RunLLM's Knowledge Base Optimization feature systematically improves document quality in three steps:
- Pain Point Diagnosis: View the AI-generated question hotspot map in the Insights panel to identify topics that are frequently asked but for which documentation is missing (e.g., "OAuth 2.0 authorization process" may be marked as a red warning area).
- Intelligent Completion: The first draft is automatically generated based on the document framework suggested by the AI (Markdown export is supported), and the technical writer only needs to add details. Practical tests show that this approach reduces the document writing time by 40%.
- Closed-loop verificationThe percentage of AI references to the new version of the document is checked by simulating user questions after updating the document through the "Query Simulation" feature.Arize increased the document coverage from 651 TP3T to 891 TP3T after using this method.
Advanced Tip: Turn on version control to ensure that the AI prioritizes referencing the latest version when documents are updated.
This answer comes from the articleRunLLM: Creating an enterprise-grade AI technical support assistantThe
May not be reproduced without permission:AI productivity tools " How to optimize the completeness and usability of technical documentation?
