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This feature is currently in Beta. Enable it in your agent settings to start testing with your team.
AI agents can now improve your semantic layer by proposing changes to your data models. When enabled, agents can update field descriptions, create new metrics, and refine your data documentation based on conversations and user feedback. All changes are tracked in changesets and can be reviewed or reverted at any time.

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How it works

When self-improvement is enabled, your AI agent can:
  1. Propose changes to your semantic layer during conversations
  2. Apply changes immediately to a changeset (batch of changes)
  3. Track all modifications with full history and attribution
  4. Allow review and rejection of changes by authorized users
Changes are visible in the chat interface and can be managed through the Project Settings > Changesets page.
Self-improvement changes in chat updating a description of a dimension

Updating a description of a dimension

Self-improvement changes in chat custom metric

Creating a custom metric

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What agents can improve

Update descriptions for better documentation:
  • Explore descriptions to clarify data sources and use cases
  • Metric descriptions to explain calculations and business logic
  • Dimension descriptions to provide field context
Create new metrics based on conversations:
  • Custom aggregations derived from existing dimensions

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Enabling self-improvement

To enable self-improvement for an agent:
  1. Go to your agent settings
  2. Toggle the “Enable Self-Improvement” switch
  3. Save your changes
Enable self-improvement toggle
Only admins and developers can enable and use self-improvement

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Managing changes

All proposed changes are tracked in changesets, which you can access from Project Settings: View all changes:
  • Navigate to Project Settings > Changesets
  • See a complete list of proposed changes with details about what was modified
  • View who proposed each change and when
Self-improvement changes in changeset view from project settings
Review changes in chat:
  • Each proposed change appears as a card in the conversation
  • Click “View Changeset” to see the full details
  • Use the “Reject” button to revert changes you don’t want
Revert changes:
  • Individual changes can be rejected directly from the chat interface
  • Use “Revert” in the changesets page to undo specific changes
  • Use “Revert All” to undo multiple changes at once
  • If a project is re-deployed, the changeset will be applied if possible
Once a change is reverted, the action cannot be undone. The semantic layer will return to its previous state for that field or metric.