Anatomy of a ticket

Range:

Validation & drill-down view. Use this page to understand exactly how each flow metric is computed for one project, and where the AI cohort differs from the human cohort. Headline numbers on /flow and /overview roll up the same formulas across all projects. Hover any lane label for the formula and a sample-size note.

Anatomy of a ticket — ADS

Window: 30d · All 42 · AI 1 · Human 41

Jira Flow Lead Time (raw / wall-clock)

92hn=42AI27hn=1 · directionalH93hn=41

Lead Time (active, ÷ pauses)

92hn=42AI27hn=1 · directionalH93hn=41

Time to Ready

0.1hn=42AI0.0hn=1 · directionalH0.1hn=41

Cycle Time (raw / wall-clock)

69hn=42AI27hn=1 · directionalH91hn=41

Lead Time for Changes

Not enough data in this window

Cycle Time (active, ÷ pauses)

69hn=42AI27hn=1 · directionalH91hn=41

Time to First PR

2.1hn=6AIno dataH2.1hn=6 · directional

PR Review Duration

27hn=8AIno dataH27hn=8 · directional

Created

Ready

In Progress

In Review

Done

Deployed

AI vs Human comparison

Bars proportional within each row (max = 100%). Δ% lower-is-better — green = AI faster.

Jira Flow Lead Time (raw / wall-clock)

Created → Done · wall-clock hours including weekends and pauses

directionalView tickets (1/41) →

27h n=1 · dir.

Human

93h n=41

Lead Time (active, ÷ pauses)

Created → Done · business hours minus configured pause statuses

directionalView tickets (1/41) →

27h n=1 · dir.

Human

93h n=41

Time to Ready

Created → first transition into a ready status (Selected / Approved / Ready)

directionalView tickets (1/41) →

0.0h n=1 · dir.

Human

0.1h n=41

Cycle Time (raw / wall-clock)

First cycle-start status → Done · wall-clock hours

directionalView tickets (1/41) →

27h n=1 · dir.

Human

91h n=41

Cycle Time (active, ÷ pauses)

First cycle-start status → Done · business hours minus pauses

directionalView tickets (1/41) →

27h n=1 · dir.

Human

91h n=41

Not measurable (one cohort has zero samples):

·Time to First PR — no AI cohort samples (no completed tickets with an AI assignee, or no PRs by AI authors)
·PR Review Duration — no AI cohort samples (no completed tickets with an AI assignee, or no PRs by AI authors)
·Lead Time for Changes — no tickets / PRs measurable in this window

Cohort breakdown

⚠ marker when AI or Human cohort sample size is below 10.

Metric	All p50	n	AI p50	n	Human p50	n	Δ (AI vs Human)
Jira Flow Lead Time (raw / wall-clock)	92h	42	27h	1 ⚠	93h	41	—
Lead Time (active, ÷ pauses)	92h	42	27h	1 ⚠	93h	41	—
Time to Ready	0.1h	42	0.0h	1 ⚠	0.1h	41	—
Cycle Time (raw / wall-clock)	69h	42	27h	1 ⚠	91h	41	—
Cycle Time (active, ÷ pauses)	69h	42	27h	1 ⚠	91h	41	—
Time to First PR	2.1h	6	—	0 ⚠	2.1h	6 ⚠	—
PR Review Duration	27h	8	—	0 ⚠	27h	8 ⚠	—
Lead Time for Changes	—	0	—	0 ⚠	—	0 ⚠	—

All = every measurable ticket / PR in the window. AI = agent-owned cohort (ticket assignee or PR author is an active agent at completion). H = human cohort (everyone else, including unassigned). Δ compares AI vs Human p50 — negative = AI faster.

Side metrics

Throughput / week

9.8

AI 0.2 · H 9.6

WIP — Active now

Blocked 14

Bug rate / week

0.7

AI participation

AI 1 / 42

Top bottleneck

In Deployment

median 94h

Deploys / week

0.0

ADO-style

Change failure rate

—

no ADO mapping

PR acceptance

87%

AI — · H 87%

🧠 AI deep analysis

Generate an LLM-driven explanation of WHY the AI cohort is faster / slower on each lane. Cites specific tickets from the evidence pack, suggests next steps.

Active variants use business hours minus pause statuses (same formula as the per-project Cycle / Lead pages). Raw variants are pure wall-clock. AI cohort = ticket assignee (or PR author) is an active agent at completion time. Sample-size suppression marks values directional only when AI or Human cohort drops below 10 — the value is still shown for context but trust it less.

19 tickets excluded — managed centrally.