Playbook Reporting

VitallyJanuary 2026

Problem Summary

Playbooks are Vitally's most powerful feature, however, performance was hard to understand at scale. Users can inspect individual run histories or specific objects, but there is no clear, unified view of how a Playbook is behaving overall, where runs break down, or what each action actually produced. This forces teams to click through runs one by one, guess at outcomes, and rely on support to interpret errors, states, or missing outputs, slowing iteration and reducing confidence in automation.

Opportunity

How might we make Playbook behavior and outputs transparent and self-explanatory within the editor, so users can quickly understand what happened, what was created, and where issues occur, enabling faster troubleshooting, better optimization, and confident use of Playbooks at scale?

Solutions

Solution Image 1

Redesigned action nodes to include aggregate run data and object creation (e.g. conversations) data. Improved the run history to be filterable by each specific action.

Solution Image 2

Updated the ouput of individual runs to be consice and account for every possible edge case so users are not left in the dark about what happened and why.