I don't think it's a bad thing, if it will help real people rather than the usual bigcorp/unicorn critters.
See also: Jevon's paradox
>[Tech companies], both historical and modern, typically expect that higher [revenues] will lower [tech debt], rather than expecting the Jevons paradox
As software becomes more essential to a business its reliability becomes more important. If your customers can tolerate defects or downtime it’s a signal that:
A) you’re not providing any real value
B) You provide so much additional value compared to your competition you still come out ahead in the wash
C) Your customers are hostages via vendor lock-in
A and C are the most common cases of persistent bad software.
[1] https://en.wikipedia.org/wiki/Jevons_paradox
edit: whoops that's the point of the original article
As it becomes easier and more profitable to accrue tech debt, more tech debt will be accrued
Engineers will still continue to work like crazy and produce 100x the output. The pay could still remain the same because the profit margins on these newly developed software is gonna be so much better.
That being said, I think there will be a cycle of adjustment - may be 2-5 years for this reality to set in. So in that interim there may be joblosses.
This assumes software developers will be the ones needed to meet the demand. I think it will be more like technical product managers
Whatever juice there is to squeeze out of generative AI coding, the people who will squeeze the most from it in the near future (10-20 years) are current and incoming software developers. Some may adopt different titles as the role matures, especially if there's a pay differential. This already happened with data engineering, database administration, etc
So it's possible that the absolute number of people carrying the title approximately like "software developer" may be fewer in 10 years than it is today, although I personally find that very unlikely. But the people leading and maturing whatever alternate path comes up, for the next generation or so, will more often than not have a professional or academic background in software development regardless.
The whole point of the article is that generative AI represents a lever that amplifies the capabilities of people who best know how to apply it. And for software development, that's ultimately going to be software developers.
I disagree. SWE skills are not the same as TPM skills. Those who like doing SWE work may not like nor be good at TPM work. And my point is TPM skills will be what’s likely more needed. Therefore they may not be the same individuals, though many will need to adapt. Or go into woodworking or something
Even with traditional software development you'll be a much more effective software developer with good product management skills in a lot of niches (basically anything that's building a something user-facing)
I imagine there is an upper bound on how much of the world can be eaten by software, and the trend seems to be getting closer to that point. Unless there are some massive breakthroughs in robotics or cybernetics which open more of the physical world to software.
There's also a point where incremental software improvement requires bulldozing, paving, or burning so much nature that we'll be worse off in the end. Watching billionaires squabble about who gets the new AI data centers makes me wonder if we haven't crossed over that point a few funding rounds ago.
Like Simon’s quote above says, software is a competitive advantage so when one company develops software that makes them more efficient or grows revenue, competitors have to follow suit or get left behind. It’s an economic arms race. That’s why the dreaded outsourcing wave of the 2000s never materialized: companies ended up hiring a bunch more software engineers in the US and outsourced a bunch of other engineering to India and other countries.
The interesting question is how this will interact with current interest rates and the end of ZIRP.
I think a product like GithubNext Spark [1] that can handle deployment, SSO, databases, uploads, etc with an LLM fine tuned on the managed runtime API will be a very productive tool. It already works surprisingly well in my experience although it’s an mvp and they havent fleshed out database stuff yet. Kind of like a higher code Retool that can still be used by non-programmers.
The original dream of Web Services and SOA.
I work at a small business and understand the entire system as a whole.
Most the complexity we have is in the UI so non-technical people can interact and work with company data/databases. Our SaaS is really the same thing but stuff we didn't want to build in house. There is no rocket science being done here.
At some level of AI accuracy though it would seem like there would be a phase transition that most of this UI goes away along with the need for many of the employees.
Right now there is no risk of this happening but at some level of accuracy we go from 200 people to like 20 with the only future head count coming in sales. Most likely though I would expect a competitor to eat our lunch in the phase transition and we go from 200 to zero.
Pushing 50 here, I am trying to think right now of my AI hedge/career change to something more creative/artistic that being a human itself has value. I managed to avoid working in a factory like my father by being a shitty computer but there might be no market for shitty human computers in 10 years.
Until it becomes cosmic code.
( https://minimaxir.com/2025/01/write-better-code/ / https://news.ycombinator.com/item?id=42584400 )
What evidence suggests this to you?
The reality is business can't really just scale their revenue by adding more profitable or positive ROI projects. There are not enough of them to go around. Eventually you hit a plateau in terms of growth and the R&D / engineering productivity can't translate into revenue anymore.
But that’s across the whole economy. Individual businesses will very much behave idiosyncratically. Businesses tend to have an upside U in terms of their growth; unlike the economy as a whole, they don’t go up and to the right forever. And the economy as a whole, if you zoom out, does go up an to the right, but it is bumpy.
I guess in summary, I don’t think it makes sense to extrapolate long term trends by focusing on just the last 2 years, when the market for software engineers has cooled. After all, these cooler years followed what I can only feel were 3 or 4 years of a scalding hot market for software engineers.
However there are at least 3 tipping points in the medium term that can alter this dynamics:
- AI becoming more capable and cost-effective than human in most aspects of software engineering. This would dramatically shift the ROI calculations and tip towards AI over human.
- We reach a stage where software resources and products are abundant, they solve most of our problems, and we don't need more software anymore. Sort of like WALL-E. Obviously we don't need so many software engineers then.
- AI systems take over software systems as the backbone of our technology layer, where AI is cheaper and more capable than software. Maybe we only need 100 different AI systems instead of 100k software systems. At this stage, we are going to be replacing software with AI, so we need less software engineers.
Machines shifted things away from manual labor, but AI sifts it from intellectual labor.
If AI can make high paying workers more efficient, then the companies that leverage that efficiency to grow will outpace the companies that can't. There's no net loss of high paying workers.
The argument boils down to diminishing returns.
Honda can’t scale to producing 10,000x as many cars. What they can do is sell the cars they are already producing for less, so if some aspect of their business becomes more efficient they don’t just do more of it endlessly, they quickly cross a threshold and then spend less on it.
If you accept that AI as we know it is a tool (and not a wholesale replacement for human beings) then it will follow the same trend of any other productivity tool of expanding markets and increasing demands for labor.
That changes nothing about diminishing returns here.
Expanding into a market doesn’t dramatically increase the demand for products in that market. If Tesla started to make Hybrids they could sell more cars and employ more people, but other companies would experience fewer sales and thus cut back on staff.
Competition is great for overall productivity, but the gains aren’t magically spread evenly across the economy.
> expanding markets and increasing demands for labor.
Many industries like banking, mining, and farming have drastically cut back on labor. When the majority of those lost jobs were low skilled the productivity benefits allowed more high skilled labor to be employed. But specifically cut high skill labor and new jobs are less likely to also be high skill.
All this is fine but then they take this to the extreme by laying off developers when there are no more ROI projects. Then bit rot sets in, systems degrade, customers abandon ship, and suddenly there are no engineers to help the business. And no, hiring contractors last minute doesn't cut it because they don't know what pile of gunk has been running and what caused the degradation.
Software requires maintenance, much like a bespoke car. For every bespoke car you produce, you need to continuously service it with bespoke skills else it will stop working - and cause your revenue to drop.
If AI gets as good as the people building it hope it will, then it doesn't matter what new jobs crop up or what opportunities there are left to uncover, the machine will just handle it.
Sure, maybe apparent exponential growth tails off into an S curve at some point, as often happens. But this blog post seems to assume that is guaranteed to happen, which is a big leap of faith, and also makes this not a very interesting blog post. Because it's basically just, "Well if I assume the best arguments against my position are wrong, then I don't even need to address them, and I can instead focus on lesser arguments that are easier for me to discuss".
Do many people pay for software. Other than some small, one-time donations to shareware back in the day and to more recent project that operates outside of "app stores" I pay zero dollars for software. It is a negligible expense.
No doubt businesses still pay for software. Having friends in software sales, I know it does not necessarily sell itself. It takes (non-developer) work. Whether businesses truly need to purchase these licenses is an open question. Most companies I know want to reducedd their software bill, some believe they are being overcharged.
I think the first step betrays the weakness in this reasoning.
We already know that more powerful software tools do not make all developers more efficient. So the reverse can be true.
For software jobs to remain, not only must the tools keep making human developers more efficient, but the human developers need to continue making the automated developers more efficient.
Both directions must be accounted for.
Question: what is something our best human developers can do, that will always enhance the artificial developers results? Regardless of how far automated developers scale in quantity, quality, speed, economy and complexity of work?
It is the same question for any new automation vs. previous process.
You need to identify that, for anything past your first reasoning step to have a chance.
But if you can definitively answer it, I don’t think you need any more steps.
"AI tools create a significant productivity boost for developers. Different folks report different gains, but most people who try AI code generation recognize its ability to increase velocity. Many people think that means we’re going to need fewer developers, and our industry is going to slowly circle the drain.
This view is based on a misunderstanding of why people pay for software. A business creates software because they think that it will give them some sort of economic advantage. The investment needs to pay for itself with interest. There are many software projects that would help a business, but businesses aren’t going to do them because the return on investment doesn’t make sense.
When software development becomes more efficient, the ROI of any given software project increases, which unlocks more projects. [...] Cheaper software means people are going to want more of it. More software means more jobs for increasingly efficient software developers."