In hardware automation, a "go slow to go fast" approach is essential. Iterations are too slow and costly once hardware is built. Front-loading validation through drawings and simulations avoids major architectural issues that often get buried later due to project momentum or "go fever."

Forget the linear waterfall or even the classic design loop. Dylan Field sees today's best product teams using a non-linear process, 'hopping' between ideation, design, prototyping, and code in any order. The key is the ability to start anywhere and move fluidly between these stages.

True design intuition isn't innate; it's built through repetition. The fastest way to learn is to take many "shots on goal." Focus on generating a high quantity of rough, low-fidelity ideas and storyboards, rather than a few polished ones, to accelerate your learning and discovery process.

The team no longer relies solely on PRDs and design docs. Product managers are now required to build a functional prototype as a core part of the development cycle, ensuring ideas are validated with a working model early on.

An interaction can look perfect in a static tool like Figma but feel terrible when built. Prototyping allows designers to experience the 'feel' of their work—a crucial step for validating ideas, developing intuition, and creating higher-quality products that you can't get from static mockups alone.

Early demos shouldn't be used to ask, "Did we build the right thing?" Instead, present them to customers to test your core assumptions and ask, "Did we understand your problem correctly?" This reframes feedback, focusing on the root cause before investing heavily in a specific solution.

Product development's most valuable activity is iteration. The goal isn't to avoid failure, but to achieve it quickly and cheaply to maximize learning. A good failure uses the simplest possible prototype (e.g., duct tape and a 2x4) to answer a key question and inform the next step.

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.

The panel suggests a best practice for AI prototyping tools: focus on pinpointed interactions or small, specific user flows. Once a prototype grows to encompass the entire product, it's more efficient to move directly into the codebase, as you're past the point of exploration.