Pattern Without Overgeneralization

You see a pattern three times and declare a law.

"Remote teams always move slower."

"Adding people always creates drag."

"Technical founders always struggle with delegation."

You're not wrong. You saw the pattern. It happened three times.

But pattern recognition without context discrimination is just sophisticated bias.

The skill isn't seeing patterns. AI can find patterns in seconds that would take you months to notice.

The skill is knowing when the pattern applies and when it doesn't.

Remote teams move slower… when communication infrastructure is weak. They move faster when you've designed for async.

Adding people creates drag… when coordination overhead exceeds new capacity. It accelerates when you've designed for autonomy.

Technical founders struggle with delegation… when they hire for execution instead of judgment. They excel when they build leadership bench strength early.

The pattern is real. The boundary conditions determine whether it fires.

Good judgment pairs pattern recognition with context discrimination.

It asks: Does this pattern apply here? What's different about this situation? What conditions make this pattern break? What am I missing that changes the dynamic?

Pattern recognition is seeing similarity.

Context discrimination is seeing difference.

You need both.

Otherwise you're just applying yesterday's lessons to today's different problem.