The operating judgment behind the diagnostic.
This diagnostic is derived from an intake-to-decision operating system. The summary below shows where AI can assist, where human judgment must hold, and how each diagnostic dimension maps back to a workflow stage.
The design is organized around decision quality, capacity allocation, and delivery predictability as AI enters the workflow.
Prepares, detects, routes, summarizes, and drafts option sets.
Approve, fund, defer, narrow, accept risk, override, and commit capacity.
Any agentic AI placement must be bounded in scope, observable in effect, and reversible if wrong. Placements that fail any of the three do not get made.
AI is deliberately absent at the executive decision moment. The decision right stays with an accountable person, and the rationale is recorded.
Execution data returns to planning. Actual effort, cycle time, and handoff quality are compared against the original estimate. Lessons from delivery update the intake and planning system. Someone owns the decision to sunset or stop work that is no longer worth continuing.
| Stage | Dimension |
|---|---|
| 01 | Demand Intake Discipline |
| 02 | Problem Framing and Triage |
| 03 | Capacity and Estimation Realism |
| 04 | Cross-Functional Risk and Dependency Visibility |
| 05 | Option Formulation and Tradeoff Clarity |
| 06 | Decision Packet and Governance |
| 07 | Decision Rights and the Executive Moment |
| 08 | Execution Feedback and Learning Cadence |