Hey, Aron here.
I talk to people all the time with huge ideas, but no idea what to do next.

Often, they reach out asking what their next step should be after getting AI feedback. The first move isn’t obvious… they have a huge category-disrupting idea, but stall when it comes time to move.

Do I write a business plan? Do I talk to customers? Do I create a pitch deck? Do I build a landing page?

There’s a paradox at play here. We’re thinking big, but we also need to think small at the same time. And, with AI enabling anyone to build anything, fast - this paradox is even more pronounced.

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Hey Aron, I have an amazing idea to disrupt the concert ticket market.
Hello, I want to disrupt eBay, their fees are outrageous. There’s a better way.
Hey, gym memberships are a scam. I have a better idea and it could be huge.

This sounds like all of us.
Frustration with what exists, huge problems to solve, major opportunities.

But, then what?

In order to take the first step, we need to shrink our idea down to something so incredibly small, so we can make immediate progress and get feedback. This is what I want you to know:

• The big vision is why, but the super-small first version is the how.
  Every great startup had the big vision in mind, but they launched with an embarrassingly small version. Uber, AirBnB, Facebook, Stripe, DoorDash, all started local, and small.

• Most founders confuse the destination with the starting point.
  If you’re trying to build the full vision on day one, that’s why you’re struggling to make progress.

• If you start with a super small first customer group, you’ll learn very fast.
  This is everything. If you go talk to 3 small venues, in person, to learn about what frustrates them, you’ll leave with insights you didn’t have before.

• Scope reduction is the one big change before most founders build.
  Our data shows that around 30% of founders who actually move forward reduce the scope right before they commit. Removing complexity is critical on day one.

• Your first version should feel laughably small.
  If your MVP doesn’t feel a bit embarrassingly small, compared to your big vision, it’s probably still too big. Your first version should barely scratch the surface of the full potential you have in mind.

• Your first 10 customers will shape your idea anyway.
  Founders who talk to real people typically have a clearer, more executable version of their initial vision.

With AI, the cost and timeframe to build have been greatly slashed. It’s not 6-months and $50,000 to build a ticketing platform. It’s $500 in AI credits and one involved weekend. The technical barrier to building the full vision is lower than ever.

This has changed our perception of what starting small even means.

But what stays the same is the customer need. 
AI can build the Ticketmaster killer, but it cannot tell you whether venue owners actually want what you think they want, whether the real problem is fees or something else entirely you haven't discovered yet, or whether anyone will pay for your solution once it exists.

The point is: Building the wrong thing faster is still building the wrong thing.

The new paradox AI creates
AI makes it dangerously easy to skip the small step entirely. Why talk to three concert venues when you can just build the platform this weekend? Now, with AI, the platform gets built and the customers don’t show up. Instead of learning with early conversations, you learn with 3 months of inactivity.

The advice that actually changes in the AI age
Your first version can now be a working product (as opposed to a landing page or manual process) because the tools to build it are so accessible. Instead of the advice being “talk to 10 people, then build” now the advice is "build the smallest version and put it in front of ten specific people before you build anything else."


AI can now help you build the wrong thing, just faster. Quicker doesn’t mean it’s correct. You still need to get the feedback of real users as you take those initial steps to build.

👉 Move your idea forward

Happy to discuss your big idea, any time.

Aron Meystedt
Chief Data Nerd - ValidatorAI

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