Only the old hand knew the data rules. Will the AI still know them?

#Someone knows the traps, but nobody wrote them down

Every company has a veteran who knows the traps in its data. "Amounts in that table were in thousands of won until 2023." "Status code 09 isn't cancelled. It's on hold." "The customer table never deletes customers who left, so always filter them out." Remarks like these rarely make it into a handover document. They live in a few people's heads and disappear when those people change departments or leave the company, and the next owner makes the same mistakes and finds the same traps all over again.

OwlAI attaches that knowledge to the data itself. A fact confirmed in a conversation becomes a note on the table, and the next time anyone asks about that table, the AI reads the note too. When the veteran leaves, "09 means on hold" is not in their head but in a note on the table.

#Facts confirmed in conversation become table notes

When the AI confirms a long-lived fact about the data during a conversation, it can leave a note on that table or on a specific column: what a column means, what a code value stands for, how to join to another table, what to watch for when using the data.

Notes come about in two ways. A user may tell the AI, "This column uses a different unit, be careful." Or the AI may spot an odd value in a query result, confirm the cause, and record it. Either way, nobody has to sit down and write documentation.

#A note from sales shows up in a finance hire's answer

Everyone who uses a table sees its notes. When the AI opens a table's information to query it, the notes come along. A "watch the amount unit" note someone in sales left last month shapes the answer to a question a new hire in finance asks today.

Because everyone sees them, there are limits on what notes hold. A note contains only facts about the data. The AI is instructed not to record names, employee IDs, email addresses, or who did what. Anything that applies to a single conversation, or that will turn wrong over time, stays out as well.

#Notes are hints to check before trusting

Knowledge that many people build up includes some mistakes. So the AI treats a note as a hint to check rather than something to take at face value. It consults the note, checks it against the actual data, and can correct or delete a note that is wrong or outdated. Correcting or deleting a note also requires permission on that table.

#The knowledge stays with the table when people change

Administrators open the Memory tab in a table's details on the database screen to see its notes, newest first. A note that contains personal information or a stale aggregate can be deleted there, and it drops out of everyone's answers starting with the next one.

A trap recorded once as a note goes into the answers of other people who ask about that table. Without anyone writing a separate handover document, facts confirmed in everyday conversations with the AI stay on as your team's data knowledge.

So it pays to start while the veteran is still around. If they mention the traps they know in conversations with the AI, the AI can record each one as a note, and from then on that remark shapes the answer to the next owner's very first question.