Building an AI Agent Performance Dashboard that Leaders Actually Use

#90: From outcome-first metrics to an executive-ready UI—how we built it, why it works, and how to ship your own.

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Table of contents

1. What we set out to build

2. The shortest possible build plan (6 steps)

3. The dashboard concept: what to show—and why

4. The data model you’ll need

5. Visual + interaction choices (and the brand touch)

6. How this maps to the book—and what matters for leadership

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1) What we set out to build (in 20-30 mins.)

An executive-friendly dashboard that proves agent value, not model activity. The north star is simple: elevate time saved, insight generated, and risk mitigated—the three enterprise outcomes that matter once agents are in real workflows. Token counts and latency still exist, but they’re backstage.

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2) The shortest possible build plan (6 steps)

Here’s the quick, end-to-end checklist of how we arrived at the dashboard mockup (including the design work up front) using ChatGPT (only):

Step 1 — Define success by outcomes.
Lock your top-line KPIs: time saved, insight events, and risk interventions. Keep “alignment” signals (trust, relevance, utility) for diagnostic depth.

Step 2 — Instrument the events.
Log task lifecycle, tool calls, memory reads/writes, escalations/overrides, and governance checks. These traces enable auditability and learning loops later.

Step 3 — Stand up a minimal warehouse schema.
Dimensions for agents/users/use cases; facts for tasks, task events, tool calls, memory events, feedback, governance audits, interventions, and attribution. (A starter SQL/LookML pack is linked below.)

Step 4 — Create a truthful demo.
Generate fake—but structurally realistic—series for each KPI so executives can see the story before production data lands.

Step 5 — Ship the executive row first.
Put Time saved, Insight score, and Risk interventions side-by-side as your landing view. Everything else drills down.

Step 6 — Add the operating ritual.
Wire exports to support Quarterly Agent Strategy Reviews (QASRs) so teams can revisit scope, behavior, metrics, governance, and opportunities with a fixed cadence.