Instead of guarding prototypes, build a library of high-fidelity, interactive demos and give sales and customer success teams free reign to show them to customers. This democratizes the feedback process, accelerates validation, and eliminates the engineering burden of creating one-off sales demos.

To convince executives at traditional companies of AI's potential, abstract presentations fail. Instead, provide tangible, immersive experiences. A ride in a Waymo car, for instance, serves as a powerful product demo that makes the future feel concrete and inevitable, opening minds in a way slideshows cannot.

When stakeholders interact with a feature built in actual code, it feels nearly finished. This creates an "aura of inevitability," shifting the decision from allocating resources for exploration to a simple "yes/no" on shipping the feature, which dramatically accelerates buy-in.

Go beyond static prototypes by using text-to-video tools like Flow or Sora to create promotional clips. This final step allows stakeholders to visualize the product in a real-world context and emotionally connect with the user experience, making your pitch significantly more persuasive.

Product teams often use placeholder text and duplicate UI components, but users don't provide good feedback on unrealistic designs. A prototype with authentic, varied content—even if the UI is simpler—will elicit far more valuable user feedback because it feels real.

Before writing code, you can string together hyperlinked screenshots in a design tool like Figma. This creates a 'hacky' prototype that feels like a fully built app to potential customers, allowing for rapid, low-cost user testing and validation.

Instead of providing a vague functional description, feed prototyping AIs a detailed JSON data model first. This separates data from UI generation, forcing the AI to build a more realistic and higher-quality experience around concrete data, avoiding ambiguity and poor assumptions.

In design thinking, early prototypes aren't for validating a near-finished product. They are rough, low-cost "artifacts" (like bedsheets for walls) designed to help stakeholders vividly pre-experience a new reality. This generates more accurate feedback and invites interaction before significant investment.

AI prototyping tools have broken the traditional link between visual fidelity and process maturity. Designers can now create highly realistic, functional prototypes on day one. This makes it challenging to signal to stakeholders that a concept is still early and exploratory, leading to feedback on pixels instead of strategy.