A lot of people think AI will change software because it helps us build faster.
And it will.
But I’m not sure that’s the most interesting change.
Because even before AI, large software companies could already build almost anything they wanted.
And still, most products failed.
Not because they couldn’t ship fast enough.
But because building software is not the same thing as building something people actually want to use.
For years, startups already understood this.
That’s why people talked about:
- MVPs
- Product-Market Fit
- fast iteration
- customer feedback
Long before AI.
So maybe AI doesn’t change what matters.
Maybe it simply exposes it more clearly.
Because if software becomes dramatically easier to build, then the bottleneck shifts somewhere else.
And that raises a more interesting question:
What becomes valuable when building is no longer the hard part?
More Software Doesn’t Automatically Create More Value
AI may dramatically lower the cost of creating software.
Which means we’re probably about to get:
- more products
- more features
- more AI tools
- more interfaces
- more complexity
And I think many companies will react in the same way: build more, ship faster, and add more AI capabilities.
But more capabilities don’t automatically create better products.
In many cases, they create the opposite: confusion, friction, and cognitive overload.
The best products rarely win because they have the most buttons.
They win because they make complicated things feel simple.
The Real Value of Software
Think about navigation apps.
Technically, most of them do very similar things: maps, routing, traffic, directions.
But users still strongly prefer certain ones.
Not because they understand the algorithms.
Because some products simply feel easier, clearer, and more trustworthy.
The value of software is often not the capability itself.
It’s helping people navigate complexity successfully.
Maybe that’s why UX still matters so much.
Not because of visuals.
But because good products guide people.
They reduce ambiguity.
They create confidence.
They help users complete tasks successfully without needing to fully understand the complexity underneath.
In that sense, great software often feels less like a tool — and more like a recipe.
Maybe AI Changes What Great Products Look Like
A lot of people assume the future interface is just chat.
Maybe.
But chat also creates new friction.
Users don’t always know:
- what to ask
- how to ask it
- or even what’s possible
Traditional UX still has enormous value.
Good products guide users step-by-step.
They reduce cognitive load.
They help people navigate complexity successfully.
In many cases, the real value of software is not:
“Can this technically be done?”
But:
“Can this be done simply, clearly, and reliably?”
I also think AI may push products to become more adaptive.
Because people don’t actually work the same way.
Some users want: speed, flexibility, advanced control.
Others want: structure, simplicity, guidance, clear flows.
Maybe the future isn't one perfect product for everyone.
Maybe the future is software that adapts more intelligently to different people and different ways of working.
The Bottleneck Shifts Somewhere Else
If AI dramatically lowers the cost of building software, then the bottleneck shifts somewhere else.
Toward:
- understanding people
- reducing complexity
- designing better experiences
- learning faster
- building trust
And maybe that changes how companies should use AI in the first place.
Maybe the biggest opportunity AI creates is not building more software.
Maybe it’s reducing the cost of exploration.
The ability to:
- test ideas faster
- learn faster
- adapt faster
- refine products faster
Because if software creation becomes cheap, then understanding people becomes even more valuable.
Maybe the companies that win in the AI era won’t be the ones building the most software.
Maybe they’ll be the ones learning the fastest.
Curious how others think about this.
