Engineering Flow
AI-first executive view · Custom scope · last 30d
AI Bottom Line
Throughput declined (-54.8%) and AI participation decreased (-11.3 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 On Hold (currently 17.2d) — this is the team-wide bottleneck.
AI in teams · 1 team
52 completed · 1.9% AI-touched · 0 active agents
Bottom line
EVO declined (-55.2%) in throughput. AI cohort too small for cycle comparison (n=0/52); no specific AI bottleneck stands out.
Issues done
52
-55.2% vs prev
AI-owned share
0%
-11.2 pp vs prev
AI-touched
1 (2%)
Lead Time (active)
4.6d
prev 13.7d
Cycle Time (active)
2.1d
prev 6.8d
TTR p50
1.3d
prev 1.7d
PR Review p50
—
WIP active
44
WIP blocked
5
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 0
none in window
AI Period: compare · intro 2026-04-02
Active bottlenecks · top 5
Top teams · by throughput
| Key | Team | Throughput | Lead Time (active) | Cycle Time (active) | Active WIP | Blocked WIP | AI % |
|---|---|---|---|---|---|---|---|
| EVO | Platforms Evolution | 52 | 4.6d | 2.1d | 44 | 5 | 0% |