The state of engineering, 2026

AI made your team faster.
The code wait got worse.

Copilots ship code 2× quicker — and pile it up at review, QA and release. Without telemetry, AI doesn't multiply output. It multiplies the mess. We measure where your engineering hours actually go, and put a € number on every bottleneck.

€5,160
lost per engineer / year
31%
hours spent waiting
14 days
to first measurable signal
Tickets in flight Stuck > 24h AI-authored Shipped
build flow · last 14d
AI assist
Plan
12
avg 2h
Code
28
avg 6h
bottleneck
Review
41
avg 18h ▲
QA
19
avg 7h
Ship
8
avg 1h
Bottleneck · Review +18h / ticket€ leak €2,840 / week
02 · The double edge

AI doesn't help.
Visibility into AI does.

Same tools. Same engineers. The difference is whether anyone can see the work AI is generating — and what happens to it next.

● AI without measurement

Code volume doubled. Throughput didn't.

Copilots generated 53% more PRs last quarter. Reviewers can't keep up. Tests get skipped. Tech debt compounds quietly in production.

PRs opened
+53%
Review queue
+47%
Rework rate
+22%
Shipped value
+4%
Incidents
+19%
● AI with Agile Analytics

Same AI. 31% more value shipped.

We label every AI-authored ticket in real time, score review depth, and surface flow drift before it costs you a sprint. AI becomes a multiplier — not a generator of work-in-progress.

PRs opened
+22%
Review queue
−38%
Rework rate
−41%
Shipped value
+31%
Incidents
−27%
03 · How we see it

One loop. Three lenses.
One real metric: shipped value.

Engineering productivity isn't a single number — it's a flow. AgileEx, DevEx and OpsEx are the three lenses that make the whole loop measurable. Drag your sprint through it and watch where the hours go.

All lensesAgileExDevExOpsEx
live · sprint 47
PlanCodeBuildTestReleaseReviewRefineBacklogDeployRunObserveAlertResolvePostmortemSLOLearnENGINEERING84%HOUR EFFECTIVITYtarget ≥ 80%bottleneck
14d → 7d
Loop time, this quarter
+31%
Throughput, same headcount
€512K
Reclaimed (100-eng team)
04 · The bill nobody added up

Hours leak. Hours cost money.

Drag the slider to plug in your team size and burdened cost. The € figure updates live. This is the leak we surface — to the minute.

BottleneckHrs / eng / weekShare of lossDistribution€ / year
Waiting on review3.1h28%
€144K
Slow CI / build feedback2.4h22%
€112K
Unplanned interruptions2.0h18%
€94K
Reworking AI output1.8h17%
€86K
Handover gaps1.6h15%
€76K
Total leak10.9h / week≈ 27% of hoursat a 100-engineer team · 240 workdays€512K
100
95
Annual total · €512K
05 · The lever

Pull a lever. See your sprint heal.

Adjust the dial. This is the median improvement our customers see in their first 90 days — across review wait, lead time, rework, and SLO compliance.

90-day after Agile Analytics:
measurable change across the loop.

Live preview · drag dial →
Lead time10.6 d
Review wait11.0 h
Rework rate15.5 %
SLO compliance85.0 %
Hour effectivity72.5 %
Days in
45d
since onboarding
Day 0306090
Reclaimed
€258K
06 · Engineering productivity

Engineering productivity
has an SLA now.

Every team sets targets for hour-effectivity, lead time and review SLO. We track every breach — and tell you which loop it came from.

Hour effectivityon target
84%
target ≥ 80% · breach budget 4d remaining
Lead time p50at risk
7.4d
target ≤ 5d · breached 2× this sprint
Review SLO < 24hbreached
62%
target ≥ 95% · burned 7d in last 30d

Stop guessing.
Start measuring.

14-day Quickscan plugs into your Jira + GitHub + CI. Your first € leak report lands in 7 days, no slides.