AI Output History

Review generated outputs with prompt, model, user, latency, feedback, cost, and downstream action history for debugging and reuse. This example brings All outputs and Saved together so AI product teams can find the next task without losing context.

It includes representative records such as Enterprise summary output and CRM follow-up draft. Use the screenshot to study the layout, then adapt its components and product states to your own design system.

AI Output History
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Template facts

Screen

Table

Primary action

Export history

Pattern

Table

State

Default, loading, empty, error, permission, success

Design system

Configurable product UI theme

What this screen helps users do

Product teams need to export history while keeping outputs today, saved and exceptions visible. The interface should show what changed and who should act next.

Key elements

  • Main workspace: All outputs gives users an obvious place to start.
  • Supporting view: Saved keeps the related context close.
  • Primary action: Export history stays visible when people need it.
  • First signal: Outputs today shows a useful value (1,842).
  • Second signal: Saved gives additional context (126).
  • Sample record: Enterprise summary output.
  • Next record: CRM follow-up draft.

States worth designing

  • No rows in current filters: say what changed, protect progress, and offer a clear next step.
  • Sorting or bulk action in progress: say what changed, protect progress, and offer a clear next step.
  • Row update conflict: say what changed, protect progress, and offer a clear next step.
  • Bulk update partly failed: say what changed, protect progress, and offer a clear next step.
  • Restricted columns: say what changed, protect progress, and offer a clear next step.
  • Export complete: say what changed, protect progress, and offer a clear next step.

Where this screen sits in the flow

All outputs → Saved → Export history → Review outcome

Patterns used

Table, All outputs, Saved, contextual actions, error recovery

Why these choices work

Prioritize columns that help people act. Keep filters when readers drill into details and return; show who owns each unresolved exception.

Pay attention to all outputs and saved. People need to distinguish Enterprise summary output from CRM follow-up draft. Keep outputs today visible, especially when a record changes owner or status.

Before this screen reaches handoff, verify keyboard focus, empty and permission states, and what happens after someone chooses “Export history”. Make error recovery as clear as the happy path.

Related screen examples to explore next: AI Safety Review, Human Review Queue, Evaluation Dataset.

Start from this in Figr

Design a ai output history screen inside our existing product. Use our current components, tokens and content language. Include All outputs and Saved views, credible records like Enterprise summary output, and a clear “Export history” action. Use our product permissions and show loading, empty, error and success states. Keep the output editable in Figma.

Open Figr