AI agents flood market with apps nobody wants or uses

The market is witnessing a strange dual opinion on language models: they either change everything or nothing. New data on mobile app releases shows both extremes are wrong. App submissions are skyrocketing because agents have made shipping code trivial—anyone can generate a functional app in minutes. However, actual user traction is almost nonexistent. This chart proves the disconnect: we are mistaking writing code for solving a problem. When an agent does the macro thinking, you end up with a system you have to read to make sense of, not one you already understand. The code might look identical from the outside, but under the hood, every microscopic choice—abstractions, nomenclature, structure—is debt you inherit. If the agent makes a call you wouldn't have made, the codebase starts resisting the moment you need to pivot or ship a fast update based on user feedback.

This is why thousands of new apps are flatlining. People used agents to avoid the friction of thinking through the project, leaving them with an alien codebase they can't adapt when reality hits. Software development is not just typing lines—it's a discipline of turning fuzzy market problems into testable solutions. The agent is fine for the tail end of that pipeline, but figuring out what the project actually needs is still entirely on you. If you skip that heavy lifting, you just add to the mountain of apps that nobody opens. The irony is that AI's ability to generate code at scale amplifies the biggest error in product development: building something without first understanding the problem.