4 ms·
AI productivity gains are closer to 10% than 10x
- mytailorisrich 2mo agoAI has the potential to be extremely powerful but it is also very new. People and organisations are just at the beginning of the learning process.
- goatlover 2mo agoSure but the hype has been about the 10x productivity increases and how less employees are needed. Also all the AGI/singularity stuff being just around the corner, not simply AI potentially making employees a lot more productive.
- mytailorisrich 2mo ago> Sure but the hype has been about the 10x productivity increases and how less employees are needed Which will probably be true at some point when we have become good at using AI, and maybe when AI has improved further as well.
- maleero 2mo ago10% seems low. I think 1.5-3x is more like it without sacrificing quality. You can easily go 10x if you don’t care about the results too much.
- Tagbert 2mo agoThere are probably larger gains in some areas like testing and coding. other areas, less so as they depend on messy data. I can tell you that only some areas of project management benefit from AI. the rest is more of a people problem.
- watwut 2mo ago> You can easily go 10x if you don’t care about the results too much. People are also much faster when they dont care about quality at all.
- satvikpendem 2mo agoNot really. There's a limit to how much you can focus on and literally type, even caring little about quality.
- watwut 2mo agoYou dont need to focus if you dont care about quality. Overworked teams do it all the time.
- satvikpendem 2mo agoYou need to make sure the text you're typing actually compiles into a working program, so there is some degree of focus required. Compare that with vibe coding, just type a sentence of what you want and it does everything itself with no continued focus from you. The degree is completely different.
- watwut 2mo agoI did worked in teams that produced crap. They were initially all able to proceed much faster then teams that did not produced crap. They felt like being super productive the whole time, cranking out issues one after another. The initial speed slowed down after 2-3 months, but they did not noticed it. They ended up being actually slower, customers were unhappy because they were not getting functional software they wanted and the team believed themselves to be victims. The overall results, if you joined them later was "wow this is slow, you are producing crap and customer is entirely correct when they complain". My point here is that "don't care about quality" does a lot in that claim. It leads to a lot of useless and contra-productive work - you would be better off if they have done nothing. And I think what people are reproducing that state here, just faster.
- smcg 2mo agounless AI also speeds up the 84% of work that isn't coding, that is not possible.
- whateveracct 2mo ago3x? a year of work in 4 months? it's almost August - companies should have two years of progress since Jan 1 2026.
- type0 2mo ago> if you don’t care about the results too much. if you like slop
- didibus 2mo agoI mean, they went and measured it, you're just "feeling" it?
- simianwords 2mo agoThis is very similar to how you can double the employees in a company and only get marginal improvement in productivity. If that’s true, AI gives the same gains doubling labour. No?
- jimz12 2mo agoIf you don’t get return on productivity then you cut and get savings
- mycentstoo 2mo agoMy unsolicited thoughts: * AI will drive additional features as development accelerates * There will be a window where fast adopting AI companies can deliver features faster than peers * Those fast adopting AI companies will be able to garner additional revenue * Gap closes as AI benefits slow in their impact to feature development and slower adopting companies catch up * Companies that were faster adopters can no longer charge more for additional revenue without giving up market share to now caught-up competitors * New normal is that companies are in a bind - they have to pay for tokens/AI aided development else they lose speed and therefore market share - but the paying is now without additional revenue and exists as a tax Assumptions: * No AGI * LLMs have bounded impact on features * Timeframe is long enough that companies that trail in AI won't be starved out https://www.youtube.com/shorts/iVHmp9F4Rl0 https://www.youtube.com/shorts/iVHmp9F4Rl0
- discreteevent 2mo ago> There will be a window where fast adopting AI companies can deliver features faster than peers >Those fast adopting AI companies will be able to garner additional revenue The companies going 50% slower on reliable features that customers want to pay for will continue to wipe the floor with the hyper productive companies producing fluff.
- joshstrange 2mo agoI reject the premise that you can’t use LLM’s to build reliable features.
- budsniffer952 2mo agoAnd you get down voted for saying something truthful and mundane because, apparently, HackerNews is now filled with morons.
- cyanydeez 2mo ago* AI will drive 10x bike shedding for 90% of the consumers diluting any real speed up, except the one...autist.
- UltraSane 2mo ago10% is still huge.
- discreteevent 2mo ago10% in profit is huge but that's not what the article is about.
- UltraSane 2mo agoA 10% increase to total labor productivity would be huge. It would add trillions to global GDP.
- smcg 2mo agoit's much lower than common claims about AI.
- UltraSane 2mo agoBit it would still add trillions to global GDP
- deleted 2mo ago[deleted]
- horticulturist 2mo agoThe variation in individual developer throughput was as much as 20x pre-AI. 10% is basically nothing. You’d be better off firing your worst performer and replacing them with someone good (or great).
- jijijijij 2mo agoGood luck getting those devs. Between the fallout of covid and AI in education, there is likely half an upcoming generation poorly educated and comparatively less qualified. Right now the market favors employers, but I think when the sobriety sets in this will rapidly change. Senior devs are gonna get more expensive. Companies should massively invest in education programs.
- Kuyawa 2mo agoHow long it takes for a seasoned developer to write a full app with database design, full authentication register/login/logout/forgot/session, basic crud for all entities, payment processing, admin dashboard with analytics, recent users, transactions, moderation, etc Usually from 1 to 3 months Now it all can be developed in just 5 mins, add cosmetic changes in just 24 hours and you have a fully functioning app already deployed in production So if that doesn't make you a 10X developer you are not using enough AI
- deterministic 2mo ago> Now it all can be developed in just 5 mins Please go ahead and post a YouTube video showing us all how to do it.
- vrighter 2mo agoI would like to add the constraint that if your software doesn't work, regulatory bodies will fine and sanction your country.
- evanmoran 2mo ago> Our team at DX analyzed engineering velocity from November 2024 to February 2026 In my experience Claude Code only really started to be really strong in December 2025 and most people didn’t notice/adopt it until Opus 4.6, which launched in Feb 2026. So I’d expect quite a different result if measure since then.
- mstaoru 2mo agoMy rather simplistic take: Everybody have access to the same LLMs. Eventually if everybody is a "Nx engineer" (see PS below), then nobody is. Just a new baseline. Once you are at this point, you can either invest further in LLMs, marginally increasing "productivity", or invest in people and culture, increasing potential for innovation by bringing in deep domain expertise that is not in any LLM and never will be. PS: many measure "Nx engineer" by lines of code or number of "features" someone churns out; a better metric would be real world impact. Can I 10x my "made the world a better place" metric with LLMs? Hard to say. Probably not.