AI found a risk: investigate Jira dependencies before deciding

Follow an AI finding back to Jira evidence, then explore the hierarchy and dependencies before deciding where to intervene.

In this video

  1. 0:00 Load the launch-decision board
  2. 0:11 See all hierarchy levels in Global view
  3. 0:17 Inspect insights and AI evidence
  4. 0:35 Highlight evidence and reveal hierarchy corridors
  5. 0:43 Organise by release timeline and issue type
  6. 1:10 Follow the selected evidence through its parent hierarchy
  7. 1:28 Regroup the same evidence by project
  8. 1:49 Human decisions need context

What the demonstration shows

The demonstration loads the Aurora launch-decision filter and switches to Global view. Board Insights opens an AI analysis grounded in the loaded work. The words “critical-path candidate” are highlighted as a finding to investigate, not as a confirmed scheduling calculation.

The evidence buttons highlight the cited items and reveal their hierarchy corridors. The board is organised using a Fix versions timeline and Issue Type rows. Direct and rolled-up dependencies remain part of the connected context.

The selected evidence item is IDP-7, “Validate signed token-claims compatibility”. The camera follows its hierarchy through IDP-3, “Publish signed token-claims contract v3”, to IDP-1, “Harden OAuth token and session services”.

The same board is regrouped by Project while retaining the evidence and hierarchy context. The human decision is where to investigate or intervene next, after checking the linked work. This demonstration does not establish a delivery forecast or prove that an item lacks an assignee or priority.

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