if u imagine the stack as: customers on top, over business, over analysis, over software, over machines/infrastructure..
25+ years ago i thought that DSLs and such very-high-level-mostly-formalised-descriptions will move the line between what-product-is-aka-business-analysis and software/coding towards software, reducing its part in the whole stack.
Well, it did not happen, just the opposite - instead the developers become expected to know everything from infrastructure to software to analysis to business domain and higher. So, stack became something like customers over business over... software-dev. Requirements, analysis... mostly gone / done by devs.
Now if that whole "software" part collapses into zero-margin, i see two ways: either businesses very quickly resurrect the business-analysis (what the product is) and make that their margin/moat, or the customers start making their own software (as throwaway 100 wrongs is now possible) - and removing the business from the whole transaction...
The equation for making money with software changed forever in 2026.
But not the way you think. And not the way everyone says.
Everyone's celebrating that AI made building cheap. They're missing what it made expensive.
The equation was always: Demand × Product × Attention = Money
Here's what actually changed:
Product collapsed to near-zero. Lovable ships MVPs in 2 hours. Cursor writes your backend in 30 minutes. Claude Code generates entire stacks. Building went from $50K and 6 months to $500 and 6 hours.
Incredible. Genuinely world-changing. So naturaly, billions are pouring into the AI application layer. The opportunity is massive and real.
But here's the part nobody's talking about:
Demand got a lot harder. Not easier. HARDER.
Why? Because anyone can build an MVP now and everybody does. But the pool of good ideas didn't grow. The number of people chasing them grew 100x overnight.
Attention became nearly impossible. Thousands of new apps launch daily. Your customers are buried in options. Standing out went from hard to borderline impossible.
And here's the brutal part: 42% of startups still fail because they built something nobody wanted. Not slowly. Not badly. Just the wrong thing.
That number isn't improving. It's getting worse.
Because everyone's optimizing the wrong variable. They're focused on:
Shipping faster
Building cheaper
Iterating quicker
Almost nobody is focused on:
Validating systematically
Testing demand first
Talking to customers before touching code
AI didn't solve the hard problem. It made the easy problem trivial and exposed what the hard problem always was: figuring out what people actually want.
Yet nobody is tackling demand testing and validation systematically. Well, almost nobody. We do at buildsherpa.ai.
Everyone's racing to build. Nobody's stopping to ask "should I?" So the discipline to validate first is the only edge left. Because in a world where everyone can ship an MVP in a weekend, knowing WHAT to build is the only remaining moat.
The beginning of the equation is now THE MOST IMPORTANT part.
Demand. Not Product. Not Attention.
Demand.
Because if Demand = 0, the rest doesn't matter:
0 × Easy × Hard = $0
You can build anything now.
Which means you better know WHAT to build.
Validate first. Ship second.
The speed at which you fail is not a metric.
What stuck out to me once I reflected on my failed startup, after I gave up emailing ppl who didn't care about what I built, is that it's actually hard to imagine that I put months into validating instead of building.
It just doesn't really come naturally to my mind. Yet, the fact is, clear as day, that I would have been perhaps better off actually putting 8 (or 10) hrs a day investigating demand.
Building gives you code and screens, which show momentum, while investigating demand mostly gives you negative information, which feels like you're not going anywhere - even when it’s the highest leverage work.
For me, I reframe validation as finding out what people already do ... not trying to convince anyone or predict any kind of behavior. It’s much more simple and less satisfying than building, but it helps me make decisions faster.
if u imagine the stack as: customers on top, over business, over analysis, over software, over machines/infrastructure..
25+ years ago i thought that DSLs and such very-high-level-mostly-formalised-descriptions will move the line between what-product-is-aka-business-analysis and software/coding towards software, reducing its part in the whole stack.
Well, it did not happen, just the opposite - instead the developers become expected to know everything from infrastructure to software to analysis to business domain and higher. So, stack became something like customers over business over... software-dev. Requirements, analysis... mostly gone / done by devs.
Now if that whole "software" part collapses into zero-margin, i see two ways: either businesses very quickly resurrect the business-analysis (what the product is) and make that their margin/moat, or the customers start making their own software (as throwaway 100 wrongs is now possible) - and removing the business from the whole transaction...
The equation for making money with software changed forever in 2026. But not the way you think. And not the way everyone says.
Everyone's celebrating that AI made building cheap. They're missing what it made expensive.
The equation was always: Demand × Product × Attention = Money
Here's what actually changed: Product collapsed to near-zero. Lovable ships MVPs in 2 hours. Cursor writes your backend in 30 minutes. Claude Code generates entire stacks. Building went from $50K and 6 months to $500 and 6 hours.
Incredible. Genuinely world-changing. So naturaly, billions are pouring into the AI application layer. The opportunity is massive and real.
But here's the part nobody's talking about: Demand got a lot harder. Not easier. HARDER.
Why? Because anyone can build an MVP now and everybody does. But the pool of good ideas didn't grow. The number of people chasing them grew 100x overnight.
Attention became nearly impossible. Thousands of new apps launch daily. Your customers are buried in options. Standing out went from hard to borderline impossible.
And here's the brutal part: 42% of startups still fail because they built something nobody wanted. Not slowly. Not badly. Just the wrong thing. That number isn't improving. It's getting worse.
Because everyone's optimizing the wrong variable. They're focused on: Shipping faster Building cheaper Iterating quicker
Almost nobody is focused on: Validating systematically Testing demand first Talking to customers before touching code
AI didn't solve the hard problem. It made the easy problem trivial and exposed what the hard problem always was: figuring out what people actually want.
Yet nobody is tackling demand testing and validation systematically. Well, almost nobody. We do at buildsherpa.ai.
Everyone's racing to build. Nobody's stopping to ask "should I?" So the discipline to validate first is the only edge left. Because in a world where everyone can ship an MVP in a weekend, knowing WHAT to build is the only remaining moat.
The beginning of the equation is now THE MOST IMPORTANT part.
Demand. Not Product. Not Attention.
Demand.
Because if Demand = 0, the rest doesn't matter: 0 × Easy × Hard = $0
You can build anything now. Which means you better know WHAT to build.
Validate first. Ship second. The speed at which you fail is not a metric.
I learned this the hard way..
What stuck out to me once I reflected on my failed startup, after I gave up emailing ppl who didn't care about what I built, is that it's actually hard to imagine that I put months into validating instead of building.
It just doesn't really come naturally to my mind. Yet, the fact is, clear as day, that I would have been perhaps better off actually putting 8 (or 10) hrs a day investigating demand.
Building gives you code and screens, which show momentum, while investigating demand mostly gives you negative information, which feels like you're not going anywhere - even when it’s the highest leverage work. For me, I reframe validation as finding out what people already do ... not trying to convince anyone or predict any kind of behavior. It’s much more simple and less satisfying than building, but it helps me make decisions faster.
Exactly, talk to them and learn from them.
I do want to do this at scale though, run various threads and ideas (meanwhile i checked OP's platform, it coudl actually be be useful, so thanks).