Note: This is part of the product creator series of articles, based on the overview article, The Era of the Product Creator.
As a VP of Product Management at HighLevel, Inc., I’m constantly reminded that prototypes aren’t deliverables—they’re decisions. I recently revisited “The Purpose of Prototypes” from Silicon Valley Product Group, and it reinforced a belief I hold deeply: we prototype to learn faster than risk compounds. In product discovery, the right prototype at the right moment helps us surface assumptions, test them quickly, and focus our teams on evidence over opinions.
When I frame the purpose of a prototype, I anchor on four core risks: value (will anyone care?), usability (can they figure it out?), feasibility (can we build it with our constraints?), and viability (does the business model work?). Each prototype exists to retire a specific risk, not to approximate the final product. If we can’t name the risk and the assumption, we’re not ready to build anything—not even a prototype.
Here’s how I choose: I start with the lightest-weight artifact that can answer the next most important question. If I’m unsure about value, I’ll run a simple landing page, ad test, fake door, or concierge experience. If usability is unclear, I’ll move to paper sketches or a Figma click-through. If feasibility is in doubt, I’ll commission a quick engineering spike, an API mock, or a data model prototype. If viability is the concern, I’ll test pricing, packaging, or acquisition economics before writing a single production line of code.
In our practice, ai-based prototyping and gen ai are accelerants. We use AI to generate realistic UI states, draft microcopy, create test data, simulate edge cases, and scaffold throwaway services for feasibility spikes. This shortens cycles dramatically, especially when paired with disciplined product discovery methods and clear success criteria.
I’ve found that forward deployed engineers working hand-in-hand with design and product lead to our fastest learning loops. We timebox aggressively (often 24–72 hours), instrument every prototype for the signal we need, and refuse to promote ideas to the roadmap until the relevant risk is retired. The result is more confidence, less waste, and momentum that teams can feel.
One recent example: a deceptively simple pricing and messaging test revealed that what we thought was a killer feature didn’t drive willingness to pay—but the workflow time-savings did. A one-day value prototype saved us three sprints of build and a painful launch reversal. That’s the power of purposeful prototyping.
My operating cadence is straightforward: articulate the assumption, select the minimum viable prototype, define what success (and failure) looks like, run the test with the right users, then decide—proceed, pivot, or pause. Repeat until the key value, usability, feasibility, and viability risks are de-risked. Only then do we invest in production.
For product creators, this mindset is liberating. Prototypes are not about polish; they’re about progress. If you’re navigating the transition described in “The Era of the Product Creator,” leaning into focused, risk-targeted prototypes will transform your product discovery velocity and your product management leadership impact.
Inspired by this post on SVPG.
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