Jira Metrics

Engineering Flow

AI-first executive view · Custom scope · last 30d

AI Bottom Line

AI-narratedcached· 2026-07-19 15:27 UTC

Throughput increased to 42 issues done, but flow remains constrained by long active wait states—especially Waiting for Client—and there were no successful deployment runs in the period.

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
42 23.5%
Last 8w
AI participation
2.4% 72.7%
Last 8w
Lead Time (active)
3.8d 52.6%
no trend
Cycle Time (active)
2.9d 2.5%
Last 8w

AI insight

  • Where AI helps:The single AI-owned completion was faster than the overall median on lead time, cycle time, and time to ready, but the sample is one item so this is directional only.
  • Where AI hurts:AI-touched work ran slower than the overall median on lead time and cycle time, indicating AI involvement is concentrated in more delayed work rather than showing a clear flow benefit here.
  • Next focus:Reduce external dependency wait and clean up long-stuck in-progress work before adding more demand.

AI in teams · 1 team

ADSAdvertisement
2.4% AI

42 completed · 38.1% AI-touched · 2 active agents

Bottom line

ADS improved (23.5%) in throughput. AI-vs-Human cycle comparison is directional only (sample too small) (n=1/41); the main AI bottleneck is Ready For Review.

Issues done

42

+23.5% vs prev

AI-owned share

2%

-6.4 pp vs prev

AI-touched

16 (38%)

Lead Time (active)

3.8d

prev 8.1d

Cycle Time (active)

2.9d

prev 3d

TTR p50

0.1h

prev 0.2h

PR Review p50

WIP active

30

WIP blocked

14

AI insight

Where AI helps

No statistically stable AI advantage detected yet. Directional-only signals below numerically favor AI but sample size is below threshold.

Where AI hurts

No AI-owned metric is currently slower than the human cohort.

Directional only (sample too small)

  • · Cycle Time (active): AI 1.1d vs Human 3.8d (n=1/41, below 20)
  • · Lead Time (active): AI 1.1d vs Human 3.9d (n=1/41, below 20)
  • · Time to Ready p50: AI 0h vs Human 0.1h (n=1/41, below 20)

Top AI bottleneck

Ready For Review
1.1d

Active agents · top 2

Nikolaos
96
Oliver
41

AI Period: compare · intro 2025-08-01

Active bottlenecks · top 5

Workflow stageRelative wait timeMedian time
Waiting for Client
84.5dp50
Ready For Canary
2.1dp50
On Hold
16.7hp50
In Progress
6.3hp50
Ready For Review
0.3hp50

Top teams · by throughput

KeyTeamThroughputLead Time (active)Cycle Time (active)Active WIPBlocked WIPAI %
ADSAdvertisement423.8d2.9d30142%

Data quality amber

Sync freshness1/1 synced
Latest sync1/1 OK
Config coverageall configured
PR linkagelow: ADS

Report version: engineering-flow.v8 · metric definitions: 2026-05-24.audit18.v1

Period: 2026-06-202026-07-20 · scope: Custom scope (1 project)

Detail view (/overview) → — full per-metric tables, AI Period comparison, longest-stuck list.

19 tickets excluded — managed centrally.