That is in line with L6 comp at Netflix and similar companies pre-AI mania. So presumably companies do see 10x performance differences in staff and are willing to pay for it because they aren't charities. And I'd be using the heck out of LLMs if I was still working there, because they have proven their worth to me on open source FreeBSD work and I know the sentiment is shared by many other prolific src committers.

The main problem with LLM productivity improvement is most of us are basically treading water already as employees.. and we all tend to use new tools to keep up with the times. So everyone roughly leveling up over the same couple of years isn't going to net any pay increase, and the best you can do is job hop to somewhere that rewards you accordingly if you are able to demonstrate outstanding capabilities.

But most ironically, LLMs are also pretty terrible for current corporate structuring, because there were already massive turf wars and performative theatrics, and LLMs just make that easier/worse. So small teams and projects are really poised to benefit at the moment, because it will take a long time to figure out how to adapt organizations and management structures to this reality. I also have no idea how a large org would interview to find stand out personnel, a leetcode interview was always a bit of a performance and hazing ritual and seems completely absurd at this point when it can be solved in real time with a prompt.

But is it?

Is it really 100x? Imagine that in 3 days you get the same amount of customers as you would in a almost a year so then in the next 3 days can you get the same and in the next 3 days again ... This is not even considering the idea that with AI you will get 100x of the previous 100x maybe which is really something pretty big.

If you have examples please share them.

I know good examples that are accelerating quite a lot with AI but not at the level of 100x.

These "10x developer" discussions are sort of meaningless unless it's discussing a comparison to a hypothetical typical professional software developer.

I've had some coworkers who appeared to have negative value. You were infinitely more productive then them before you could code. Doing nothing was superior.

Well, 0 to 1 - but that's still infinity times more than you could do before.

Amdahl can be applied directly to sequential tasks in projects.

In project management the overall gains can be even smaller than that. If the task is not on the critical path (ref a GANTT chart), then speeding it up does nothing to overall completion time.

Of course the particular resource can still be freed earlier. Which might make it possible to do other things with it. But nothing on overall completion time.

If one underestimates the swtiching costs of changing the task a resource has, one can end up with negative effects on the original project.

Ozim law - you can speed up your development 100x or 1000x and it doesn’t matter because your users are not able to absorb and understand the changes at that rate.

I was already working on teams where we got push back on too many changes so we had to scale back to monthly releases.

Modyfying database structure so fast? Good luck having useful insights when you mutate data so quick.

Maybe I am not smart enough having not smart enough customers but to judge if something meaningful is an improvement you need at least 3 months of data for a lot of things.

I agree that now what's good or bat will be a comparison with your peers.

2x might be awesome if your peers are 1x. It might be bad if they are 4x. We'll be optimising local maxima. Per company.

The multiplier won't be such a precise number, but rather more of a feeling of "X person seems to be producing double what I'm producing". It will definitively be used as criteria for employment for a while.

Then the industry will converge into a "new normal". Best practices will propagate fast thru the industry, and all developers will have a similar baseline. Dev that were great before and doing 2x, will continue to do so. Same for underperformers. The industry as a whole will produce a whole lot.

IMHO, this will only raise the bar. It will define what's the new normal.

Every place has had some experience with some problem that entire different teams, with dozens or even small hundreds of people failed to solve for years and years, and then some individual came and did it.

And almost everybody has seen or heard some similar story.

The thing is, those stories don't have a lot of similarity to each other, and there isn't much you can conclude for anybody's competence without looking at all the details. But they happen all the time, and not only in software development (just not on the same frequency, for obvious reasons).

"One solo dev who achieves as much as a N-person team" or alternatively, "N developers who achieve as much as a 10*N person team" is the one most easily supported with evidence. Prior to their acquisition, WhatsApp had 55 employees of which 32 were engineers. Facebook Messenger had a team that was most likely 100x larger than that and could not displace them in the target markets. In 1995 when Microsoft effectively defeated IBM as the premier software company, Microsoft had just 17,000 employees to IBMs 225,000 employees. The entire reason why a startup can even succeed is because a smaller, skilled team can overcome a much larger team with much more resources.

You're right. That's precisely the problem. The "Nx Engineer" is catchy and we all know "what it means" when we first hear it. We most likely relate it with an early experience when we were juniors and a senior developer pair programmed with us. For me it was mind-blowing. So we can relate to it.

But the issue is the ambiguity. The multiplier is there, but not the unit/metric being measured. So it's just a shorthand for "someone exceptionally good" as said by a sibling comment.

I don't think listed options are "different scales" - they seem similarly "out of reach for normal people" just in different directions

Imagine a gaussian distribution of all engineers. It's a figure of speech to say someone's productivity falls in the right-side tail of that distribution.

The multiplier isn't meant literally. It's shorthand to say someone is exceptionally good in a way that is rare to find.

Nowadays a single solo dev can outright achieve as much as entire _organizations_ could in the early 2010s. I know multiple people whos raw code output easily exceeds say everything Amazon/Google/Facebook (likely combined) could do in a single year in the 2010s.

> most developers ... are barely capable of programming

[big sigh]

As much as I keep trying to believe that this can't possibly be true, I keep seeing that it is. And I really don't think that AI is going to help matters.

OP here! I'm honestly curious about those projects where you saw 100x improvement. Can you share what they were about?

I see a lot of peers worried when there are claims about how _other_ people are performing in other companies/projects, and how we "need to catch up". In the article I try to convey that 10x (let alone 100x) were just figures of speech. They have been adopted by the industry. The original meaning is lost. And some now believe are _real_ multipliers.

This post is a reminder of that, to be able to chill a little bit :)

> My company has a huge problem where a junior engineer will complete tasks very quickly and appear to be extremely productive, but they're just hiding tech debt that has to be cleaned up later.

You're so right. Measuring wrong the impact, without taking into account incidents, tech debt, and so on. A classic.

We have very short attention spans and even shorter working memory. Also, the big numbers trigger our fomo very easily.

I just wrote a program that writes code at ~200mb/s and so will create a codebase the size of the mainline Ubuntu in minutes.

Never mind that it's just sedding "print "Hello, World!"" to the penultimate line.

I may not be too bright, but Lines of Code? I've got those.

Point taken! The example tries to exemplify the massive difference. Lifestyle inflation is a thing you're right. Why not to think in the reverse, then?

> 10x LESS salary for $70.000/year (~avg salary in USA) is 7k€/year. Imagine the lifestyle change

:)

Productivity never translates to wages.

A 0.1x developer becomes 0.01x with AI, not 1x.

Sure. The benefits will be for the company, no the engineer.

One way to make our job better is to remind ourselves that not data-backed claims of productivity might not be real at all.

I've written about it as well: https://jcarreras.es/posts/let-engineers-enjoy-the-benefits-...

> Actually, the most depressing part is that programming languages don't matter as before, the fun on open source projects is gone, and 2x as a team, means management now can do the same with 1/2 of the previous team sizes, most think they always land on the lucky half

I see it very differently:

* AI automated most tedious parts of coding leaving us creative parts (design, research)

* while individual productivity increased, but also complexity of products, systems, problems increased too, I am not sure corps who downsize task-force will benefit from it in long run

OP here. I literally asked Brave Search for "avg salary for a developer in the USA" and AI returned that number.

How ironic. I'm a 0.8x blog writer now, thanks to AI :joy:

"only" ~€631,113.70

A 20x employee is not making 80% less than a median 20x employee anywhere else. At that echelon the pay differences based on location, if they exist at all, are insignificant compared to base.

Yes, good catch. Math was not mathing.

My sources say programmers at the time could punch 100-200 lines of holes or 6-24,000 individual holes per hour.

The back of my napkin suggests that punching 60 to 240 billion holes per hour (~16.7M-66.7M per second)results in incineration of the media leading to a net 0X in production of useable code.

E.T. (the worst game in history) was done in 5 weeks. Experienced game developer can make similar game in hour. AI in minutes.

Not 100% related, but I have a draft on a thought experiment: how would change if AI responses were immediate?

Like sub-second latency for _any_ change you ask it. Let it be 100 files changed, MR review and fix of each point, design document, anythikng.

Tool execution (eg: running tests) would be the next tech bottleneck. And human-on-the-loop the obvious one.

Maybe that's where 1000x productivity hides, who knows :)

For me personally? Local processing power. The reason I rolled my own harness environment is because my 16 core CPU was literally MAXED OUT with parallel compilation units and edit streams. A custom harness barely helped. Just allows me to run a few more sessions in parallel

Reading speed, working memory. Agents are good coders, they are not good middle managers.

Do you dispute that an AI can be 100x better at boilerplate and scaffolding? I readily believe that. And if someone's mental model of their job is that they select the right AbstractBeanFactoryFactory pattern and then write a bunch of boilerplate then sadly they are completely outcompeted by AI. In the future nobody will pay you to write boilerplate.

But 100x on scaffolding or 50x for tests obviously doesn't translate into 100x or 50x overall throughput. The doc states, "The compression ratio between human-team time and AI-assisted time ranges from 3x (research) to 100x (boilerplate)". So Tan's position is not that you have 100x gains, but that you have 100x gains on tedium.

From personal experience depending on the type of software these numbers sound reasonable. Some software is more difficult than others. But for plain old web dev, yes you can absolutely crush it with AI now.

This is a point that I think folks miss a lot in these discussions.

I've seen my own raw code output increase by more that 100%, and that's after human review to make sure it's not just slop, before sending it to the rest of the team for review. And we're all doing that. We're all shipping way more code than ever before.

But I don't think our number of users is changing dramatically at all. "Engagement" (or however else you want to measure usage) isn't something that's gone up by the same factor.

\<half baked thought>

I think the simple explanation is this: there is finite "attention". Digital products cost nothing[^1] to copy and ship. They can scale to your maximum amount of users with the same cost to write. And now that cost to write is →0.

But attention hasn't increased by the same factor. People still spend exactly the same amount of time in front of their PCs. Orders of magnitudes of additional features aren't going to actually result in orders of magnitudes more usage.

Maybe there's some hypothetical product that could gain such an advantage in the market that it would fully displace all other entrenched players. Maybe a new application category might come to exist (agentic engineering applications come to mind).

But us being 10x faster at building out features doesn't mean there's suddenly 10x more supply. That's the smoke and mirrors of it all. What does being 10x faster actually get you?

<even less baked>

The logical outcome would be to spend 90% less on the cost center (engineering), to retain the same productivity, right? That's a accounting view of the world, one that can't account for the institutional capital that's built from human collaboration, and redundancy from having more maintainers of a project. But that seems like the only way this ends up working. Trading 10 engineering payrolls for 1 engineer and (<9 engineering payrolls) worth of tokens.

[^1]: perfectly spherical vacuum approximation, of course

So someone who went from producing ~30k loc/year to 30 million hasn't increased their productivity?