AI tools have made building software incredibly fast, shifting the primary bottleneck for new products. The hard part is no longer the initial build, but the timeless challenge of marketing, distribution, and growing an audience. Technical barriers have fallen, but market barriers remain.

Even if AI can autonomously generate thousands of viable companies, their success is constrained by the scarce resource of customer attention. The proliferation of AI-generated businesses creates a discovery problem, as potential customers lack the time to find and evaluate them, making marketing the key barrier.

Metrics like new app creation are spiking due to AI tools, but this increased activity doesn't ensure value. This mirrors the smartphone era, where the explosion of photos devalued the marginal photo. AI's productivity may simply create more low-margin noise.

AI tools are causing an explosion of features, making execution a commodity. The core skill for product teams is no longer building, but deeply understanding user needs. The winning products will be those that solve real problems, not those that are merely built fast.

The ease of app creation and AI content generation will exponentially increase products competing for user attention. However, the primary acquisition channels (Meta, Google, TikTok) remain fixed. This supply-demand imbalance will cause a customer acquisition cost (CAC) crisis for marketers.

AI is creating a fork in marketing strategy. It disrupts traditional demand acquisition channels like search, making it harder and more expensive to get measurable traffic. Simultaneously, it provides powerful new tools to monetize existing demand more effectively. This forces a strategic shift from a volume-based to a value-extraction model.

A key driver of AI adoption in the workplace is its ability to smooth over moments of high cognitive effort, like starting a document from a blank page. For brains already exhausted by constant context switching, this is a welcome relief but ultimately creates a dependency that further weakens the ability to focus.

The proliferation of AI has dramatically reduced development time, shifting the primary constraint in product delivery from engineering capacity to the customer's ability to learn and integrate new features into their workflow. More output no longer guarantees more value.

With AI lowering the barrier to building software, getting user attention is harder than ever. This shifts the competitive advantage to distribution. Incumbents can spray a 'good enough' AI model across billions of users, establishing a default that's difficult for a superior startup product to displace.