Knowledge Updates
Fixes and answers discovered in real conversations flow back into your knowledge base as reviewed, credited, versioned updates — so the docs age at the speed of reality, not the speed of free afternoons.
Think of the family recipe binder where everyone knows the oven temperature on page 12 is wrong — but nobody ever fixes the page, so the correction lives by word of mouth. This is the person who actually updates the binder: every real correction becomes a proposed edit, someone who knows the recipe approves it, and the next reader gets the right temperature.
The problem, in plain words
Your knowledge base was accurate the day it was written. Since then, the product changed, the policy changed, the workaround on page 12 stopped working — and the docs stayed put. The truth now lives in scattered corrections: a resolved thread here, a teammate's actually, that changed message there. And stale docs are not just annoying — every AI tool that retrieves answers from your knowledge base is quietly poisoned by them, confidently serving last year's instructions.
What we set up
We build the return path. When a resolved thread or a correction shows that a knowledge page is wrong or missing, a draft update is proposed automatically. The owner of that channel or topic reviews it: approve, edit, or reject. Approved drafts land in the knowledge source as versioned changes (every edit is recorded, so you can see what changed and when, and roll it back) with attribution (the person behind the fix is credited). Then two things happen downstream: retrieval picks up the change at the next refresh, so your AI tools start answering from the updated page — and the eval set (your bank of test questions with approved answers) re-runs against the updated corpus, catching anything the change quietly broke.
How it works, step by step
- Reality corrects the docs
A resolved thread, a flagged mistake, an approved better answer — evidence that a knowledge page is wrong or missing.
- A draft update is proposed
The correction is turned into a concrete edit of the specific page — ready to review, not a to-do item.
- The owner reviews it
The person responsible for the topic approves, edits, or rejects. Nothing changes the official record without a human yes.
- The change lands, versioned and credited
The update carries its author and its history. What changed, when, and by whom is always answerable.
- Downstream systems catch up
Retrieval picks up the new content at the next refresh, and the test set re-runs against the updated corpus to catch surprises.
What changes for you
Before: docs decay silently, corrections live in chat scrollback, and your AI answers from pages everyone privately knows are stale. After: knowledge freshness is something you can measure, updates flow from real conversations at the rate reality changes, and retrieval quality holds because the sources underneath it stay true. What it won't do: it won't bypass your reviewers — a draft nobody approves changes nothing, so owners who sit on reviews remain a bottleneck the system makes visible rather than removes.