# Why KDNA?

AI agents are becoming better at using tools, retrieving documents, and following workflows. But many failures still come from weak judgment rather than missing information.

A model may know many facts about a domain and still make poor choices because it lacks:

- the domain's starting assumptions
- the difference between central and peripheral ideas
- the terms that should not be used
- the predictable traps that distort judgment
- the scenario signals that change what matters
- the reasoning path from principle to action

KDNA packages these elements into a structured, inspectable, and reusable format.

## The Judgment Layer

KDNA does not retrieve documents. It does not execute tools. It does not replace memory. It does not replace skills.

Instead, it shapes how the agent interprets and uses all of the above.

## The Minimum Useful Difference

A KDNA domain is useful only if the loaded agent behaves differently from an unloaded agent in judgment quality.

If the only difference is that the agent repeats special vocabulary, the KDNA is not working.
