How to treat Prototypes as Decision-Making Tools

​Dear Reader,​

You've probably heard the statement "With the friction of building nearing zero, it's even more important to have conviction about what to build and why" before. Truth is, this reduction in friction does not just apply to software in production. It also applies to the methods you use before that.

The comparison I see to "pre-AI" ways of working is that teams, which were good at or limited to qualitative interviews, tried to reduce the uncertainty around each Discovery question with, you guessed it, interviews. I call these dogmatic defaults.​

​A recent article by Ravi Mehta prompted (pun intended) me to revisit this idea - only this time with prototypes.

With everyone on your team (and in the boardroom) getting excited about prototyping with Lovable, V0 & Co., it's tempting to prototype every uncertainty you're trying to reduce. But that's dogmatic defaults all over again - just in a different color.

We have to remember what prototypes can help you learn:

• Does this interaction feel right?
• Does the flow make sense?
• Can customers navigate this UI without getting stuck?
• Do these two design directions trigger different reactions when people click through them?
• Is this integration technically feasible before we commit engineering weeks to it?

They're also fantastic alignment tools since a visual idea can replace lengthy written and spoken discussions.

What prototypes can't tell you

They won't get you to informed conviction about scaled adoption or willingness-to-pay. Not because the tools aren't good enough yet, but because those questions require a different category of evidence.

Prototype reactions are attitudinal. Adoption and willingness-to-pay are behavioral. Someone saying "yeah, I'd use this" while clicking through your Lovable prototype in a 30-minute interview tells you almost nothing about whether they'll actually trade their time, attention, or money for it when the moment of truth arrives.

Humans are notoriously bad at predicting their own future behavior. No prototype, no matter how fast you produced it or how polished it is, changes that.

The underlying principle

Every discovery question deserves a method that matches it. The temptation with any new tool is to let the hammer pick the nail.

The question isn't "Should we prototype this?" The question is "What are we trying to decide, and what's the lightest, most honest way to get evidence for it?"

Sometimes that's a prototype. Sometimes it's a fake door. Sometimes it's a pricing page with a pre-order button. Sometimes it's still a good old interview.

The AI era doesn't make prototypes the answer to everything. It just makes them cheap enough to be the answer to more things than before. Which is why choosing when not to prototype is now a skill worth sharpening.

Thank you for Practicing Product,

​Tim​

If you consume one thing this week, make it this...

Who is Tim Herbig?

As a Product Management Coach, I guide Product Teams to measure the real progress of their evidence-informed decisions.

I focus on better practices to connect the dots of Product Strategy, Product OKRs, and Product Discovery.