Great angle to look at the releases of new software. I, too, thought we'd see a huge increase by now.
An alternative theory is that writing code was never the bottleneck of releasing software. The exploration of what it is you're building and getting it on a platform takes time and effort.
On the other hand, yeah, it's really easy to 'hold it wrong' with AI tools. Sometimes I have a great day and think I've figured it out. And then the next day, I realize that I'm still holding it wrong in some other way.
It is philosophically interesting that it is so hard to understand what makes building software products hard. And how to make it more productive. I can build software for 20 years and still feel like I don't really know.
When working on anything, I am asked: what is the smallest "hard" problem that this is solving ? ie, in software, value is added by solving "hard" problems - not by solving easy problems. Another way to put it is: hard problems are those that are not "templated" ie, solved elsewhere and only need to be copied.
LLMs are allowing the easy problems to be solved faster. But the real bottleneck is in solving the hard problems - and hard problems could be "hard" due to technical reasons, or business reasons or customer-adoption reasons. Hard problems are where value lies particularly when everyone has access to this tool, and everyone can equally well create or copy something using it.
In my experience, LLMs have not yet made a dent in solving the hard problems because, they dont really have a theory of how something really works. On the other hand, they have really helped boost productivity for tasks that are templated .
One of the rebuttals at the end of the post addresses this.
> That’s only true when you’re in a large corporation. When you’re by yourself, when you’re the stakeholder as well as the developer, you’re not in meetings. You're telling me that people aren’t shipping anything solo anymore? That people aren’t shipping new GitHub projects that scratch a personal itch? How does software creation not involve code?
So if you’re saying “LLMs do speed up coding, but that was never the bottleneck,” then the author is saying, “it’s sometimes the bottleneck. E.g., personal projects”
Also when vou create a product you can’t speed up the iterative process of seeing how users want it, fixing edge cases that you only realized later etc. these are the things that make a product good and why there’s that article about software taking 10 years to mature: https://www.joelonsoftware.com/2001/07/21/good-software-take...
This is the answer. Programming was never the bottleneck in delivering software, whether free-range, organic, grass-fed human-generated code or AI-assisted.
AI is just a convenient excuse to lay off many rounds of over-hiring while also keeping the door open for potential investors to throw more money into the incinerator since the company is now “AI-first”.
Just like writing Lord of the Rings is actually not just about typing. You have to live a life, go to war, think deeply for years, research languages and cultures and then one day you type all that out
An alternative theory is that writing code was never the bottleneck of releasing software. The exploration of what it is you're building and getting it on a platform takes time and effort.
On the other hand, yeah, it's really easy to 'hold it wrong' with AI tools. Sometimes I have a great day and think I've figured it out. And then the next day, I realize that I'm still holding it wrong in some other way.
It is philosophically interesting that it is so hard to understand what makes building software products hard. And how to make it more productive. I can build software for 20 years and still feel like I don't really know.