Engineering Flow
AI-first executive view · Custom scope · last 30d
AI Bottom Line
Throughput declined (-80.0%) and AI participation steady. 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 In Progress (currently 3.5d) — this is the team-wide bottleneck.
AI in teams · 1 team
2 completed · 50.0% AI-touched · 1 active agent
Bottom line
IMC declined (-66.7%) in throughput. AI cohort too small for cycle comparison (n=0/0); no specific AI bottleneck stands out.
Issues done
2
-66.7% vs prev
AI-owned share
0%
+0.0 pp vs prev
AI-touched
1 (50%)
Lead Time (active)
29.6d
prev 20.2d
Cycle Time (active)
—
prev 0h
TTR p50
6.4h
prev 4.8d
PR Review p50
—
WIP active
2
WIP blocked
0
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 1
Active bottlenecks · top 5
Top teams · by throughput
| Key | Team | Throughput | Lead Time (active) | Cycle Time (active) | Active WIP | Blocked WIP | AI % |
|---|---|---|---|---|---|---|---|
| IMC | [Engineering]: Incident Management | 2 | 29.6d | — | 2 | 0 | 0% |