Building MarketScope taught me one thing: AI loves to hype ideas

The first version of MarketScope was fast and useful — it compared new startup ideas with existing products using public data, demand patterns, and market gaps.

It was meant to be a quick scanner to help founders avoid duplicate ideas and save hours of research.

But there was a problem:

AI often gave optimistic scores because it didn’t consider real-world execution issues.

For example, an idea for a unified aggregator of multiple streaming platforms scored 75/100, simply because demand and market gaps looked strong.

But in the real world, you’d face licensing, legal barriers, and heavy funding requirements.

So I had to fix that.

I redesigned the analysis layer so MarketScope now evaluates:

• execution difficulty

• operational complexity

• competitive feasibility

It’s learning to behave like a practical market analyst, not a hype machine.

This is the direction I’m building toward — realistic, early-stage validation that founders can trust.