Trustworthy & Reliable AI

Action Audit Trail

Provide a timestamped, structured log of every action the agent took - grouped by task, with reversibility status, selective undo, and diff views - so users can review and correct agent behavior after the fact.

What is Action Audit Trail?

After an agent has acted - especially across multiple steps or over extended periods - users need a clear, reviewable record of what happened. This is fundamentally different from traditional undo/redo because agentic actions may span multiple systems, occur asynchronously, and have cascading consequences. A user who discovers their agent has sent 15 emails, rescheduled 3 meetings, and updated a spreadsheet needs to quickly understand what happened, why, and how to reverse specific actions. The Action Audit Trail provides a timestamped log grouped by task with plain-language descriptions, reversibility color-coding (green/amber/red), selective undo capabilities, and before/after diff views for document modifications. This extends source attribution from citing information sources to citing action sources.

Problem

After an agent has acted across multiple steps or systems, users need a clear, reviewable record of what happened. Traditional undo/redo doesn't work for agentic actions that span multiple systems, occur asynchronously, and have cascading consequences.

Solution

Provide a timestamped, structured log of every agent action grouped by task, with plain-language descriptions, reversibility color-coding, selective undo for individual actions, and before/after diff views for modifications.

Real-World Examples

Implementation

AI Design Prompt

Guidelines & Considerations

Implementation Guidelines

1

Default view should be a timeline grouped by task, not a raw chronological log. Users think in goals, not timestamps.

2

Color-code by reversibility: green for fully reversible, amber for partially reversible, red for irreversible actions.

3

Include a 'What changed?' diff view for document modifications - show before/after, not just 'edited file.docx'.

4

Allow filtering by action type, time range, and affected system for efficient review.

5

For high-volume agents processing hundreds of items, provide summary statistics alongside the detailed log.

6

Include export capability for compliance and team review contexts.

7

Support selective undo - let users reverse individual actions in a chain without undoing everything.

Design Considerations

1

Audit review rate: what percentage of users review the audit trail after agent actions

2

Selective undo rate: how often users undo individual actions indicates the trail is usable and valuable

3

Time-to-discovery: how quickly users identify and correct problematic agent actions

4

Balancing log detail with performance - storing every action at full fidelity has storage and rendering costs

5

Grouping actions by task requires the agent to maintain goal context throughout execution

6

Selective undo may have cascading effects - undoing step 3 of 5 may invalidate steps 4 and 5

7

Privacy implications of detailed action logging, especially for shared or enterprise environments

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About the author

Imran Mohammed is a product designer who studies how the best AI products are designed. He studies and documents AI/UX patterns from shipped products (36 and counting) and is building Gist.design, an AI design thinking partner. His weekly analysis reaches thousands of designers on Medium.