Everyone is obsessed with prompt engineering.

I think that’s already becoming the wrong abstraction.

The best enterprise agents won’t win because they started with a better prompt.
They’ll win because they build better feedback loops.

Something subtle but extremely important:
agents didn’t improve from adding more rules.

It improved when they stopped treating the agent like software…
and started treating it like a junior employee.

That changes everything.

Most companies are still trying to write giant decision trees:
“If user says X, respond with Y.”

That breaks immediately in judgement-heavy work.

Support. Sales. Recruiting. Community. Code reviews. Product feedback. Executive communication.

The edge cases are infinite.

So the real question becomes:
How does the agent learn your company’s taste over time?

Not rules. Taste.

What feels defensive. What feels authentic.
When to push. When to empathize. What your company sounds like under pressure.

That knowledge usually lives implicitly inside teams.

Agents force companies to finally externalize it.

Which means the real moat in AI may not be the model at all.

It may be the organization that best captures, refines, version-controls, and compounds its own judgement.

In other words: the future competitive advantage might be institutional learning velocity.

Not just software velocity.