So the lifecycle of an app would be:
1) Create your game/quiz/whatever app.
2) Pay a successful app $x per install, and get a bunch of app installs.
3) Put all sorts of scammy "get extra in game perks if you refer your friends" to try to become viral.
4) Hope to become big enough that people start finding you without having to pay for ads.
5) Sell ads to other facebook app startups to generate installs for them.
It was a completely circular economy. There was not product or income source other than the next layer of the pyramid.
It didn't last long.
In a complex project the hard parts about software are harder than the hard parts about the domain.
I've seen the type of code electrical engineers write (at least as hard a domain as software). They can write code, but it isn't good.
Web dev is low entry barrier and most web devs don’t need a very deep knowledge base.
Embedded, low level language, using optimizations of the OS / hardware require MUCH more specialized knowledge. Most of the 4 year undergraduate program for Computer Science self selects for mathematics inclined students who then learn how to read and learn advanced mathematics / programming concepts.
There’s nothing that is a hard limit to prevent domain expert autodidacts from picking up programming, but the deeper the programming knowledge, the more the distribution curves of programmers / non-programmers will be able to succeed.
Non programmers are more likely to be flexible to find less programming-specific methods to solve the overall problem, which I very much welcome. But I think LLM-based app development mostly just democratizes the entry into programming.
My belief is that engineers should be the prime candidates to be learning the domain, because it can positively influence product development. There’s too many layers between engineers and the the domain IME
The beauty of LLMs is that they can quickly gather and distill the knowledge on both sides of that relationship.
"Are there more or less examples of successful companies in a given domain that leverage software to increase productivity than software companies which find success in said domain?"
There’s a requisite curiosity necessary to cross the discomfort boundary into how the sausage is made.
The best part, of course, is that this mostly works, most of the time, for most busineses.
Now, the same domain experts -who still cannot code- will do the exact same thing, but AI will make the spreadsheet more stable (actual data modelling), more resilient (backup infra), more powerful (connect from/to anything), more ergonomic (actual views/UI), and generally more easy to iterate upon (constructive yet adversarial approach to conflicting change requests).
Hallucinations sure make spreadsheets nice and stable.
Programming is not something you can teach to people who are not interested in it in the first place. This is why campaigns like "Learn to code" are doomed to fail.
Whereas (good) programmers strive to understand the domain of whatever problem they're solving. They're comfortable with the unknown, and know how to ask the right questions and gather requirements. They might not become domain experts, but can certainly learn enough to write software within that domain.
Generative "AI" tools can now certainly help domain experts turn their requirements into software without learning how to program, but the tech is not there yet to make them entirely self-sufficient.
So we'll continue to need both roles collaborating as they always have for quite a while still.
My codebase is full of one-offs that slowly but surely converge towards cohesive/well-defined/reusable capabilities based on ‘real’ needs.
I’m now starting to pitch consulting to a niche to see what sticks. If the dynamic from the office holds (as I help them, capabilities compound) then I’ll eventually find something to call ‘a product’.
He kept ranting about what a b*tch of a problem that was, every time we went out drinking, and one day, something got into me, and thought there must be some software that can help with this.
Surely there was, and I set up a server with an online web UI where every employee could put in when they were able to work, and the software figured out how to assign timeslots to cover requirements.
I thought it was a nice exercise for me in learning to admininster a linux server, but when I showed it to my friend, he looked me in the eye and told me I a saved him a day of work every week, and called me a wizard :D
It occured to me, how naturally part of the programming profession is to make things in fixed amounts of time, that turn difficult and time consuming tasks a human needed to do into something that essentially just happens on its own.
There are an infinite amount of problems to solve.
Deciding whether they’re worth solving is the hard part.
Or maybe ask yourself what do you like to do outside of work? maybe build an app or claude skill to help with that.
If you like to cook, maybe try building a recipe manager for yourself. I set up a repo to store all of my recipes in cooklang (similar to markdown), and set up claude skills to find/create/evaluate new recipes.
Building the toy apps might help you come up with ideas for larger things too.
It’s really liberating. Instead of saying “gosh I wish there was an app that…” I just make the app and use it and move on.
This is not even AI - it's pre-AI, and everyone has continued to try to create things that other people can use as a dependency, just on a much higher pace.
I've found writing simulations that my childhood brain would have LOVED to see run fun and fulfilling.
AI is a product in search of a killer feature
First AGI was anyday going to come. Gpt5 had showed intelligence apparently
Then got started adult chat with paying customers
Also what does society need? Smart workers and people who believe in the system... so where does that leave us? We need to make something that would better enable children to want to grow up in the world and participate. Otherwise were doing nothing of value and in a death spiral
selling it is the hard part, nothing new there
Don’t get me wrong, I have found uses for various AI tools. But nothing consistent and daily yet, aside from AI audio repair tools and that’s not really the same thing.
They'll work for hours and end up with $4 of gold
Outside of tech companies, I think this is extremely common.
These are the pets.com of the current bubble, and we'll be flooded by them before the damn thing finally pops.