> software production has become a mass-produced commodity in every sense - it's much more expensive to produce software manually, but the quality is not the same.
Agreed.
Homer reunites with his long lost brother, who runs car company Powell Motors. Homer is ultimately tasked by his brother with helping to design a car for the “average man” that ultimately bankrupts the company for being wildly overengineered and costing too much ($82,000 in 1991-money).
Here’s the car: https://simpsons.fandom.com/wiki/The_Homer
You will really have to weigh the cost of making the software against the expected revenue.
In such markets, what you produce is either worth nothing or worth millions of dollars. For as long as it's the case that well-constructed code (with or without LLM help) is more likely to be in the latter category, the economics of software don't really change.
Even before LLMs, you could've commissioned a half-assed clone of any app you wanted from a 3rd world consultancy for a few thousand dollars. LLMs are basically Bangalore-as-API.
I remember hearing a story that in the past movies were so technically difficult to make that any movie that got made had a good chance to be a profitable hit. But as movies got cheaper to make, more movies got made. Nowadays movie studio execs have to really calculate out the audience and expected revenue for any new movie and balance that against the budget and the cost of the studio's failed movies.
I think a similar dynamic may happen in software
That might be part of it, but I think it also has to do with the reality of replicating and scaling. Hardware or physical goods simply don’t scale like digital goods. There can be hundreds of knock-off physical products that have lower quality and lower cost but serve 90% of the same purpose, because physical capacity for raw materials, construction, labor, shipping, etc. have scaling limits in each market and economy. Digital goods are just so much easier to replicate and scale, so it often doesn’t make sense to buy software at lower quality and lower price if it doesn’t do most of the job. There are still limits of course, and different from physical goods, but I think this is a key reason why software is seen as winner-take-all.
I.e. because software was hard to make and complex to copy you would tend to have "natural monopolies" that were hard to compete with. Who wants to try to build a new desktop OS to compete with Windows? Or a web browser from scratch? Or a new search engine? Etc.
Those and other pieces of software were complex and hard to make. The cost to copy and compete was very high. So one winner took most because that winner was the company who could figure that software out.
But as we can see with Kimi Work and other such things, software is now much easier to copy. Let's say it took $1 billion to make a copycat piece of software with people but now takes $100 million or $10 million with AI. Suddenly a copy and compete tactic makes much more sense than before
For example, with AI it might make financial sense to build a Chinese Native OS instead of Windows. Similarly for Russia, Iran, the EU, and a whole bunch of other places. All of a sudden, Windows might not be the winner take most OS, we might have lots of Operating Systems, with smaller markets and lower profits, which require much more careful financial analysis to stay profitable.
This would be just like Movies, TV Shows, Books or Music. When something works, people relentlessly copy it and different regions put their own spin on the idea. After Iron Man succeeded we had so many super hero movies. Etc. So there is not really a winner take most dynamic in these other digital products. Software may be moving that way
Fairly sure software dev was always an iceberg. Most software and most software devs aren't working on horizontal software, but on vertical software, in cost centers. Sales for that kind of software don't scale as much.
[1]: https://pluralistic.net/2024/04/24/naming-names/#prabhakar-r...
Same with a junior dev. They don't write long form spaghetti because they're trying to write more LOC. They do it because not doing it is hard, literally above their pay grade.
I use LLM every day, but they're still completely awful at architecture. I don't think this clear lack of ability is some conspiracy.
I was only able to do that after I had solved multiple related problems in different places and started introducing subtle bugs by accident / had difficulty detecting all edge cases
I've noticed whenever I use LLMs they introduce the same kind of thing but at much smaller scales than I would. They often suggest solving the wrong problem when I prompt them to diagnose specific bugs too. Usually opting for a shortcut that introduces its own issues and ironically calling the proper direction "too complex" when it's really not.
For who?
The public? The public has never liked buying software at any price.
Businesses? Businesses need higher quality software when it's relevant to their core competencies, so they hire people instead. Buying competing SaaS or depending too much on AI is throwing the baby out with the bathwater.
Also just remember - minimalist code looks and feels great but customers do not read your code. I have caught myself many times providing "corrections" to abstractions that were already ~fine, just not perfect. The average SWE costs $200/hr. Careful you don't burn $50 worrying about code that will likely be rewritten or can be better abstracted when that's actually needed.
This is a pointless quibble but the hourly rate claim is not true--it's like ~$60 in the USA [0]. Maybe you meant at a specific Org but this is important context when comparing "pricing" between human and AI.
[0] https://www.salaryexpert.com/salary/job/software-developer/u...
Even for a junior making $100K, I have a hard time believe their time is worth less than $75/hr or so.
Edit: Fine, "Senior" is not "Average". But naive salary is not the true numerator.
I have a hard time believe their time is worth less than $75/hr or so.
Pay hits a ceiling, and that ceiling is moving lower regardless of experience. That has nothing to do with AI, but what the market will bear. Hiring counts of humans must increase no matter what. Moving some of the spend to AI reduces the risk of hiring less qualified employees they might have rejected a decade ago.
Wages at the top end are stagnating to subsidize this. That's undeniable.
"Will I benefit from this code being minimalist before [date]", where [date] is whenever you think the agent will be good enough to come back and make the corrections you would make today.
Even as a self-contained unit, you can't step in the same river twice, and on [date] some important details may have seriously faded, both in terms of text that can be mined and also in terms of human "why did we do that" and "what was the reason we did it this way and not that way" etc.
And this is how I find out I'm woefully underpaid.