Comment by zby
13 hours ago
Classic Jevons Paradox - when something gets cheaper the market for it grows. The unit cost shrinks but the number of units bought grows more than this shrinkage.
13 hours ago
Classic Jevons Paradox - when something gets cheaper the market for it grows. The unit cost shrinks but the number of units bought grows more than this shrinkage.
Of course that is true. The nuance here is that software isn’t just getting cheaper but the activity to build it is changing. Instead of writing lines of code you are writing requirements. That shifts who can do the job. The customer might be able to do it themselves. This removes a market, not grows one. I am not saying the market will collapse just be careful applying a blunt theory to such a profound technological shift that isn’t just lowering cost but changing the entire process.
You say that like someone that has been coding for so long you have forgotten what it's like to not know how to code. The customer will have little idea what is even possible and will ask for a product that doesn't solve their actual problem. AI is amazing at producing answers you previously would have looked up on stack overflow, which is very useful. It often can type faster that than I can which is also useful. However, if we are going to see the exponential improvements towards AGI AI boosters talk about we would have already seen the start of it.
When LLMs first showed up publicly it was a huge leap forward, and people assumed it would continue improving at the rate they had seen but it hasn't.
Exactly. The customer doesn't know what's possible, but increasingly neither do we unless we're staying current at frontier speed. AI can type faster and answer Stack Overflow questions. But understanding what's newly possible, what competitors just shipped, what research just dropped... that requires continuous monitoring across arXiv, HN, Reddit, Discord, Twitter. The gap isn't coding ability anymore. It's information asymmetry. Teams with better intelligence infrastructure will outpace teams with better coding skills. That's the shift people are missing.
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>The customer will have little idea what is even possible and will ask for a product that doesn't solve their actual problem.
How do you know that? For tech products most of the users are also technically literate and can easily use Claude Code or whatever tool we are using. They easily tell CC specifically what they need. Unless you create social media apps or bank apps, the customers are pretty tech savvy.
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We talk about things like S curves for AGI, and how it's slowing down.
But where is the S curves for programmers at?
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> The customer might be able to do it themselves
Have you ever paid for software? I have, many times, for things I could build myself
Building it yourself as a business means you need to staff people, taking them away from other work. You need to maintain it.
Run even conservative numbers for it and you'll see it's pretty damn expensive if humans need to be involved. It's not the norm that that's going to be good ROI
No matter how good these tools get, they can't read your mind. It takes real work to get something production ready and polished out of them
There are also technical requirements, which, in practice, you will need to make for applications. Technical requirements can be done by people that can't program, but it is very close to programming. You reach a manner of specification where you're designing schemas, formatting specs, high level algorithms, and APIs. Programmers can be, and are, good at this, and the people doing it who aren't programmers would be good programmers.
At my company, we call them technical business analysts. Their director was a developer for 10 years, and then skyrocket through the ranks in that department.
I think it's like super insane people think that anyone can just "code" an app with AI and that can replace actual paid or established open-source software, especially if they are not a programmer or know how to think like one. It might seem super obvious if you work in tech but most people don't even know what an HTTP server is or what is pytho, let alone understanding best practices or any kind of high-level thinking regarding applications and code. And if you're willing to spend that time in learning all that, might as well learn programming as well.
AI usage in coding will not stop ofc but normal people vibe coding production-ready apps is a pipedream that has many issues independent of how good the AI/tools are.
> Instead of writing lines of code you are writing requirements.
https://www.commitstrip.com/en/2016/08/25/a-very-comprehensi...
The way I would approach writing specs and requirements as code would be to write a set of unit-tests against a set of abstract classes used as arguments of such unit-tests. Then let someone else maybe AI write the implementation as a set of concrete classes and then verify that those unit-tests pass.
I'm not sure how well that would work in practice, nor why such an approach is not used more often than it is. But yes the point is that then some humans would have to write such tests as code to pass to the AI to implement. So we would still need human coders to write those unit-tests/specs. Only humans can tell AI what humans want it to do.
Anecdote: I have decades of software experience, and am comfortable both writing code myself and using AI tools.
Just today, I needed a basic web application, the sort of which I can easily get off the shelf from several existing vendors.
I started down the path of building my own, because, well, that's just what I do, then after about 30 minutes decided to use an existing product.
I have hunch that, even with AI making programming so much easier, there is still a market for buying pre-written solutions.
Further, I would speculate that this remains true of other areas of AI content generation. For example, even if it's trivially easy to have AI generate music per your specifications, it's even easier to just play something that someone else already made (be it human-generated or AI).
I've heard that SASS never really took off in China because the oversupply of STEM people have caused developer salaries to be suppressed so low that companies just hire a team of devs to build out all their needs in house. Why pay for a SASS when devs are so cheap. These are just anecdotes. Its hard for me to figure out whats really going on in China.
What if AI brings the China situation to the entire world? Would the mentality shift? You seem to be basing it on the cost benefit calculations of companies today. Yes, SASS makes sense when you have developers (many of which could be mediocre) who are so expensive that it makes more sense to just pay a company who has already gone through the work of finding good developers and spend the capital to build a decent version of what you are looking for vs a scenario where the cost of a good developer has fallen dramatically and so now you can produce the same results with far less money (a cheap developer(does not matter if they are good or mediocre) guiding an AI). That cheap developer does not even have to be in the US.
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My experiments with AI generated code is you have to specify it like a programmer would, i.e. you have to be a programmer.
The nuance here is that AI cant do what you think it can.
AI can code because the user of AI can code.
Debbie from accounting doesn't have a clue what an int is
"Thinking clearly about complexity" is much more that writing requirements.
"yours is not to reason why, yours is just to do, or die"
( variation of .. "Ours is not to reason why, ours is but to do and die" )
Does that automatically translate into more openings for the people whose full time job is providing that thing? I’m not sure that it does.
Historically, it would seem that often lowering the amount of people needed to produce a good is precisely what makes it cheaper.
So it’s not hard to imagine a world where AI tools make expert software developers significantly more productive while enabling other workers to use their own little programs and automations on their own jobs.
In such a world, the number of “lines of code” being used would be much greater that today.
But it is not clear to me that the amount of people working full time as “software developers“ would be larger as well.
> Does that automatically translate into more openings for the people whose full time job is providing that thing?
Not automatically, no.
How it affects employment depends on the shapes of the relevant supply/demand curves, and I don't think those are possible to know well for things like this.
For the world as a whole, it should be a very positive thing if creating usable software becomes an order of magnitude cheaper, and millions of smart people become available for other work.
I debate this in my head way to much & from each & every perspective.
Counter argument - if what you say is true, we will have a lot more custom & personalized software and the tech stacks behind those may be even more complicated than they currently are because we're now wanting to add LLMs that can talk to our APIs. We might also be adding multiple LLMs to our back ends to do things as well. Maybe we're replacing 10 but now someone has to manage that LLM infrastructure as well.
My opinion will change by tomorrow but I could see more people building software that are currently experts in other domains. I can also see software engineers focusing more on keeping the new more complicated architecture being built from falling apart & trying to enforce tech standards. Our roles may become more infra & security. Less features, more stability & security.
Jevon's Paradox does not last forever in a single sector, right? Take manufacturing business for example. We can make more and more stuff with increasingly lower price, yet we ended up outsourcing our manufacturing and the entire sector withered. Manufacturing also gets less lucrative over the years, which means there has been less and less demand of labor.
I'm quite convinced that software (and, more broadly, implementing the systems and abstractions) seems to have virtually unlimited demand. AI raises the ceiling and broadens software's reach even further as problems that previously required some level of ingenuity or intelligence can be automated now.
> yet we ended up outsource our factories and the entire sector withered.
hmm outsourcing doesn't contradict Jevon's paradox ?
You're right. I updated it to "in a single sector". The context is about the future demand of software engineers, hence I was wondering if it would be possible that we wouldn't have enough demand for such profession, despite that the entire society will benefit for the dropping unit cost and probably invented a lot of different demand in other fields.
Jevons paradox is the stupid. What happened in the past is not a guarantee for the future. If you look at the economy, you would struggle to find buyers for any slop AI can generate, but execs keep pushing it. Case in point the whole Microslop saga, where execs start treating paying customers as test subjects to please the share holders.