For leaders overwhelmed by AI, a practical first step is to apply a lean startup methodology. Mobilize a bright, cross-functional team, encourage rapid, messy iteration without fear, and systematically document failures to enhance what works. This approach prioritizes learning and adaptability over a perfect initial plan.

In an age of rapid AI prototyping, it's easy to jump to solutions without deeply understanding the problem. The act of writing a spec forces product managers to clarify their thinking and structure context. Writing is how PMs "refactor their thoughts" and avoid overfitting to a partially-baked solution.

Traditional "writing-first" cultures create communication gaps and translation errors. With modern AI tools, product managers can now build working prototypes in hours. This "show, don't tell" approach gets ideas validated faster, secures project leadership, and overcomes language and team barriers.

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.

A prototype-first culture, accelerated by AI tools, allows teams to surface and resolve design and workflow conflicts early. At Webflow, designers were asked to 'harmonize' their separate prototypes, preventing a costly integration problem that would have been much harder to fix later in the development cycle.

Moving from a science-focused research phase to building physical technology demonstrators is critical. The sooner a deep tech company does this, the faster it uncovers new real-world challenges, creates tangible proof for investors and customers, and fosters a culture of building, not just researching.

Instead of writing detailed Product Requirement Documents (PRDs), use a brief prompt with an AI tool like Vercel's v0. The generated prototype immediately reveals gaps and unstated assumptions in your thinking, allowing you to refine requirements based on the AI's 'misinterpretations' before creating a clearer final spec.

Traditional agile development, despite its intent, still involves handoffs between research, design, and engineering which create opportunities for misinterpretation. AI tools collapse this sequential process, allowing a single person to move from idea to interactive prototype in minutes, keeping human judgment and creativity tightly coupled.

Instead of immediately building, engage AI in a Socratic dialogue. Set rules like "ask one question at a time" and "probe assumptions." This structured conversation clarifies the problem and user scenarios, essentially replacing initial team brainstorming sessions and creating a better final prompt for prototyping tools.