expect them to be transformative, and they're only transformative in narrow ways. The places they shine are quite low-level: transcription, translation, image recognition, search, solving clearly specified problems using well-known APIs, etc. There's value in these, but I'm not seeing the sort of universal accelerant that some people are anticipating.
  • bandrami 8mo ago
    That's probably true for some, but I think a lot of big orgs are simply risk-averse and see AI in general as a giant risk that isn't even fully baked enough to quantify yet. The security and confidentiality issues alone will make Operations hesitant, and Legal probably has some questions about IP (both the risk of a model outputting patented or otherwise protected code, and the huge legal gray area that is the copyrightability of the output of an LLM). Give it a year or two and let things settle down and (assuming the music is still playing at that time) you might see more dinosaurs start to wander this way.
• tehjoker 8mo ago
  There is probably a threshold effect above which the technology begins to be very useful for production (other than faking school assignments, one-off-scripts, spam, language translation, and political propaganda), but I guess we're not there yet. I'm not counting out the possibility of researchers finding a way to add long term memory or stronger reasoning abilities, which would change the game in a very disorienting way, but that would likely mean a change of architecture or a very capable hybrid tool.
  • DaedalusII 8mo ago
    the greatest step change will be when mainstream business realise they can use AI to accurately fill in PDF documents with information in any format filling in pdf documents is effectively the job of millions of people around the world
    • oblio 8mo ago
      That would require accurate validation of said documents, which is extremely hard now. Pointing 1 million PDF LLM machine guns at current validation pipelines will not end well, especially since LLMs are inherently unreliable.
      • coffeefirst 8mo ago
        This is lost on people. A 98% accurate automation is useful if you can programmatically identify the 2% of cases that need human review. If you can’t, and it matters, then every case needs human review. So you lose a lot of benefits to the time sync, but since people tend to have their eye glaze over when the correction rate is low, you may still miss the 2% anyway. This is going to put a stop to a lot of ideas that sound reasonable on paper.
• bubblewand 8mo ago
  My company’s behind the curve, just got nudged today that I should make sure my AI use numbers aren’t low enough to stand out or I may have a bad time. Reckon we’re minimum six months from “oh whoops that was a waste of money”, maybe even a year. (Unless the AI market very publicly crashes first)
  • mr_toad 8mo ago
    So management basically have no clue and want you to figure out how to use AI? Do they also make you write your own performance review and set your own objectives?
    • datenyan 8mo ago
      > So management basically have no clue and want you to figure out how to use AI? This is basically the same story I have heard both my own place of employment and also from a number of friends. There is a "need" for AI usage, even if the value proposition is undefined (or, as I would expect, non-existent) for most businesses.
    • fn-mote 8mo ago
      Look, to make something productive out of it: a job seeker who has high level skills using LLM assistance will be much more valuable than one without the experience. Never mind your current company mangement's policies.
    • SoftTalker 8mo ago
      > Do they also make you write your own performance review and set your own objectives? Not to get off on a tangent but this has got to be a "tell" for how much a company is managed by formula and how much it's actually got thinking people running things. Every time I've had to write my own review I fill out the form with some corporatese bullshit, my supervisor approves it and adds some more bullshit, it disappears into HR and I never hear anything about it until it's time for the next review, and it starts over again. There isn't even reference to any of my "objectives" from the last review, because that review has simply disappeared. But I'm sure some HR exec is checking boxes for following "best practices" in employee evaluation.
• Herring 8mo ago
  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.
  • Haven880 8mo ago
    I think both. Most organizatuons lack someone like Steve Jobs to prime their product lines. Microsoft is a good example where you see their products over the years are mostly meh. Then meetings are pervasive and even more so in most companies due to msteam convenience. But currently they faced reduced demands due softer market as compare 2-3 years ago. If you observed that no effect while they layoff many and revenue still hold or at least no negative growth, I would surmise that AI is helping. But in corporate, it only counta if directly contributed sales numbers.
  • amrocha 8mo ago
    Then where are all the amazing open source programs written by individuals by themselves? Where are all the small businesses supposedly assisted by AI?
    • Herring 8mo ago
      > 4% of GitHub public commits are being authored by Claude Code right now. At the current trajectory, we believe that Claude Code will be 20%+ of all daily commits by the end of 2026. https://newsletter.semianalysis.com/p/claude-code-is-the-inflection-point https://newsletter.semianalysis.com/p/claude-code-is-the-inf...
      • amrocha 8mo ago
        There’s lots of slop out there, that doesn’t mean it’s actually good or useful code.
        • 8mo ago
• sebmellen 8mo ago
  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 business/bullshit job (ala Graeber) work is meeting with people, “aligning expectations”, getting consensus, making slides/decks to communicate those thoughts, thinking about market positioning, etc. Maybe tools like Cowork can help to find files, identify tickets, pull in information, write Excel formulas, etc. What’s different about coding is no one actually cares about code as output from a business standpoint. The code is the end destination for decided business processes. I think, for that reason, that code is uniquely well adapted to LLM takeover. But I’m not so sure about other white-collar jobs. If anything, AI tooling just makes everyone move faster. But an LLM automating a new feature release and drafting a press release and hopping on a sales call to sell the product is (IMO) further off than turning a detailed prompt into a fully functional codebase autonomously.
  • DaedalusII 8mo ago
    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 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 automated stock broking. This will reduce the average RIA fee from 1% per year to 0.20% or even 0.10% per year just like mutual fund fees dropped in the early 00s
    • arctic-true 8mo ago
      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.
• maininformer 8mo ago
  Thousand of companies to be replaced by leaner counterparts that learned to use AI towards greater employment and productivity
  • LunaSea 8mo ago
    Where are my LLM-crafted Google and Instagram?
    • maininformer 8mo ago
      Not part if the thousands
• SilverElfin 8mo ago
  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.
  • throwawaysleep 8mo ago
    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.
    • yoyohello13 8mo ago
      Yeah Microsoft has consistently been bragging about how so much code is written by AI, yet their products are worse than ever. Seems to indicate “using AI” is not enough. You have to be smart about when and where.
    • conductr 8mo ago
      It’s not just that though. You find when going through AI projects in an organization that many times the process is manual for a reason. This isn’t the first wave of “automation” that’s came through. Most things that can be fully automated already have been long ago and they manual parts get sold as we can make AI do it, until you see the specs and noodle around on the problem some then you realize it’s probably just going to remain manual as the amount of model training requires as much time and effort as just doing it by hand.
      • sebmellen 8mo ago
        I have a dystopian future vision where humans are cheaper machines than robots, so we become the disposable task force for grunt work that robots aren’t cheap enough for. To some degree this is already happening.
    • transcriptase 8mo ago
      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?”
• pram 8mo ago
  It’s funny because at work we have paid Codex and Claude but I rarely find a use for it, yet I pay for the $200 Max plan for personal stuff and will use it for hours! So I’m not even in the “it’s useless” camp, but it’s frankly only situationally useful outside of new greenfield stuff. Maybe that is the problem?
  • fourthark 8mo ago
    Why do you find it useless for legacy code? I find I have to give it plenty of context but it does pretty well on legacy code. And Ask DeepWiki is a great shortcut for finding the right context… Granted this is open source and DW is free. Is it the specific nature of your work?
• crazygringo 8mo ago
  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 benefit to the economy overall. The reason is that investing in IT was very expensive, there were lots of wasted efforts, and it took a long time for the benefits to outweigh the costs across the entire economy. And so we should expect AI to look the same -- it's helping lots of people, but it's also costing an extraordinary amount of money, and the few people it's helping is currently at least outweighed by the people wasting time with it and its expense. But, we should recognize that it's very early days, and that productivity will rise with time, and costs will come down, as we learn to integrate it with best practices. [1] https://en.wikipedia.org/wiki/Productivity_paradox https://en.wikipedia.org/wiki/Productivity_paradox
  • kamaal 8mo ago
    One part of the system moving fast doesn't change the speed of the system all that much. The thing to note is, verifying if something got done is harder and takes time in the same ballpark as doing the work. If people are serious about AI productivity, lets start by addressing how we can verify program correctness quickly. Everything else is just a Ferrari between two traffic red lights.
    • hawaiianbrah 8mo ago
      Really? I disagree that verifying is as hard as doing the work yourself. It’s like P != NP.
  • torben-friis 8mo ago
    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 I think there are enough short term supposed benefits that something should be showing there.
• istillcantcode 8mo ago
  Anyone read the goal lately?
• cmiles8 8mo ago
  I like AI and use it daily, but this bubble can’t pop soon enough so we can all return to normally scheduled programming. CEOs are now on the downside of the hype curve. They went from “Get me some of that AI!” after first hearing about it, to “Why are we not seeing any savings? Shut this boondoggle down!” now that we’re a few years into bubble, the business math isn’t working, and they only see burning piles of cash.
  • boxedemp 8mo ago
    I consume a lot of different content on a lot of different places. Every site or app has its vibe and communal beliefs. They rarely if ever agree on anything, but they all agree we're in a massive bubble. I don't have a point, just that it's an unlikely unity.
  • sowbug 8mo ago
    "return to normally scheduled programming" is probably not the exact phrasing you want to use. :)
  • topocite 8mo ago
    This is the standard stupidity here based on emotion and denial. This is the narrative that people want to hear. Of course, trying to automate with chatGPT 4o was stupid. Trying to automate with Sonnet 4.6 will work better. Trying to automate with the models a year from now will work all the better. To believe we are going to stop and go back to 2019 at this stage is seriously delusional. I wish it were true. I would love to go back to 2019 but we obviously are not. We never go backwards.
    • cmiles8 8mo ago
      “Regularly scheduled programming” includes progress, not stasis. It just means the AI hype firehouse runs out of money and we rerun to normal sane progress and productivity enhancements without all the overpricing and under delivering of the last few years.
• n_u 8mo ago
  Original paper https://www.nber.org/system/files/working_papers/w34836/w34836.pdf https://www.nber.org/system/files/working_papers/w34836/w348... Figure A6 on page 45: Current and expected AI adoption by industry Figure A11 on page 51: Realised and expected impacts of AI on employment by industry Figure A12 on page 52: Realised and expected impacts of AI on productivity by industry These seem to roughly line up with my expectations that the more customer facing or physical product your industry is, the lower the usage and impact of AI. (construction, retail) A little bit surprising is "Accom & Food" being 4th highest for productivity impact in A12. I wonder how they are using it.
  • CSSer 8mo ago
    Figure right after A6 is pretty striking. Ask people if they expect to use AI and a vast majority say yes. Ask if they expect to use AI for specific applications and no more than a third say yes in any industry. That should be telling imo. What we have is a tool that looks impressive to any non-SME for a lot of applications. I would caution against the idea that benefits are obvious.
• carefree-bob 8mo ago
  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 https://www.frbsf.org/wp-content/uploads/crafts.pdf
  • robinwhg 8mo ago
    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.
    • efreak 8mo ago
      On the contrary, this was actually used for something. The aeliopile is quite a bit older and was used for precisely nothing.
• beloch 8mo ago
  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 law was relentless. The exponential growth phase of the J-curve for AI, if there is one, is going to be heavily damped by the enshitification phase of the winning AI companies. They are currently incurring massive debt in order to gain an edge on their competition. Whatever companies are left standing in a couple of years are going to have to raise the funds to service and pay back that debt. The investment required to compete in AI is so massive that cheaper competition may not arise, and a small number of (or single) winner could put anyone dependent on AI into a financial bind. Will growth really be exponential if this happens and the benefits aren't clearly worth it? The best possible outcome may be for the bubble to pop, the current batch of AI companies to go bankrupt, and for AI capability to be built back better and cheaper as computation becomes cheaper.
  • robinwhg 8mo ago
    But there already is cheaper competition? Open models may be behind, but only ~6 months for every new generation.
• rr808 8mo ago
  BTW the study was from September 2024 to 2025, so its the very earliest of adopters.
  • hydrox24 8mo ago
    This article is mostly based on NBER working paper 34836, which was published this month, and the data was collected from September 2025 to January 2026[0] [0]: See page 2: https://www.nber.org/system/files/working_papers/w34836/w34836.pdf https://www.nber.org/system/files/working_papers/w34836/w348...
• pengaru 8mo ago
  At $dayjob GenAI has been shoved into every workflow and it's a constant source of noise and irritation, slop galore. I'm so close to walking away from the industry to resume being a mechanic, what a complete shit show.
  • bitwize 8mo ago
    Meanwhile in some auto shop, "Perfect! Let's delve into the problem with the engine. Based on the symptoms you describe, the likely cause is a blown head gasket..."
• deadbabe 8mo ago
  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.
  • boxedemp 8mo ago
    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.
    • deadbabe 8mo ago
      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.
• kittbuilds 8mo ago
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• J_Shelby_J 8mo ago
  It’s simple calculus for business leaders: admit they’re laying off workers because the fundamentals are bad and spook investors, admit they’re laying off workers because the economy is bad and anger the administration, or just say it’s AI making roles unnecessary and hope for the best.
• acjohnson55 8mo ago
  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.
  • azuanrb 8mo ago
    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.
    • acjohnson55 8mo ago
      Fair point. What it really does for me is give me a better UX for having a bunch of parallel workstreams. I could achieve a similar effect thing with scripting, and maybe some clever ways of getting something like the sidebar for seeing the status of everything on a single pane. But Conductor packaged it up in a way that I found much improved over multiple Cursor or VSCode windows.
• nowittyusername 8mo ago
  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....
• 1broseidon 8mo ago
  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.
• ahepp 8mo ago
  I read an article in FT just a couple days ago claiming that increased productivity was becoming visible in economic data > My own updated analysis suggests a US productivity increase of roughly 2.7 per cent for 2025. This is a near doubling from the sluggish 1.4 per cent annual average that characterised the past decade. good for 3 clicks: https://giftarticle.ft.com/giftarticle/actions/redeem/97861f54-87a9-4124-896e-7efe522dee56 https://giftarticle.ft.com/giftarticle/actions/redeem/97861f...
• chrismarlow9 8mo ago
  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.
  • bunderbunder 8mo ago
    And, hear me out here - perhaps for the sake of morale it makes sense to leave a smidge of the part of the job that actually attracts people to this profession in the first place on their plates. Otherwise we may find that, after the novelty wears off, we’re left with a net productivity dropoff because there’s not as much left to keep people motivated to do à good job of the remaining work.
• AngryData 8mo ago
  I think the biggest problem is calling it AI to start with. It gives people a huge misrepresentation of what it is actually capable of. It is an impressive tool with many uses, but it is not AGI.
• jurschreuder 8mo ago
  Workers may see the LLM as a productivity boost because they can basically cheat a their homework. As a CEO I see it as a massive clog up of vast amounts of content that somebody will need to check. A DDoS of any text-based system. The other day I got a document of 155 pages in Whatsapp. Thanx. Same with pull requests. Who will check all this?
  • huflungdung 8mo ago
    [dead]
  • beart 8mo ago
    > Who will check all this? The answer to that, for some, is more AI. I had a peer explain that the PRs created by AI are now too large and difficult to understand. They were concerned that bugs would crop up after merging the code. Their solution, was to use another AI to review the code... However, this did not solve the problem of not knowing what the code does. They had a solution for that as well... ask AI to prepare a quiz and then deliver it to the engineer to check their understanding of the code. The question was asked - does using AI mean best-practices should no longer be followed? There were some in the conversation who answered, "probably yes". > Who will check all this? So yeah, I think the real answer to that is... no one.
  • thisoneisreal 8mo ago
    Just yesterday one of my junior devs got an 800-line code review from an AI agent. It wasn't all bad, but is this kid literally going to have to read an essay every time he submits code?
    • jurschreuder 8mo ago
      Yes it's like "double it and pass it to the next developer". Even more troublesome is importing libraries. I have no idea which ones are AI generated and they are better and better at hiding their original authors.
  • franktankbank 8mo ago
    Who gave you the 155 page doc? How quickly were they fired?
• yalogin 8mo ago
  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.
  • autoexec 8mo ago
    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.
• an-allen 8mo ago
  Yep just a risk amplifier. We are having a global warming level event in computing and blindly walling into it.
• ruddsky 8mo ago
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  • signa11 8mo ago
    and how do you know it is not going to be an inverted j-curve ?
    • ruddsky 8mo ago
      Ha ha. I suppose an inverted j curve technology would offer short term productivity but yield long term slow-downs. I can see aspects of that - perhaps using agents people write code that quickly adds the next feature but overall is not maintainable. Or they quickly write a project plan but in the long term it doesn’t result in good payoffs. I’ve already observed both of these. I think the hardest part to figure out will be delineating the illusion of productivity from actual productivity. In the other hand - we do have empirical research (from the economist in this article) even from 2023 showing LLMs ability to offer real productivity in certain tasks : https://www.nber.org/papers/w31161 https://www.nber.org/papers/w31161. And the models have become much more better since then. So it’s probably a question of if we can use them for what they are good for without being lulled by the sirens song of fake productivity.
• deleted 8mo ago
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• matt3210 8mo ago
  I’m not sure about this. I’ve been 100% ai since jan/1 and I’m way more productive at producing code. The non code parts (about 90% of the work) is taking the same amount of time though.
• lqstuart 8mo ago
  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 needs to be done and uses internal frameworks that are not well documented, and now Claude is my best friend at work. The best part is everyone else’s AI code still sucks, because they ask it to do stupid crap and don’t apply any critical thinking skills to it, so I just tell AI to re-do it but don’t fuck up the error handling and use constants instead of hardcoding strings like a middle schooler, and now I’m a 100x developer fearlessly leading the charge to usher in the AI era as I play the new No Man’s Sky update on my other PC and wait for whatever agent to finish crap.
  • g-mork 8mo ago
    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
    • lqstuart 8mo ago
      We just haven’t figured out how to use it. You wouldn’t try to create an entire project out of IDE templates, but how many “low code” attempts were there to do just that at some point? I think there are phases in a project’s lifecycle where it’s more appropriate, at the very beginning and very late. I do not think junior developers should be using it, because it is much much harder to learn and it kills productivity having senior developers review 3000 lines of slop. Just stuff like that needs to be figured out.
• johnnienaked 8mo ago
  The issue with framing this as a resurrection of the productivity paradox is that AI had never even theoretically increased productivity. I think in retrospect it's going to look very silly.
• casey2 8mo ago
  Of course AI is bullshit. If you couldn't just use it yourself and figure that out then ask yourself why people like Bezos or Altman are perfectly happy "investing" other people's money but not their own. If they actually believed their own bullshit they would personally be investing all of their money AND taking on personal debt. Instead Bezos, a guy worth ~200B, sells 5B worth of stock to invest in "AI-adjacent" (power generation) industry, while making amazon invest 200B in data centers. Talk about conflict of interest! WTF!
• transcriptase 8mo ago
  Mentioning AI in an earnings call means fuck all when what they’re actually referring to is toggling on the permissions for borderline useless copilot features across their enterprise 365 deployments or being convinced to buy some tool that’s actually just a wrapper around API calls to a cheap/outdated OpenAI model with a hidden system prompt. Yeah, if your Fortune 500 workplace is claiming to be leveraging AI because it has a few dozen relatively tech illiterate employees using it to write their em dash/emoji riddled emails about wellness sessions and teams invites for trivia events… there’s not going to be a noticeable uptick in productivity. The real productivity comes from tooling that no sufficiently risk adverse pubco IS department is going to let their employees use, because when all of their incentives point to saying no to installing anything ever, the idea of giving the permissions required for agentic AI to do anything useful is a non-starter.
• lukaslalinsky 8mo ago
  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.
• tabs_or_spaces 8mo ago
  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
  • aurareturn 8mo ago
    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 explosive software production, not from big tech but from small companies. I don't think this will only apply to the software industry. I expect this to apply to every industry.
    • itake 8mo ago
      yeah, I agree. When Engineering Budget Managers see their AI bills rising, they will fire the bottom 5-10% every 6-12 months and increase the AI assistant budget for the high performers, giving them even more leverage.
      • aurareturn 8mo ago
        In my case, over the last 3 years, every dev who left was not replaced. We are doing more than ever. Our team shrunk by 50% but we are serving 200% more customers. Every time a dev left, we thought we're screwed. We just leveraged AI more and more. We are also serving our customers better too with higher retention rates. When we onboard a customer with custom demands, we used to have meetings about the ROI. Now we just build the custom demands in the time we took to meet to discuss whether we should even do it. Today, I maintain a few repos critical to the business without even knowing the programming language they are written in. The original developers left the company. All I know is what is suppose to go into the service and what is suppose to come out. When there is a bug, I ask the AI why. The AI almost always finds it. When I need to change something, I double and triple check the logic and I know how to test the changes. No, a normal person without a background in software engineering can't do this. That's why I still have a job. But how I spend my time as a software engineer has changed drastically and so has my productivity. When a software dev say AI doesn't increase their productivity, it truly does feel like they're using it wrong or don't know how to use it.
• trappist 8mo ago
  "Admitted" as the verb in a statement like this is blatant editorialization. Did they just finally "admit" what they had been reluctant to reveal? No doubt with their heads hung in shame? Maybe this bothers me more than it should.
• brutalc 8mo ago
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• Arifcodes 8mo ago
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• VerifiedReports 8mo ago
  "What had promised to be a boom to workplace productivity.." No. BOON. A BOON to workplace productivity. And then the writer doubles down on the error by proving it was not a typo, ending the sentence with "...was for several years a bust."
  • VerifiedReports 8mo ago
    Yes, downvote facts.
• jillesvangurp 8mo ago
  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.
• enraged_camel 8mo ago
  This study spans 3 years, so it goes back to ChatGPT 3.5 era. Not sure how valid it is, considering the breakneck speed at which everything moves.
• littlecranky67 8mo ago
  I'm saying it over and over, AI is not killing dev jobs, offshoring is. The AI hype happens to fall into the end of the pandemic, and lots of companies went to work-from-home and are now hiring cheaper devs around the world.
• alexwennerberg 8mo ago
  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.
  • vjk800 8mo ago
    Indeed. Most large companies don't need AI to increase productivity - they just need to stop wasting time on stupid bullshit. However, figuring out what is stupid bullshit and what is not seems to be an impossible task, and I don't think AI is going to help here at all.
    • psychoslave 8mo ago
      What are you talking about, if there is one thing on which LLM shine, it’s generating vast amount of bullshit. That’s extreme productivity gains. Also flame-wars can be autofed ad nauseam now, so there’s going to be less and less interest in engaging into them. In an act of desperation, idle trolls will turn to tasks tracked by KPIs.
• d--b 8mo ago
  CEOs have no clue what's going on at the IC level. I bet many CEO PA are using AI for many tasks. It's typically a role where AI is very useful. Answering emails, moving meetings around, booking and buying a bunch of crap.
  • bandrami 8mo ago
    I ask this as a genuine question: who needs help "answering emails" and what part of it do they need help with?
    • d--b 8mo ago
      A lot of people obsess over phrasing. Like for instance you want to tell a coworker his work is shit, but don't know how to put it in a way that's not going hurt them or make you look like an asshole. I know people who'd potentially spend hours on a single email like this.
• vjk800 8mo ago
  My experience has been that AI is much more useful on my own systems than on company systems. For AI to (currently) be useful, I need to choose my own tooling and LLM models to support AI centered workflow. At work, I have to use whatever (usually Microsoft) tools my company has chosen to purchase and approve for my corporate computer, and usually nothing works as well as on my own machine where I get to set it up as I want.
  • sigmoid10 8mo ago
    What you are describing is a failure to integrate AI into said company systems. I have seen quite a few companies now that buy MS AI products with great hopes only to be severely disappointed, because they may as well have just used vanilla ChatGPT (in fact then they would at least get newer models faster). But there are counter examples too. If you can pull all your company documentation into a vector db and build a RAG based assistant, you can potentially save countless hours across your workforce and possibly customers too. But this is not easy and also requires some level of UI interactivity that noone really offers right now. In fact they can't offer it, because you usually need to integrate ancient, arcane sources into your system. So you do have to write a lot of integration code yourself at every step. Not many companies are willing to spend that kind of money and effort, because managers just want to buy a MS product and be done with improving efficiency by next quarter.
    • mark_l_watson 8mo ago
      I have been using vector based RAG for about two years now, I am not knocking the tech, but last year I started experimenting with going way back in time and also in parallel trying BM25 search (or hybrid BM25 and vector). So: not even a very good example use case of LLMs, the tech is not always applicable. EDIT: I am on a mobile device and don’t have a reference handy but there have been good papers on RAG scaling issues - basically the embedding space gets saturated (too many document chunks cluster in small areas of the embedding space), if my memory is correct.
      • sigmoid10 8mo ago
• builderhq_io 8mo ago
  [flagged]
• hestefisk 8mo ago
  I am in strategy consulting and I can tell you the productivity gains are real in terms of research, model building, and summarising work. The result is price pressure from our clients.
• EastLondonCoder 8mo ago
  I think the deluge on projects on show HN points to something real, its possible today to ship projects as a one man shop that looks like something that just a year or so would have required a team. Personally I have noticed strange effects, where I previously would have reached for a software package to make something or solve an issue, its now often faster for me to write a specific program just for my use case. Just this weekend I needed a reel with a specific look to post on instagram but instead of trying to use something like after effects, i could quickly cobble together a program that was using css transforms that outputted a series of images I could tie together with ffmpeg. About a month ago I was unhappy with the commercial ticketing systems, they were both expensive and opaque so I made my own. Obviously for a case like that you need discipline and testing when you take peoples money, so there was a lot of focus on end to end testing. I have a few more examples like this, but to make this work you need to approach using LLMs with a certain amount of rigour. The hardest part is to prevent drift in the model. There are a certain number things you can do to make the model grounded in reality. When the tool doesn’t have a reproducer, it’ll happily invent a story and you’ll debug the story. If you ground the root cause in for example a test, the model can get context enough to actually solve the problem. Another issue is that you need to read and understand code quickly, but its no real difference from working with other developers. When tests are passing I usually do a PR to myself and then review as I usually would do. A prerequisite is that you need tight specs, but those can also be generated if you are experienced enough. You need enough domain intuition to know what ‘done’ means and what to measure. Personally I think the bottleneck will go from trying to get into a flow state to write solutions to analyze the problem space and verification.
  • lm28469 8mo ago
    > I think the deluge on projects on show HN points to something real, its possible today to ship projects as a one man shop that looks like something that just a year or so would have required a team. Lots of these project have a lifespan of a week and will never ever be maintained. When you pour blood and sweat in a projet you get attached to it, when you vibe code it in an afternoon and it's not and instant hit you move on to the next one.
• Havoc 8mo ago
  I find this difficult to reconcile with things like for example freelance translation being basically wiped out wholesale Or even the simple utility of having a chatbot. They’re not popular because they’re useless Which to me says it’s more likely that people under estimate corporate inertia
• mark_l_watson 8mo ago
  I think the best point made in this conversation is that AI is often enough used to do things quickly that have little value, or just waste people’s time. I am glad to see articles like this that evaluate impact, but I wish the following would get more public interest: With LLMs we are chasing sort-of linear growth in capability at exponential cost increases for power and compute. Were you mad when the government bailed out mis-managed banks? The mother of all government bailouts might be using the US taxpayer to fund idiot companies like Anthropic and OpenAI that are spending $1000 in costs to earn $100. I am starting to feel like the entire industry is lazy: we need fundamental new research in energy and compute efficient AI. I do love seeing non-LLM research efforts and more being done with much smaller task-focused models, but the overall approach we are taking in the USA is f$cking crazy. I fear we are going to lose big-time on this one.
• vagrantstreet 8mo ago
  Perhaps something went wrong along the career path of a developer? Personally during my education there is a severe lack of actual coding done mid lectures, especially any sort of showcase of tools that are available. We didn't even get taught how to use debuggers, I see late year students still struggle how to do basic navigation in a terminal. And the biggest irony is that the "scariest" projects we had at our university ended up being maybe 500-1000 lines of code, things really must go back to hands on programming with real time feedback from a teacher. LLM's only output what you ask and won't really suggest concepts used by professionals unless you go out of your way to ask for it, it all seems like a vicious cycle even though meaningful code blocks can range along 5 to 100 lines which. When I use LLM's I just get information burn out trying to dig through all that info or code
• amelius 8mo ago
  In other words, everybody is benefiting from AI, except CEOs.
• cadamsdotcom 8mo ago
  Many people are using AI as a slot machine, rerolling repeatedly until they get the result they want.. Once the tools help the AI to get feedback on what its first attempt got right and wrong, then we will see the benefits. And the models people use en masse - eg. free tier ChatGPT - need to get to some threshold of capability where they’re able to do really well on the tasks they don’t do well enough on today. There’s a tipping point there where models don’t create more work after they’re used for a task, but we aren’t there yet.
• TimByte 8mo ago
  General-purpose technologies tend to have long and uneven diffusion curves. The hype cycle moves faster than organizational change
• concats 8mo ago
  If we assume people are somewhat rational (big ask I know), and the Efficient-market hypothesis, then we can estimate the value created by AI to be roughly equal to the revenue of these AI companies. That is: A professional who pays 20€/month likely believes that the AI product provides them with roughly 20€ each month in productivity gains, or else they wouldn't be paying, and similarly they would pay more for a bigger subscription if they thought there was more low hanging fruit available to grab. Of course this doesn't take into account people who just pay to play around and learn, non professional use cases, or a few other things, but it's a rough ballpark estimate. Assuming the above, current AI models would only increase the productivity for most workplaces by a relatively small amount, around 10-200 € per employee per month perhaps. Almost indistinguishable compared to salaries and other business expenses.
  • Ukv 8mo ago
    > A professional who pays 20€/month likely believes that the AI product provides them with roughly 20€ each month in productivity gains, or else [...] they would pay more for a bigger subscription Unless I'm misunderstanding, shouldn't someone rational want to pay where (value - cost) is highest, opposed to increasing cost to the point where it equals value (which has diminishing returns)? A $40 subscription creating $1000 worth of value would be preferred over a $200 subscription creating $1100 of value, for instance, and both preferred over a $1200 subscription creating $1200 of value.
    • concats 8mo ago
      True! (value - cost) would be better. I was more so limiting myself to the simpler heuristic where people only pay roughly what they personally think something is worth, and not significantly more/less regardless of the options. But of course, as you've pointed out, in real life the options available really do matter, and someone might decline a 200:1200 trade if there are even more lopsided options available. It does complicate the though experiment somewhat if you try to take this into account.
• emptyfile 8mo ago
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• NVHacker 8mo ago
  Isn't it a bit early to draw such conclusions ? We are just getting started with AI use, especially in tech / engineering teams, and have only scratched the surface with regards to what is possible.
• kittikitti 8mo ago
  [flagged]
• flurdy 8mo ago
  It's the same reason why I have, for more than a decade, been so frustrated with people refusing to consider proper pair programming and even mob programming, as they view the need to keep people busy churning lines of code individually as the most important part of the company. That multiple AI agents can now churn out those lines relatively nearly instantly, and yet project velocity does not go much faster, should start to make people aware that code generation is not actually the crucial cost in time taken to deliver software and projects. I ranted recently that small mob teams with AI agents may be my view of ideal team setup: https://blog.flurdy.com/2026/02/mob-together-when-ai-joins-the-team https://blog.flurdy.com/2026/02/mob-together-when-ai-joins-t...
  • lonelyasacloud 8mo ago
    > ... and yet project velocity does not go much faster 1) The models like us have finite context windows and intelligence, even with good engineering practices system complexity will eventually slow them down. 2) At the moment at least, the code still needs to be reviewed and signed off by us and reading someone else's code is usually harder than writing it.
    • flurdy 8mo ago
      Are people still reading PRs in detail manually? I am after the automated PR agents have all passed a PR I tend to let Claude Code and Codex give me a summary, with an MCP skill to read the requirement story. I trust their ability to catch edge cases and typos more than me. I just check the general structure of the PR
      • flurdy 8mo ago
        I may use my own skill to automate this... https://github.com/flurdy/agent-skills/blob/main/skills/review-pr/SKILL.md https://github.com/flurdy/agent-skills/blob/main/skills/revi...
      • lonelyasacloud 8mo ago
        Anthropic, OpenAI, Google et. al. have EULAs and the best lawyers money can buy ready to argue that any damage done by publicly releasing bad or malicious code produced or reviewed with their systems is the developers responsibility for not checking properly. > I trust their ability to catch edge cases and typos more than me. Given the vendors EULAs etc, if poop really hits the fan with released code, then how is that likely to sound if the lawyers get involved? > Are people still reading PRs in detail manually? Ultimately it all depends on circumstance and appetite for risk, but yes many/most places still manually checking releases.
• spants 8mo ago
  Maybe the CEOs do not realise that their workers are achieving great productivity, completing their tasks in 1 hour instead of 8, and spending time on the beach, rather than at their desks?
  • ssantoshp 8mo ago
    most likely scenario
• crispyambulance 8mo ago
  I accept that AI-mediated productivity might not be what we expect to be. But really, are CEO's the best people to assess productivity? What do they _actually_ use to measure it? Annual reviews? GTFO. Perhaps more importantly, it's not like anything a C-level says can ever be taken at face value when it involved their own business.
  • NoLinkToMe 8mo ago
    The latest company I worked in had your typical fee-earners and fee-burners categories of employees. The fee-earners had KPIs tied to the sales pipeline, from leads to contracts to work completed on fixed contracts or hours billed on variable-rate contracts. It's relatively easy to measure improvements here. Though it's harder to distill the causes of that and tie it to LLMs. The fee-burners like in IT, legal, compliance, marketing, finance, typically had KPIs tied to the department objectives. This stuff is a LOT more subjective and a lot more prone to manipulation (goodhart's law). But if you spend 60 hours a week on work in such a department, you tend to have a pretty good idea if things are speeding up or not at all. In a department I was involved in there was a lot of KYC that involved reviewing 300+ pages per case, we tracked case workload per person per day, as well as success rates (percentage of case reviews completed correctly), and could see meaningful changes one could attribute to LLM use. Agreed though that I'm more interested in a few case studies in detail to understand how they actually measured productivity.
  • gjk3 8mo ago
    Most CEOs of large firms arent all that involved in the details, so theres no way they can have a true and proper view of the day-to-day operations on the ground level. Steve Jobs is the only CEO of a large firm that I can re-call that always remained intimately involved.
• squeefers 8mo ago
  thank goodness! our jobs are safe lads!!
• hsuduebc2 8mo ago
  https://archive.is/t5Wxz https://archive.is/t5Wxz
• metalman 8mo ago
  As a small bespoke manufactuter of things made out of metal, I have recently begun implimenting a policy of abandoning most online services, including banking, well almost as customers can still send me money online, but I have to go to a branch to see or get funds, except for monthly reports. It is awsome, the web brings me customers via 2 web sites, and searches useing AI, but the whole thing is asymetrical, as it has been more than a year since my last online purchase or filling out a form, aplication etc, all done on paper, in person, or I live without whatever it is. The result is a work environment that is focused on customers and production, and external obligations, requirements are litteral, as they must be managed efficiently in person and in such a way as to be finnished or stable, none of the death by 1000 emails brain rot. The mental state of haveing zero knowledge of what is happening on a millisecond by millisecond basis and letting everything go, and lo the world grinds on just fine without me, and I get a few things done. Mr Solow called it long ago, and my intuition has always been that the busy work was shit, and have now proven that in my one specific circumstance.
• steveBK123 8mo ago
  I think we are entering the phase where corporate is expecting more ROI than they are getting, but want to remain in the arms race. The firmwide AI guru at my shop who sends out weekly usage metrics and release notes started mentioning cost only in the last few weeks. At first it was just about engaging with individual business heads on setting budgets / rules and slowing the cost growth rate. A few weeks later and he is mentioning automated cost reporting, model downgrading and circuit breaking at a per-user level. The daily spend where you immediately get locked within 24 hours is pretty low.
  • dranudin 8mo ago
    I noticed something similar at my work. The CEO is hyping AI, but at the same time free access to the big models was taken away and rate limits seem to be much tighter..
• rsynnott 8mo ago
  Look, that's hardly the point, now, is it, CEOs? AI, or at least saying "AI" a lot, makes number go up.
• himata4113 8mo ago
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• izucken 8mo ago
  At my current job I am in deep net LOC negative despite all new features... Somebody is getting fired and sued for stealing all these LOCs from the company...
• DivingForGold 8mo ago
  Mirror: https://archive.ph/tAUFb https://archive.ph/tAUFb
• nivcmo 8mo ago
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• seyz 8mo ago
  Including 999 using Copilot.
• RegW 8mo ago
  Productivity is a moveable feast and tricky to compare with the past. The productivity business talk about is the ratio of cost to profit. As tech become available to help reduce your costs and drive up your profit, the same tech also reduces your competitor's costs and perhaps lets more competitors into the market. This drives down your product prices and reduces your profit. So you invest but see no increase in productivity, but if you don't do it - you're toast.
• saezbaldo 8mo ago
  One underexplored reason: companies can't give AI agents real authority. The moment an agent needs to do anything beyond summarizing text — update a CRM, transfer funds, modify infrastructure — the security question kills it. No one wants an agent that can take irreversible actions with no approval chain. Until the trust architecture problem is solved, AI stays in read-only mode for most enterprises.
  • plaidfuji 8mo ago
    This is the biggest bottleneck. To realize the “replacement of white collar workers” fever dream, (which is, I still believe, technically feasible), you need the agent that replaces them to have all of the context they had. All of the emails, all of the Slacks, all of the meeting minutes, access to private corporate systems and files, etc. I can’t think of a single company that would want to turn all of that over to OpenAI.
    • bdangubic 8mo ago
      > I can’t think of a single company that would want to turn all of that over to OpenAI you’d be surprised… the largest IP in the majority of cases is the codebase itself. once that hurdle was crossed the rest is easy decision
• K0balt 8mo ago
  This is because the vast majority of white collar activity in a large corporation produces no direct economic value. Making it easier/better just means more/higher quality “worthless” work is performed. The incentives in the not-directly -productive parts of organizations are to keep busy and maintain a stream of signals of productivity. For this , AI just raises the bar. The 25% of the work that -is- important to producing economic value just gets reduced to 15%. The workforce in large orgs that is most AI adjacent is already idling along in terms of production of direct economic value. Making them 10x more productive in nonproductive work will not impact critical metrics in a short timeframe. It’s worth noting that these “not directly productive” activities actually can (and often do) produce value, eventually. Things like brand identity, culture, and meta-innovation, vision (search-space) are intangibles that present as cost centers but can prove invaluable in longer timescales if done right.
  • ddtaylor 8mo ago
    There are a lot of people who sit with their laptop open while streaming something, sleeping or messing with their phone while periodically waking up to join a new meeting or fiddle with something to make it look like they are active. These are the people "shocked" when they are displaced.
    • gjk3 8mo ago
      There are many reasons why such people might be employed. E.g. preventing a competitor from hoarding talent, so you decide to do it too. Whats taught in economics textbooks doesnt always reflect reality - ha.
  • gjk3 8mo ago
    Principal-agent problem. The manager wants a large team. The shareholder who ultimately employs the manager but does not control operations does not want that of course. Hmm.
• octoclaw 8mo ago
  [dead]
• cowpig 8mo ago
  NVIDIA is doing circular finance deals with all of the top labs to pump up demand for its products and charging a monopoly rate on those products. Everything in computing is costing more. Access to capital for everyone else is dropping. And the US economy is being managed by chaos monkeys, causing all kinds of supply chain disruptions. Oligopolies in almost every market are increasingly jacking up prices above market equilibrium rates as they are emboldened by a corrupted FTC. Despite what Peter Thiel may have led you to believe, Monopolies are not healthy for an economy in aggregate. Of course the economy is slowing.
• giancarlostoro 8mo ago
  I'm not sure how you even measure productivity going up or down, for many of us LLMs have allowed us to trim down the amount of effort required to scour through google search results.
• Ithildin 8mo ago
  If I do something faster by pairing with AI, why should my employer reap the benefit? Why would I pass the savings on to my employer? Could it be that employers are not seeing the difference because most employees are doing something else with the time they've saved by using AI? There's been massive wage stagnation, benefits are crap, they play games with PTO. Most people I talk to who use AI as a part of their workflow are taking advantage of something nice that has come their way for a change.
• JanickSpielmann 8mo ago
  I hope that RAM prices will drop soon as a result. Companies cease to exist; therefore, datacenters are unnecessary.
• des429 8mo ago
  This title is so click bait-y and misleading compared to what the actual article is about it's tough not to feel disappointed this is on the front page. @dang
  • dang 8mo ago
    Belatedly fixed. Thanks! p.s. @dang doesn't work reliably - hn@ycombinator.com is the way to get a message delivered
• DonnyV 8mo ago
  I think the reason tech didn't help productivity until the late 90s is pretty obvious. The internet was missing. Computers needed the internet to make them useful to everyone. So the question should be. What is Ai missing that will make it useful to everyone?
• rybosworld 8mo ago
  Companies over a certain size (say more than 25+ employees), are universally bad at: - measuring productivity - adapting to change This article just reinforces that. Past a certain headcount, executives have little to no understanding of what IC day-to-day is like. AI tooling doesn't fix the bureaucracy the c-suite helped to create.
  • zubiaur 8mo ago
    And there are incentives to miss-report. My team has gained a reputation of being some sort of firefighting crew. We are being called by PMs when projects are failing, usually engineering-data and engineering-adjacent stuff. (Mechanical/Electrical). We automate the heck out the processes, using a mix of AI processing, RAGs, and AI assisted coding. We rescue the projects. Finish ahead of schedule. Make fewer mistakes. We gain additional scope. We win new projects. We bring new clients. But when higher ups ask the people we helped about productivity gains, the most generous will say stuff like "it takes as long to review as it takes to do things manually", "They really helped on {inconsequential part of the deliverable}" If the that is the takeaway these people were taking, they would incredibly misled. Luckily for me, I have people who deal with the politics, while my team can focus on delivery. Our reputation keeps growing, and we keep delivering faster. The heads of the departments we work with love us, the middle rank who were doing the laborious crap, maybe not so much.
• SKILNER 8mo ago
  If you've ever undertaken the task of documenting entire workflows, then you know that you quickly put up the white flag at the word "entire". When you actually talk to people about what they do there are often many, many nuances, micro-events, micro-decisions and micro-actions in their work. This is why it can take days/weeks/months to completely train a new person for a job. This level of detail is barely documented - anywhere. There is a huge amount of information buried in workflows that AI has barely had access to for training. A lot of this is more in the realm of world models, rather than LLMs. So imagine trying to use AI to improve these workflows it knows so little about. Then imagine AI trying to reinvent them across an organization. We find these use cases where AI provides great value - totally true - but these barely scratch the surface of what goes on.
• deleted 8mo ago
  [deleted]
• skeeter2020 8mo ago
  Q: fortune (and a other sites) seem to be posted regularly but they're inevitably paywalled; is this common for others or just me? If it's common why are they posted here?
• yubblegum 8mo ago
  I've sat in a room with a too big to tail banker's VP happily telling me and my boss that "we're getting rid of this whole floor". Dateline ~2010. Location: NYC Why:Indian outsourced shops. Now the zinger, dear hn, is this: He actually said to us (we ran a more boutique consulting firm) that "everything has to be done 3 times" and "their work is crap". But "we're getting rid of this floor". That, imho, was due to geopolitical machinations of inducing India to become part of the West. The immediate equation of "money for quality work" wasn't working but the 'our higher ups' had more grand plans and sacrificing and gutting the IT industry in US was not a problem. So, given the incentives these days, do not remotely pin your hopes on what these CEOs are saying. It means nothing whatsoever.
  • franktankbank 8mo ago
    And India buys russian oil so what exactly is the goal there.
• bob1029 8mo ago
  The analogy that an LLM is simply an amplifier is apt for most general business. If you've already got a very effective team with clear vision/goals, this technology will almost certainly help to some degree. If you've got a sinking ship of a business, this technology will likely drag you down faster. You always have to work backward from the customer into the technology. AI will never change that. I've found myself waffling on advice to some clients regarding AI because whether or not they can effectively leverage it depends more on what the people in the business are willing to do than what the technology can do.
• mulmen 8mo ago
  How do they define productivity? How is it measured?
• 1vuio0pswjnm7 8mo ago
  Erik Brynjolfsson: Productivity is 'Much Higher' Due to AI https://www.wsj.com/video/erik-brynjolfsson-productivity-is-much-higher-due-to-ai/CF9D0538-A797-4088-AFAA-F297ED29B569 https://www.wsj.com/video/erik-brynjolfsson-productivity-is-...
• _slih 8mo ago
  most of these companies deployed microsoft copilot, watched it hallucinate meeting summaries for six months, and called that an AI strategy. source: current situation
• h0ek 8mo ago
  Yeah, maybe the CEO doesn’t see any impact on productivity — but mine definitely changed. I actually have more time for my own stuff now, because AI quietly handles part of the work for me. Of course, if productivity is measured by how many PowerPoint slides get presented to the board, then sure — nothing changed. Especially when HR reports say “everything looks the same” — because no one is tracking how much work is silently being offloaded to AI. And just to avoid overworking myself, I even asked AI to write this comment so I could focus on something else in the meantime.
• qgin 8mo ago
  This may mean the centaur era will be shorter than expected. If we take as a given that: * AI is doing real work * Humans using AI don't seem to get more done with AI than without There is a huge economic pressure to remove humans and just let the AI do the work without them as soon as possible.
  • plaidfuji 8mo ago
    I suspect this may be the case. There’s inherent inefficiency in having a human forced to translate everything into context for the LLM. You don’t get the full benefit until you allow it to be fully plugged in.
• insane_dreamer 8mo ago
  It's not that AI is ineffective, but it will take time to create solutions that are actually highly useful in real-world business scenarios. Quickly slapping "AI features" on a bunch of existing products -- like almost every SW company seems to have done in an effort to appear "on the cutting edge" -- accomplishes almost nothing.
• placebo_effect 8mo ago
  https://archive.ph/tAUFb https://archive.ph/tAUFb
• vagab0nd 8mo ago
  The "productivity gain" in the world of bits has been pretty much exponential for 100 years. But as they spill over into the world of atoms, they flatten into step changes, because you lose the compounding effect. I do think we are on the verge of something tho. Once the compounding effect happens in the world of atoms (recursive robotics), it's over.
• ssvt 8mo ago
  Maybe I’m slow (alright, I know I am) but it seems to me that HN has jumped the shark with it’s apparent shift to “all AI, all the time” making me lose interest. Yes, I won’t let the door hit me in the ass on the way out…