Engineering Flow
AI-first executive view · Custom scope · last 30d
AI Bottom Line
Throughput improved (+36.8%) and AI participation decreased (-2.6 pp). Not enough samples for AI/Human comparison this period (n<20 across all metrics).
Headline KPIs · last 30d
AI insight
- Where AI helps:Not enough samples for AI/Human comparison this period (n<20 across all metrics)
- Next focus:Reduce wait time in Waiting for Client (currently 139.8d) — this is the team-wide bottleneck.
AI in teams · 1 team
52 completed · 13.5% AI-touched · 2 active agents
Bottom line
ADS improved (33.3%) in throughput. AI cohort too small for cycle comparison (n=0/52); no specific AI bottleneck stands out.
Issues done
52
+33.3% vs prev
AI-owned share
0%
-2.6 pp vs prev
AI-touched
7 (14%)
Lead Time (active)
4.7d
prev 6.5d
Cycle Time (active)
0h
prev 3.8d
TTR p50
3.9d
prev 0.1h
PR Review p50
—
WIP active
26
WIP blocked
17
AI insight
Where AI helps
No AI-owned metric is currently faster than the human cohort.
Where AI hurts
No AI-owned metric is currently slower than the human cohort.
AI cohort too small for direct comparison on this team.
Top AI bottleneck
no AI-owned cohort with stage data
Active agents · top 2
AI Period: compare · intro 2025-08-01
Active bottlenecks · top 5
Top teams · by throughput
| Key | Team | Throughput | Lead Time (active) | Cycle Time (active) | Active WIP | Blocked WIP | AI % |
|---|---|---|---|---|---|---|---|
| ADS | Advertisement | 52 | 4.7d | 0h | 26 | 17 | 0% |