Vercel — Engineering Performance
50 engineers now deliver what 163 would have in Q1 2025.
Performance snapshot
Today's rolling 90-day reading for Vercel, compared with the start of the series. Pick a window to move that comparison point.
Avg. perf / dev / mo
+226.5%
1.54 → 5.04 ETV
Active engineers
+4.2%
48.0 → 50.0
Features
+4.6pp
25.7% → 30.3%
vs. 500 OSS index
1.3x
1.7x → 1.3x · +31% above
Engineering capacity
Effective engineers behind Vercel, against its pre-AI baseline. Each subject has its own: Vercel's is 1.54 ETV / dev / mo, its first reading in Q1 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.
Vercel vs. 500 OSS Performance Index
Per-engineer ETV for Vercel 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: Vercel is 31% above the index (5.04 vs 3.85 ETV/dev/mo). At the start of the tracked period the gap was 68% above.
Behind the numbers
Written summary of the work completed each month.
In August 2026, the team recorded 422 commits with 51 Features, 43 Tests, 25 Fixes, 19 Maintenance, and 18 Docs, reflecting steady delivery in line with the recent run rate. Key accomplishments included enabling export-name mangling in Turbopack, expanding AI SDK provider capabilities across Bedrock and Azure, and refining Next.js cache and prerendering mechanics. Under the provisional evaluation threshold, Docs score rose 89% above the 5-month average while Maintenance score decreased by 35% compared to the 5-month average.
Highlights
- Added export-name mangling to Turbopack (a84bc8de (Tobias)) and enabled it by default in canary production builds (6f44fd34 (Tobias)) to reduce bundle sizes.
- Optimized turbo-persistence key lookups in SST blocks without hashes (33a5d542 (Luke)), improving lookup performance by up to 30%.
- Enhanced the AI SDK Core with strict tool choice validation and error handling in 8b6b756a (Aayush), and exposed parsed structured output to
onEnd/onFinishstream callbacks in 6669d691 (Lars). - Introduced granular cache keys incorporating runtime hashes and manifests for
use-cachein Next.js via e3790aa9 (Niklas) and exposeddurableUseCacheEntriesconfiguration in 3d85af96 (Niklas). - Expanded Turborepo lockfile package metadata support for single-package repositories across major package managers in 2c84c66d (Anthony) and added root Cargo workspace support in e732034b (Anthony).
Observations
- Docs score saw a notable increase to 18 vs the 9-point 5-month average (+89%), driven by extensive documentation updates for AI SDK providers and Turborepo features.
- Maintenance score dropped to 19 compared to the 29-point 5-month average (-35%), while overall output (157) remained steady relative to the 5-month average of 155 (+1%).
- CI test flakiness required repeated intervention in root sync IO tests, including skipping in 0a2bd1d5 (Janka) and reverting an attempt to re-enable them in 357e514c (Janka).
- Refactoring in Next.js internal architecture included isolating the image optimization transform pipeline into modular utilities (1cb20a1d (Steven), d4c838a7 (Steven)) and migrating Turborepo CLI parsing to
usage-rs(712e0e4a (Anthony)).
Based on 422 commits95.2 ETVUpdated Sep 30, 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.
turborepo
Avg performance
22.17 ETV
per engineer per month
Avg. dev performance / month (90-day MA)
+303.0%
Work mix
Features
35%
Maint
28%
Tests
16%
Docs
3%
Fixes
18%
ai
Avg performance
5.41 ETV
per engineer per month
Avg. dev performance / month (90-day MA)
+55.3%
Work mix
Features
33%
Maint
7%
Tests
38%
Docs
8%
Fixes
15%
workflow
Avg performance
4.76 ETV
per engineer per month
Avg. dev performance / month (90-day MA)
+36.1%
Work mix
Features
23%
Maint
6%
Tests
39%
Docs
17%
Fixes
14%
next.js
Avg performance
4.18 ETV
per engineer per month
Avg. dev performance / month (90-day MA)
+78.5%
Work mix
Features
28%
Maint
19%
Tests
31%
Docs
5%
Fixes
18%
sandbox
Avg performance
0.61 ETV
per engineer per month
Avg. dev performance / month (90-day MA)
+26.1%
Work mix
Features
50%
Maint
2%
Tests
35%
Docs
7%
Fixes
6%
vercel
Avg performance
0.37 ETV
per engineer per month
Avg. dev performance / month (90-day MA)
-67.0%
Work mix
Features
36%
Maint
10%
Tests
34%
Docs
7%
Fixes
14%
swr
Avg performance
0.26 ETV
per engineer per month
Avg. dev performance / month (90-day MA)
+228.4%
Work mix
Features
40%
Maint
6%
Tests
51%
Docs
3%
Fixes
0%
sdk
Avg performance
0.01 ETV
per engineer per month
Avg. dev performance / month (90-day MA)
-98.3%
Work mix
Features
0%
Maint
63%
Tests
38%
Docs
0%
Fixes
0%
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
−69%
If performance per engineer more than doubled, each unit of engineering performance now costs approximately 69% less 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 Added
+113 engineers
At today's productivity, the current 50-person team delivers the performance equivalent of 163 engineers at the baseline 90-day rolling window (ending 2025-04-01). That's roughly 113 engineers worth of capacity added through productivity gains, not hiring.
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.
- CapEx %
- 93.7%
- OpEx %
- 6.3%
- CapEx %
- 91.6%
- OpEx %
- 8.4%
- CapEx %
- 80.0%
- OpEx %
- 20.0%
- CapEx %
- 78.3%
- OpEx %
- 21.7%
- CapEx %
- 77.6%
- OpEx %
- 22.4%
- CapEx %
- 63.6%
- OpEx %
- 36.4%
- CapEx %
- 53.7%
- OpEx %
- 46.3%
- CapEx %
- 37.5%
- OpEx %
- 62.5%
- CapEx %
- 68.1%
- OpEx %
- 31.9%
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. Engineers vs headcount 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.
- Engineers
- 54
- Cost / Perf Unit
- 0%
- Engineers vs headcount
- −9 engineers
- Work mix
- 22% Features
- Engineers
- 61
- Cost / Perf Unit
- −4%
- Engineers vs headcount
- −8 engineers
- Work mix
- 25% Features
- Engineers
- 67
- Cost / Perf Unit
- −10%
- Engineers vs headcount
- −4 engineers
- Work mix
- 32% Features
- Engineers
- 69
- Cost / Perf Unit
- −54%
- Engineers vs headcount
- +56 engineers
- Work mix
- 34% Features
- Engineers
- 63
- Cost / Perf Unit
- −60%
- Engineers vs headcount
- +69 engineers
- Work mix
- 28% Features