How AI changes product development.

The biggest change AI brings to product development isn't that every application suddenly needs an AI feature.

It is that the cost of building software has changed.

Historically, turning an idea into software required a fairly expensive chain of work.

Research.

Design.

Frontend.

Backend.

Testing.

Documentation.

Iteration.

Each part required specialized time.

AI doesn't remove all of that.

But it changes the cost structure.

A small team can now explore far more ideas than before.

A developer can generate a first implementation quickly.

A designer can iterate on concepts faster.

A product person can turn a rough idea into a functional prototype without waiting weeks for engineering capacity.

That changes the relationship between ideas and execution.

The bottleneck moves.

When implementation becomes cheaper, deciding what to build becomes more important.

This is why I don't think AI automatically creates better products.

It creates the ability to build more things.

Those are not the same thing.

If your product thinking is bad, AI lets you build the wrong thing faster.

That is not a technological breakthrough.

It is just more efficient waste.

The teams that benefit most are likely to be the ones that already understand the problem they are solving.

They can use AI to reduce friction between thought and execution.

A two-person team can test ideas that previously required ten people.

A founder can create a functional prototype before hiring a large engineering team.

A product manager can explore interaction patterns directly rather than communicating every idea through documentation.

The software development loop gets shorter.

Think.

Build.

Test.

Learn.

Repeat.

That loop is becoming dramatically cheaper.

The interesting question is what teams will do with that extra capacity.

The answer probably isn't "add more features."

It should be better products.