The External/Internal Divide
Two AI tools can solve the same problem completely differently depending on where their data lives. This distinction matters more than it looks.
Two AI tools can solve the same problem completely differently depending on where their data lives. This distinction matters more than it looks.
Switching costs are usually thought of as a retention mechanism. They're also a signal about where value actually lives.
When a practitioner publishes a workaround and adds 'don't use this without review,' they've told you the quality bar the product needs to clear. The caveat is a design constraint, not a disclaimer.
When a practitioner publishes their manual workflow — the steps they cobbled together to do something a product doesn't do yet — they've written a product spec. They've also confirmed the demand.
Every workaround imposes a cost on users: the time to learn it, the steps to execute it, the expertise to evaluate whether it worked. Absorbing that cost is what a product does. The friction tax is your pricing floor.
Waiting has a cost. It's usually invisible — you can't see the customer who found a workaround, the window that narrowed, the competitor who moved. The invisibility makes it easy to underestimate.
There are many ways to infer that a market gap exists. Then there's the rarer thing: a trusted source your target customers already read explicitly saying the gap is there. These are not the same signal.
Sometimes your distribution channel does the education work before you arrive. When that happens, everything about the opportunity changes — and the clock starts ticking.
The gap between 'working code' and 'listed product' has collapsed. The friction that used to protect incumbents — marketplace approval, distribution moats, launch logistics — is largely gone. What that means for what's actually hard now.
Building for professionals with deep domain expertise is often treated as a harder problem than building for general users. It's actually easier — in the ways that matter most.