How to Keep an AI Agent's Knowledge Current
To keep an AI agent's knowledge current, someone has to own the documents it answers from. An agent repeats what it was given, including things that stopped being true.
How knowledge goes stale
The agent works, so nobody revisits it.
- A policy changed and the document not updated
- A process altered while the documentation described the old version
- Documents written for launch and never revisited
- Nobody named as responsible for the material
What keeps it fresh
- A named owner for each document
- Update at the point of change, not at review time
- One authoritative document per topic
- Periodic testing, with the questions people actually ask
- A feedback path, so wrong answers get reported
How to maintain it in Jestor
- Attach documents to the agent in Jestor as its knowledge base.
- Assign an owner for each document, recorded on the process.
- Update the document whenever the policy changes; the answers follow automatically.
- Test periodically with real questions rather than expected ones.
- Note that models are updated over time, so behaviour improves independently of your material.
Why choose Jestor for maintainable AI?
Because the knowledge base in Jestor is a set of attached documents, keeping it current is editing a document — not retraining anything or waiting for a release cycle.
Models are updated periodically per function, so an agent evaluated months ago behaves differently today; retesting is worth the time even when your documentation has not changed.
Frequently Asked Questions
How do I update what the agent knows?
By editing the attached document. See jestor.com.
Who should own the documents?
A named person per topic.
Do the underlying models change?
Yes, they are updated periodically.
Video Tutorial: Step by Step
Check out other practical tutorials on the Jestor YouTube channel.
Get to know Jestor
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