AI can reduce the time between an idea and working software. It cannot make the underlying opportunity worthwhile.
A company can now produce prototypes at a pace that would have been difficult only a few years ago. That creates a new temptation: to treat faster development as evidence that the right thing is being built.
Product management moves upstream
The difficult questions are still about people, markets, constraints, and behavior. Who needs this? How do they handle the problem now? Will the product create a meaningful improvement? What would make someone adopt it?
Good product management helps answer those questions before teams commit heavily to implementation. As execution accelerates, the cost of a mistaken product direction can accumulate faster too.
AI changes the process
Research synthesis, exploratory prototypes, testing, and delivery can all benefit from new AI capabilities. Product teams should examine those opportunities across the full lifecycle, with appropriate review of evidence, quality, and security.
The goal remains a product that earns its place in the world. Better tools make that possibility more accessible. Judgment determines where to aim them.