Weeklynext Mon · Jul 6Preview ready
Leadership Brief
VP Eng, CTO
- 96 active AI-assisted engineers
- Agentic Sprint up 28 points
- 3 priority actions
Reports
Executive summaryOrganization · last 30 days
AI adoption
92%
9%
67% of engineers trained
Training lift
+27pts
avg behavior lift
Cost / issue
$135
8%
AI cost efficiency
Capacity returned
≈ $275–370k/ qtr
16% faster cycles + 24% fewer defects, as engineering time
Training → adoption
Trained teams drove adoption to 92% — cohorts that finished the Agentic Sprint rose +28 pts.
Cost
Cost per issue fell 8% while AI-assisted PRs rose 18% — spend is tracking delivery.
Outcomes
16% faster cycles and 24% fewer escaped defects ≈ $275–370k a quarter returned.
Report briefs4
Biweeklynext Jul 13Preview ready
Training Impact Report
Enablement
- 110 lesson starts
- 87 completions
- Review clinic needs follow-up
Monthlydue Aug 1Draft preview
Finance / Procurement
Finance
- $27,690 monthly spend
- PR and issue movement attached
- Premium-model review queued
Weeklynext Mon · Jul 6Draft preview
Manager Coaching
Team leads
- Aggregate coaching needs
- No public individual rankings
- Suggested team clinics
Governance & policyorg-wide · last 30 days
Actions gated
1,942
Redacted
128/128
Time to gate
42 ms
Incidents
0
Credentials redacted128
Write actions gated47
Scope violations blocked12
Data-egress blocks9
Every agent session runs behind org policy — actions gated before execution, credentials redacted before any model call. Posture travels with every export.