AI tools democratize prototyping, but their true power is in rapidly exploring multiple ideas (divergence) and then testing and refining them (convergence). This dramatically accelerates the creative and validation process before significant engineering resources are committed.

AI drastically lowers the cost of exploration. The best teams leverage this by building many prototypes and exploring multiple directions, knowing most will be discarded. This 'wasted work' is a sign of effective discovery, leading to better final products.

Capable AI coding assistants allow PMs to build and test functional prototypes or "skills" in a single day. This changes the product development philosophy, prioritizing quick validation with users over creating detailed UI mockups and specifications upfront.

Traditional SaaS development starts with a user problem. AI development inverts this by starting with what the technology makes possible. Teams must prototype to test reliability first, because execution is uncertain. The UI and user problem validation come later in the process.

In traditional software, building is the slowest step. With AI, a functional prototype can be created almost instantly. This shifts the critical bottleneck to the 'define' and 'feedback' stages of the development loop, demanding new organizational skills.

In AI, low prototyping costs and customer uncertainty make the traditional research-first PM model obsolete. The new approach is to build a prototype quickly, show it to customers to discover possibilities, and then iterate based on their reactions, effectively building the solution before the problem is fully defined.

Companies are using AI tools like Perplexity Computer to build functional MVPs almost instantly. This cultural shift allows teams to interact with a working version of an idea to gauge its value before investing significant engineering resources, replacing the traditional text-based planning phase.

Historically, resource-intensive prototyping (requiring designers and tools like Figma) was reserved for major features. AI tools reduce prototype creation time to minutes, allowing PMs to de-risk even minor features with user testing and solution discovery, improving the entire product's success rate.

As AI makes the act of writing code a commodity, the primary challenge is no longer execution but discovery. The most valuable work becomes prototyping and exploring to determine *what* should be built, increasing the strategic importance of the design function.