Get your knowledge ready for AI

An orderly glass archive with one lavender folio selected above the others.

Useful answers start with source material that people can trust, maintain, and access appropriately.

Choose a bounded collection

Start with the information needed for one useful workflow. Bringing every document into the first version makes it harder to understand missing, duplicated, or conflicting guidance. Identify an authoritative source for each important topic and someone who can resolve disagreements. Old drafts and current policy should not appear equally dependable to a reader.

Keep context with the content

A passage is easier to use when its title, owner, effective date, and scope travel with it. Preserve the relationships that make a document understandable, including headings and relevant tables. Consider how someone would verify an answer against the original source. If that connection is difficult, improve it before extending the collection.

Editorial illustration of branching paths with one route picked out in blue.
Source quality, context, and access controls each contribute to a dependable knowledge system.

Respect access in the application

Decide which information each user may retrieve and enforce that decision in the surrounding application and data services. Instructions to the model are not a substitute for access controls. Test with different user roles and include examples where relevant information exists but the current user should not receive it.

Plan for change

Specify how a correction, replacement, or deletion reaches the system. Test those changes as deliberately as new content. A knowledge collection needs ongoing ownership: someone to review outdated guidance, handle reported errors, and explain which sources the system currently uses.

In summary

Begin with a bounded collection of authoritative sources. Preserve their context, enforce access in the application, and assign ownership for corrections, replacements, and deletions.

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