Engineering Flow
AI-first executive view · Custom scope · last 30d
AI Bottom Line
AI-narratedcached· 2026-07-21 00:30 UTC
Throughput softened to 5 issues completed, while flow remains constrained by heavy active WIP and long time before work becomes ready; AI impact is not measurable in this window because no AI-attributed work appears in scope.
AI ROI: data insufficient for the last 30d. 1 project in scope, none with stable AI vs Human cohort (n≥10 both sides) on Lead Time.
Investigate per project →Headline KPIs · last 30d
Issues done
5▼ 37.5%
Last 8w
AI participation
0.0%—
Last 8w
Lead Time (active)
8.2d▼ 81.0%
no trend
Cycle Time (active)
2.1d▼ 88.5%
Last 8w
AI insight
- Where AI helps:No AI-owned work was completed, so there is no evidence of AI improving flow metrics in this window.
- Where AI hurts:AI is not contributing to throughput in scope; with 0% participation, it is not offsetting current flow delays.
- Next focus:Reduce in-flight work and explicitly triage the oldest In Progress items before starting new work.
AI in teams · 0 teams
No teams in scope have AI involvement in this window. As soon as an AI agent assignment, comment, transition, or reporter shows up, this section populates.
Active bottlenecks · top 5
Workflow stageRelative wait timeMedian time
In Progress
21.3dp50
Ready To Test
1.2dp50
In Testing
1.9hp50
Top teams · by throughput
| Key | Team | Throughput | Lead Time (active) | Cycle Time (active) | Active WIP | Blocked WIP | AI % |
|---|---|---|---|---|---|---|---|
| GAM | GameLab (Archived) | 6 | 8.2d | 2.1d | 58 | 0 | 0% |
Data quality⚠ amber
⚠ Sync freshness1/1 synced
✓ Latest sync1/1 OK
✓ Config coverageall configured
✓ PR linkageno PR data