UiPath — Engineering Performance
32 engineers now deliver what 36 would have in Apr 2025.
Performance snapshot
Today's rolling 90-day reading for UiPath, compared with the start of the series. Pick a window to move that comparison point.
Avg. perf / dev / mo
−64.1%
2.90 → 1.04 ETV
Active engineers
+3100.0%
1.0 → 32.0
Features
−35.0pp
64.5% → 29.5%
vs. 500 OSS index
0.33x
3.2x → 0.33x · −67% below
Engineering capacity
Effective engineers behind UiPath, against its pre-AI baseline. Each subject has its own: UiPath's is 0.92 ETV / dev / mo, its first reading in April 2025. Per-engineer ETV divided by that gives a capacity multiple, and that multiple applied to the engineers active in the trailing 90 days turns it into engineer-equivalents. The line is the real headcount, so the gap between line and area is what the leverage is worth. Because each baseline is its own, every subject opens at 1.0x on its first day: multiples measure improvement and are not comparable between subjects.
UiPath vs. 500 OSS Performance Index
Per-engineer ETV for UiPath against the pooled 500 OSS Performance Index. Both lines are 90-day rolling averages scaled to a 30-day month, so they share one axis and can be read against each other at any point. Pick a window to zoom the chart to it. Latest reading: UiPath is 67% below the index (1.04 vs 3.11 ETV/dev/mo). At the start of the tracked period the gap was 216% above.
Behind the numbers
Written summary of the work completed each month.
During the 2026-08 period, the team recorded steady delivery with 214 commits, focused heavily on design system standardizations in apollo-wind and apollo-react alongside SDK maintenance. Key efforts included standardizing form validation semantics, accessibility (ARIA) compliance, and Storybook layout patterns. Total output reached 35 across tracked categories, remaining in line with the recent run rate compared to the 5-month average.
Highlights
- Unified field controls, error states, and ARIA attributes across apollo-wind and apollo-react components in e48d6d9b (David) and ba2a0be7 (David)
- Integrated litellm routing via Azure GPT-5.6-luna into the evaluation framework in 636db813 (Akshaya)
- Implemented DAP workflow layouts and variable picker integrations across canvas Storybook templates in 3fae0cf0 (David) and 6f0f7bed (David)
Observations
- A significant portion of commits focused on UI accessibility and Storybook alignment, such as fixing required indicator labels and ARIA properties in aaf2daf3 (David), d29216a2 (David), and 53dbe864 (David)
- Repeated preview documentation synchronizations occurred for Maestro SDK skills across multiple commits, including fad54955 (uipreliga), 770ed0d6 (uipreliga), 47ebbe24 (uipreliga), and 87a12d68 (uipreliga)
- Total commit volume of 214 was 7% below the 5-month average of 230 commits, with total output (35) holding steady compared to the 5-month average (34)
Based on 214 commits19.2 ETVUpdated Sep 8, 2026, 4:01 PM
Repositories
Where each repository stands: average performance per engineer per month over the last 90 days, with the rolling 90-day curve behind it. The range picks the window (past 90d): it sets how much of the curve you see, the Δ across it, and the span the work mix is measured over. Ranked highest first.
apollo-ui
Avg performance
1.27 ETV
per engineer per month
Avg. dev performance / month (90-day MA)
+27.7%
Work mix
Features
41%
Maint
12%
Tests
28%
Docs
7%
Fixes
12%
uipath-integrations-python
Avg performance
1.26 ETV
per engineer per month
Avg. dev performance / month (90-day MA)
+2026.4%
Work mix
Features
33%
Maint
1%
Tests
61%
Docs
5%
Fixes
0%
uipath-langchain-python
Avg performance
0.48 ETV
per engineer per month
Avg. dev performance / month (90-day MA)
+89.7%
Work mix
Features
18%
Maint
4%
Tests
57%
Docs
5%
Fixes
17%
skills
Avg performance
0.41 ETV
per engineer per month
Avg. dev performance / month (90-day MA)
-53.3%
Work mix
Features
15%
Maint
9%
Tests
33%
Docs
34%
Fixes
10%
uipath-python
Avg performance
0.33 ETV
per engineer per month
Avg. dev performance / month (90-day MA)
-15.0%
Work mix
Features
20%
Maint
4%
Tests
55%
Docs
5%
Fixes
17%
Performance Composition
Each month's output split by type of work: Features (new value), Maintenance (sustaining systems), Tests, Docs, and Fixes (rework). The yellow line is output per engineer, so when it rises each engineer is delivering more, whatever the team size did. Unit: Engineering Throughput Value (ETV).
Cost per Performance Unit
+178%
If performance per engineer dropped 64%, each unit of engineering performance now costs approximately 178% more than at the baseline 90-day window (ending 2025-04-01). Treat this as a direction, not a price: the exact figure depends on fully-loaded engineer cost, but which way it moved is not in doubt.
Effective Capacity Lost
−21 engineers
At today's productivity, the current 32-person team delivers the performance equivalent of 11 engineers at the baseline 90-day rolling window (ending 2025-04-01). Per-engineer productivity has dipped below the baseline, leaving the team roughly 21 engineers behind that pace.
CapEx vs OpEx
Each month's work split two ways. CapEx (capitalizable investment) is the work that builds the asset: Features, plus the Tests that prove it works and the Docs that explain it. OpEx (operating expense) is keeping it running: Maintenance and Fixes. The yellow line is the CapEx share, so a rising line means more of the month went into building new rather than sustaining what exists. Unit: Engineering Throughput Value (ETV).
Hours per Repository
Trailing 90-day window (64 working days). Org-level capacity is allocated to each repo by its share of org performance, then split CapEx / OpEx by that repo's own Features + Tests + Docs vs Maintenance + Fixes mix.
| uipath-integrations-python | 99.2% | 0.8% |
| skills | 80.6% | 19.4% |
| uipath-langchain-python | 79.6% | 20.4% |
| uipath-python | 79.3% | 20.7% |
| apollo-ui | 76.5% | 23.5% |
| Total | 81.4% | 18.6% |
Feature Contribution
Who shipped each month's new feature work, as a share of that month's total. Bands of similar width mean new value is coming from across the team; one band that stays wide means most of it rests on the same person. Named engineers shipped the most Features over the period. Everyone else is grouped as Others.
Quarterly Summary
Engineers and the Features / Maintenance / Tests / Docs / Fixes mix for each quarter. Cost / Perf Unit is what one unit of performance costs against Q2'25. Eff. Capacity Added is measured against this org's own pre-AI baseline instead, its first reading in the index, so it agrees with the capacity tile and chart above.
| Quarter | |||||
|---|---|---|---|---|---|
| Q2'25 | 7 | 0% | +3 engineers | 41% Features | — |
| Q3'25 | 15 | +33% | 0 engineers | 57% Features | +61% |
| Q4'25 | 27 | −3% | +11 engineers | 41% Features | +145% |
| Q1'26 | 35 | +18% | +6 engineers | 33% Features | +7% |
| Q2'26 | 34 | +17% | +6 engineers | 32% Features | −2% |