Evolution memory

Evolution memory is where the improvement flow deposits confirmed and shipped patterns. Not a space you or the Agent write into: it’s read-mostly, and Agents that attach it benefit passively. Once attached, the Agent recalls relevant patterns automatically during diagnosis. What lands here:

• Diagnostic patterns failure → confirmed cause → winning fix chains
• Efficacy scores how often each pattern’s reuse actually holds up
• Freshness external facts decay if nobody reprobes them, surfacing revalidation candidates

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When to use it

• Long-lived Agents where quality should compound
• High-volume Agents where the improvement flow accumulates patterns quickly
• Teams that want visibility into how the diagnostic memory grows

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Graph tab

Evolution has two sub-tabs inside its primary lens.

• Metrics A metrics dashboard showing total entries, reuse and recurrence counts, efficacy and freshness distributions, and growth curves over time.
• Graph The diagnostic patterns this space has accumulated, rendered as a 3D graph. Click and drag nodes to explore.

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Log tab

Review when entries were created or updated, in chronological order. Select a log entry to inspect the change.

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Pruning nodes

In the Graph tab, click a node and hit Delete to soft-remove that diagnostic entry. Use this to strip out patterns you don’t think are actually valid. Right after removal, an Undo toast appears in the bottom-right. Click to reverse. It’s a soft remove, so admin tools can recover it later too.

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Relationship with the improvement flow

Evolution is where improvement-flow results land. Every loop through signal → cluster → improvement proposal → simulation → approval → deploy leaves a new diagnostic pattern here. See From signal to fix for the full picture.