The 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).
Good 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.
* 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
> 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.
> There will be a window where fast adopting AI companies can deliver features faster than peers
The fundamental problem is having people doing the right things. Lines of code does not equal real economic value.
I think AI will have a much different effect: raw headcount will no longer give large companies the same moat that they once had.
If AI makes a 10x engineer into an 100x engineer and unlocks this whole world of productivity, getting them to actually deliver 100x requires the proper culture where they aren't blocked by environmental factors, management, and incentive structure.
10x -> 100x is an extreme example, but the point stands: if AI amplifies our productivity and productivity is determined by motivation + environment + alignment on priorities, in order to realize the advantage from AI, a company needs to both embrace it and have the right culture
> 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.
There 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.
You 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.
I 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.
Great but none of that was my claim at all, I just said that AI vibe coding takes less physical effort, meaning literal effort to press keys, than hand coding. Either way, AI models these days are much better than those low tier coders as well as average coders, and the best models are even better than most top tier coders, all at a much higher speed, so you can't compare bad human coders and AI anymore.
Sure 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.
How 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
The 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).
Good 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.
My 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
> 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.
I reject the premise that you can’t use LLM’s to build reliable features.
> There will be a window where fast adopting AI companies can deliver features faster than peers
The fundamental problem is having people doing the right things. Lines of code does not equal real economic value.
I think AI will have a much different effect: raw headcount will no longer give large companies the same moat that they once had.
If AI makes a 10x engineer into an 100x engineer and unlocks this whole world of productivity, getting them to actually deliver 100x requires the proper culture where they aren't blocked by environmental factors, management, and incentive structure.
10x -> 100x is an extreme example, but the point stands: if AI amplifies our productivity and productivity is determined by motivation + environment + alignment on priorities, in order to realize the advantage from AI, a company needs to both embrace it and have the right culture
* AI will drive 10x bike shedding for 90% of the consumers diluting any real speed up, except the one...autist.
> 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.
10% 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.
There 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.
3x? a year of work in 4 months?
it's almost August - companies should have two years of progress since Jan 1 2026.
unless AI also speeds up the 84% of work that isn't coding, that is not possible.
> 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.
Not really. There's a limit to how much you can focus on and literally type, even caring little about quality.
You dont need to focus if you dont care about quality. Overworked teams do it all the time.
You 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.
I 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.
Great but none of that was my claim at all, I just said that AI vibe coding takes less physical effort, meaning literal effort to press keys, than hand coding. Either way, AI models these days are much better than those low tier coders as well as average coders, and the best models are even better than most top tier coders, all at a much higher speed, so you can't compare bad human coders and AI anymore.
I mean, they went and measured it, you're just "feeling" it?
> if you don’t care about the results too much.
if you like slop
10% is still huge.
10% in profit is huge but that's not what the article is about.
A 10% increase to total labor productivity would be huge. It would add trillions to global GDP.
it's much lower than common claims about AI.
Bit it would still add trillions to global GDP
This 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?
If you don’t get return on productivity then you cut and get savings
AI 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.
Sure 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.
> 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.
How 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
> 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.
I would like to add the constraint that if your software doesn't work, regulatory bodies will fine and sanction your country.