All these tools to build something, but nothing to build. I feel like I am part of a Pyramid Scheme where every product is about building something else, but nothing reaches the end user.
Note: nothing against fluid.sh, I am struggling to figure out something to build.
One of my first professional coding jobs was in 2007 when Facebook first introduced 'Facebook Apps'. I worked for a startup making a facebook app, and EVERY SINGLE app company had the same monetization strategy: Selling ads for other facebook apps.
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.
Hate to break it to you, but it’s still going on, just outside the fb app api.
The recent YC -> Circle -> Coinbase -> YC comes to mind
What is this?
YC invested in Coinbase, which invested in Circle, which is now investing in YC companies
full circle, not full stop
Yes I remember those days! I joined a startup whose first product was a Facebook app in 2007. We were right around the corner from Facebook HQ on Forest and High, and we were alpha partners for the launch of Pages. We created a feature film streaming app (the learning was: no one watches 100-minute videos on Facebook). While we never intended to be a Facebook-app company, technically it was the first thing we launched.
Fast forward 18 years, and the company is going strong with millions of subscribers and distributing Oscar winning films such as Demi Moore’s The Substance.
The Auteurs?
That sounds pretty fishy, but in my head, that's what an economy is. There aren't a lot of new inputs into the system. It's just a circulatory system of value moving around. The only new inputs would be things like mines, oil wells, and other outside forces. Labor is too I guess but I think it's less raw.
To be quite honest, in many ways AI itself feels a bit "scammy" sometimes. The biggest case for it seems to be how to shit one million garbage apps by snapping your fingers, while problems that are really hard to solve go unaffected.
What a beautiful microcosm of the attention economy.
Aren't most ads in scummy mobile games ads for other scummy mobile games, to this very day?
Yes, but those apps also have scummy microtransactions, so at least there is SOME outside revenue entering the system.
That is the problem with software developers with expertise in software, but no deep domain knowledge outside the CS world.
It is my belief with some exceptions it is almost always easier to teach a domain expert to code than it is to teach a software developer the domain.
For problems that can be solved with only a small amount of simple code that is true. However software can become very complex and the larger/more complex the problem is the more important software developers are. It quickly becomes easier to teach software developers enough of your domain than to teach domain experts software.
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.
That's true both ways though: if a theoretical physicist wants to display a model for a new theorem, it'd be probably easier for them to learn some python or js than for a software engineer to understand the theorems.
If this is the case is discoverable, for at least one direction. Reproducability is known to be a problem in some of the sciences, for various reasons. Find a paper that includes its data and software/methodology used for analysis, and try to get it running and producing the same results. Evaluate the included software/methodology on whatever software quality standards you feel are necessary or appropriate.
Hard disagree with hard parts of software are harder than domain. I don’t know your story, skills, or domain. But this doesn’t match my experience and others around me at all.
Really depends on the domain. I've been in jobs where the domain was much harder than my job as a software engineer, but I've also been in jobs where I quickly got to understand the domain better than the domain experts, or at least parts of it. I believe this is not because I'm smart (I'm not), but because software engineering requires precise requirements, which requires unrelenting questioning and attention to details.
The ability to acquire domain knowledge quickly however, isn't exactly the same as the ability to develop complex software.
Maybe you and others around you are all in some form of engineering capacity? Because I have seen software everywhere from coffee shops, bicycle repairs, to K12 education - all of whom would hard disagree with you.
Not all kinds of programming are the same.
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.
Every single time I try to get a domain expert at $job to let me learn more about the domain it goes goes nowhere.
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
I mostly agree, but I see programmers more as “language interpreters”. They can speak the computer’s language fluently and know enough about the domain to be able to explain it in some abstractions.
The beauty of LLMs is that they can quickly gather and distill the knowledge on both sides of that relationship.
It is my experience that most of these business domain experts snore the moment you talk about anything related to the difficulties of creating software.
Yeah, I think the issue has more to do with the curiosity level of the participant rather than whether they are a business domain expert or a software engineering expert.
There’s a requisite curiosity necessary to cross the discomfort boundary into how the sausage is made.
Until a few months ago, domain experts who ciuldn't code would "make do" with some sort of Microsoft Excel Spreadsheet From Hell (MESFH), an unholy beast that would usually start small and then always grow up to become a shadow ERP (at best) or even the actual ERP (at worst).
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).
We have monthly presentations at my job and the business folk are really leaning into AI. The biggest win so far are them being able to generate new user experiences and get them into figma by themselves. They're able to test a design, get it into figma, generate some code, and get it in front of users without a developer or designer at all. It's not perfect but the tests show what we need to focus on vs what falls flat when put in front of users. It's very impressive and I'm proud of them.
Super interesting. I don't know why, but something about this comment made something click for me, as an "AI fatigued" engineer.
From the view you describe, it seems AI just lets you experiment faster, when all you want to do is experiment. You find product market fit easier, you empower designers more, etc. Much easier to iterate and find easy wins from alternative designs - as long as your fundamentals work!
Only problem is that you are experimenting in public, so the massive wave of new AI generated features come to the public from everywhere at once. Hence the widespread backlash.
Not to mention, the core job function when you are experimenting is different from what defines a lot of hard technical progress: creating new technologies, or foundational work that others build on, is naturally harder and slower than building e.g. CRUD services on top of an existing stack. Deep domain expertise matters for selling, deep programming expertise matters for stability. I don't know, curious where the line will end up getting drawn.
Yeah, the examples I've seen really focus on experimentation which my employers's platform is designed around. We are constantly testing changes in design and copy and hoping that we get small incremental increases in user attention. AI is really suited for these small changes and it allows us developers to build platforms specific stuff instead of working on baby tweaks. We already had a pretty good system where astute business people could tweak HTML and CSS but now their lives are even easier and they can focus on their actual job which is increasing customer sign ups and attention
> AI will make the spreadsheet more stable
Hallucinations sure make spreadsheets nice and stable.
One of my favorite things about this field is getting to learn about all of these different business domains.
In practice, does that happen? Usually companies try to bring the best of both and build from there.
I wouldn’t argue how things historically worked, but rather where the LLM innovations suggest the trajectory will go.
This is interesting. Do you know of any examples of successful tech companies built by non-technical founders?
Your question kind of answers itself with the filter of "tech companies". If you asked broadly about successful companies, the answer would be more apparent.
But an answer to your question would be Capital One.
I think a more appropriate question would be:
"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?"
Eh, this is the kind of pithy soundbite that sounds vaguely deep and intelligent but doesn't hold up.
In what domains have you had experience taking non programmers with domain knowledge and making them programmers?
That doesn't track at all IME.
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.
Conversely, good developers can now leverage LLM’s to master any domain.
Hhmm I think that's more difficult than using these tools for creating software. If generated software doesn't compile, or does the wrong thing, you know there's an issue. Whereas if the LLM gives you seemingly accurate information that is actually wrong, you have no way of verifying it, other than with a human domain expert. The tech is not reliable enough for either task yet, but software is easy to verify, whereas general information is not.
Or... the places they have deep expertise they have NDA/non-competes to worry about. (At least, outside of California.)
Sure, I could go and create an accounting app - or a clinical trial recruitment app - as a basic clone of what I've already created. And I might even make it better for some niche. But even if I know what that product system needs, I still need to find someone with the relationships to get in the door.
The trick is - you don't need an idea man for a non-technical founder. You really need someone with a rolodex and a problem.
I want to make a business, but what is the business
It's way easier to raise for dev tools than domain tools right now.
Pretty much. I’m working on a few things with several people and I’m now constrained by their ability to find stuff to build.
I’ve been a year deep into my first job out of tech. There is a never ending slew of problems where being able to code, specially now with AI, means you have wizard-like powers to help your coworkers.
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’.
That made me remember that one time many years ago, when I had a friend who literally called me a wizard.. He was working as a shift manager at a call center, and one of his most difficult tasks he kept ranting about was scheduling employees, who were not the most consistent bunch, and had varied skillset, yet he had to meet very strict support availability requirements.
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.
The problem we have as software engineers (from an entrepreneur's pov) is that we mostly struggle with stuff that's removed from the client's problem.
I mean it in terms of owning the solution to a problem, being accountable/responsible for something working e2e not just the software or even the product - the service/experience of the customer that makes them want to give you money. Once you put on another hat - guess what - you'd probably be the star of some operations team or a great supervisor of some department. You would automate everything around you to a point others think you're the most capable person they've ever seen in that role.
Can I ask what do you do now?
I am in the same boat but I recently found I could also use these tool so reverse engineer stuff as well. For example I purchased this label printer from china and was unsatisfied with the printing quality under Linux. So I "coded" a go script to print via BLE instead of CUPS [1]. To do this I de-compiled the android app that comes with the printer and instead of spending hours going through it I just told an Agentic AI to do this for me.
I am now so deep into the rabbit hole that I have made a version that runs entirely in the browser and an ESP32 version. I have now also taken the printer apart to find that the built in BLE is an external module and I could interface directly with the printer by replacing it with my own custom PCB...
[1] https://sschueller.github.io/posts/making-a-label-printer-wo...
In macroeconomic, you have an aggregate production functions that represents output for a country or something. In many of these function you'll have a parameter for technology, it acts as a multiplier over inputs, so the greater the measure of technology the greater the output. Quite a few of these also exhibt a characteristic where output drops if technology increases too fast. To illustrate this, imagine a scenario in real life that kind of looks like a rapid evolution of some kind of technology of home phones, to cell phones, to smart phones at a rate faster than people know how to make use of them, while also spending money adoption making the intermediary adoptions quite wasteful.
I think we see an aspect of this here, a lot of things we took for granted are changing, shared assumptions are being challenged and it's a period we're all relearning new things. To some extent spending too much time diving on the current iteration of AI tooling might be for nothing if gets invalidated by another sudden jump.
With all these new tools people are building, I can't help but feel they are building foundations on moving soil.
With the industrial revolution extra demand for industrial overcapacity was created in the form of war.
After the war the US created extra demand in the form of consumerism.
China is creating extra demand for infrastructure overcapacity with its belt and road initiative.
I wouldnt underestimate the abililty of the country to creatively create demand to counter oversupply.
Talk to people.
There are an infinite amount of problems to solve.
Deciding whether they’re worth solving is the hard part.
Are any of these people willing to fund an answer to these problems?
I’m really enjoying these LLMs for making ad-hoc tooling / apps for myself. Things that I only need for a day or a week, that don’t need to work perfectly (I can work around bugs).
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.
Maybe have it build some toy apps just for fun! My wife and I were talking once about typing speed and challenged each other to a typing competition. the existing ones I found weren't very good and were riddled with ads, so I had Claude build one for us to use.
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.
Shovel market
https://substack-post-media.s3.amazonaws.com/public/images/6...
Everybody wants to build infra. Automate something which is known and well understood. Hoping someone else will use it to solve end user's problem which is hard to understand, messy and often highly contextual.
To summarize: Everyone wants to automate stuff. Most people do not want to touch boring, large problems.
I find myself building fun tools for myself and things that help with quality of life slightly, but I don’t need all this extra enterprise stuff for that. I actually find myself more likely to use something I built because I am proud of it, even if there is already something on the market that addresses my need.
When there’s a gold rush, sell shovels.
The point is that there's no gold. It's just a shovel rush.
Nailed it!
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.
I feel the same, it's like there's more offer than demand somehow
build us a way out
Sell the shovels!!
Side note, been watching gold prospecting channels lately, there will be these dig sites/claims people go to, they'll do their thing, dig a hole, run it through some angled ramp water contraption... they get like nothing, it's the experience I suppose. But I was wondering what the owner gets from all these people showing up.
They'll work for hours and end up with $4 of gold
Someone on HN pointed out how all the LLM companies are basically going “we made this thing, can y'all please find the billion dollar application for it?” and that really made a lot of things - namely why I’m frequently raising an eyebrow at these tools and the vague promises/demand that we use them - click into place.
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.
building is the easy bit, more than ever.
selling it is the hard part, nothing new there
Another option is to bring your coding skills to a industry not particularly known for using tech.
Steve Jobs used to say every product needs a killer feature
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
Isn't AGI Adult Group Interaction?
Yes, I didn't think ofthat. See he is right. They did achieve AGI, just not the one he wanted
If infirmation arbitrage is the game then it's now a race to distribution channels and trust.
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
Ask an LLM for suggestions on what to build
There are companies making a lot of money directly from software largely written by LLMs especially since Claude Code was released, but they aren't mentioning LLMs or AI in any marketing, client communications, or public releases. I'm at least very aware that we need to be able to retire before LLMs swamp or obsolete our niche, and don't want to invite competition.
Outside of tech companies, I think this is extremely common.
This type of software is mainly created to gain brand recognition, influence, or valuation, not to solve problems for humans. Its value is indirect and speculative.
These are the pets.com of the current bubble, and we'll be flooded by them before the damn thing finally pops.
Speak for yourself. I’ve been using Claude Code to build lots of customer facing things.
I’m on the other hand, I have a million ideas and AI has allowed me to implement so many of them.