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Microsoft — Engineering Performance

MicrosoftEngineering capacity
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+390Eff. engineering capacity added

136 engineers now deliver what 526 would have in Apr 2025.

+184 vs the previous 90 days

Effective engineersReal engineers
Apr 2025Dec 2025Sep 2026
Where the work wentBiggest shift: Tests up 9 points
35%
Features
12%
Maintenance
32%
Tests
3%
Docs
18%
Fixes

Performance snapshot

Today's rolling 90-day reading for Microsoft, compared with the start of the series. Pick a window to move that comparison point.

Avg. perf / dev / mo

+287.1%

1.35 → 5.22 ETV

Active engineers

−11.7%

154.0 → 136.0

Features

+2.3pp

33.0% → 35.3%

vs. 500 OSS index

1.6x

1.5x → 1.6x · +62% above

Engineering capacity

Effective engineers behind Microsoft, against its pre-AI baseline. Each subject has its own: Microsoft's is 1.35 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.

Effective engineers
526engineer-equivalents
+390 engineers above real headcount
Real engineers
136engineers
active in the trailing 90 days
Capacity vs pre-AI
3.9x
per engineer, vs 1.35 pre-AI

Microsoft vs. 500 OSS Performance Index

Per-engineer ETV for Microsoft 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: Microsoft is 62% above the index (5.22 vs 3.22 ETV/dev/mo). At the start of the tracked period the gap was 47% above.

Microsoft
5.22ETV / dev / mo
+2.12 (+68.4%) past 90d
500 OSS Performance Index
3.22ETV / dev / mo
+0.99 (+44.4%) past 90d

Behind the numbers

Aug

Written summary of the work completed each month.

During 2026-08, the team delivered major improvements across the Agent Host subsystem, Copilot session management, and remote workbench integrations across 1,810 commits. Total output reached 814, surging +60% compared to the 5-month average (510) and exceeding recent months. Delivery was highlighted by a significant increase in testing activity (295 vs 129 5-month average) alongside protocol upgrades and cross-platform UI enhancements.

Highlights

  • Upgraded the Agent Host subsystem to Agent Host Protocol (AHP) version 0.9.0 and normalized automation state schemas in 40c9634e (Connor)
  • Implemented dynamic resource label home registration to format session paths cleanly in editor breadcrumbs via f291f3fd (Sandeep) and 718038e1 (Sandeep)
  • Added support for rich content rendering including Adaptive Cards and Markdown in CmdPal details views via e1fb1333 (Mike)
  • Enhanced Model Context Protocol (MCP) app routing by routing subrequests directly through owning Agent Host connections in 006c4ca9 (Dmitriy)
  • Introduced active unarchived session counts and accessible row labels for remote Agent Hosts in c3f2a06d (Dmitriy)
  • Migrated devtools-view test suites from Jest to Mocha and JSDOM, eliminating a component memory leak in 433c666b (Joshua)

Observations

  • Tests score surged +128% compared to the 5-month average (295 vs 129 average), driven by test suite migrations and broad fixture additions across agent subsystems
  • Fixes score increased +74% relative to the 5-month average (145 vs 83 average), addressing memory leaks in pseudoterminals 4d3de9df (Simon) and git branch protection feaa8c99 (Simon), alongside path handling bugs 051440b1 (Ulugbek)
  • Docs score saw a candidate-material increase of +101% against the 5-month average (28 vs 14 average), supported by architecture specifications like session automations in 1dbbce1d (Ulugbek)
  • The Agent Host and Copilot session components experienced repeated modifications to error handling and permissions, including disabling retryable error markers in e05bae3b (roblourens) and enforcing shell-script safety classifiers in 07864e41 (joshspicer)
  • Cross-platform normalization required repeated targeted fixes across Windows path handling in 051440b1 (Ulugbek), WSL chat link resolution in 735c7376 (Dileep), and CLI output formatting fallbacks in 05b0e8ce (Dmitriy)

Based on 1,810 commits491.1 ETVUpdated Sep 8, 2026, 8:17 AM

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.

vscode

Avg performance

8.82 ETV

per engineer per month

Avg. dev performance / month (90-day MA)

+97.9%

Work mix

Features

36%

Maint

12%

Tests

33%

Docs

2%

Fixes

17%

62 devs1650 ETV+301% since Q2 2025Repository report

Agents-for-net

Avg performance

6.77 ETV

per engineer per month

Avg. dev performance / month (90-day MA)

-1.7%

Work mix

Features

31%

Maint

14%

Tests

47%

Docs

5%

Fixes

4%

3 devs61 ETV+212% since Q2 2025Repository report

TypeScript

Avg performance

4.49 ETV

per engineer per month

Avg. dev performance / month (90-day MA)

+3.7%

Work mix

Features

42%

Maint

11%

Tests

30%

Docs

2%

Fixes

15%

5 devs69 ETV−28% since Q2 2025Repository report

playwright

Avg performance

4.20 ETV

per engineer per month

Avg. dev performance / month (90-day MA)

-20.7%

Work mix

Features

31%

Maint

19%

Tests

19%

Docs

5%

Fixes

26%

7 devs88 ETV+79% since Q2 2025Repository report

PowerToys

Avg performance

3.58 ETV

per engineer per month

Avg. dev performance / month (90-day MA)

+226.0%

Work mix

Features

33%

Maint

9%

Tests

28%

Docs

3%

Fixes

27%

9 devs97 ETV+92% since Q2 2025Repository report

DeepSpeed

Avg performance

2.08 ETV

per engineer per month

Avg. dev performance / month (90-day MA)

+268.0%

Work mix

Features

31%

Maint

3%

Tests

40%

Docs

5%

Fixes

21%

5 devs32 ETV+115% since Q2 2025Repository report

fluentui

Avg performance

1.52 ETV

per engineer per month

Avg. dev performance / month (90-day MA)

-17.7%

Work mix

Features

46%

Maint

19%

Tests

17%

Docs

7%

Fixes

11%

11 devs52 ETV+61% since Q2 2025Repository report

FluidFramework

Avg performance

0.95 ETV

per engineer per month

Avg. dev performance / month (90-day MA)

+14.1%

Work mix

Features

20%

Maint

16%

Tests

30%

Docs

23%

Fixes

10%

27 devs77 ETV−24% since Q2 2025Repository report

terminal

Avg performance

0.88 ETV

per engineer per month

Avg. dev performance / month (90-day MA)

+45.0%

Work mix

Features

47%

Maint

26%

Tests

7%

Docs

1%

Fixes

19%

4 devs11 ETV−2% since Q2 2025Repository report

semantic-kernel

Avg performance

0.44 ETV

per engineer per month

Avg. dev performance / month (90-day MA)

-25.6%

Work mix

Features

18%

Maint

9%

Tests

45%

Docs

3%

Fixes

25%

5 devs7 ETV−83% since Q2 2025Repository report

markitdown

Avg performance

0.10 ETV

per engineer per month

Avg. dev performance / month (90-day MA)

+383.3%

Work mix

Features

0%

Maint

7%

Tests

0%

Docs

17%

Fixes

76%

1 dev0 ETV−100% since Q2 2025Repository report

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

−74%

If performance per engineer more than doubled, each unit of engineering performance now costs approximately 74% 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

+390 engineers

At today's productivity, the current 136-person team delivers the performance equivalent of 526 engineers at the baseline 90-day rolling window (ending 2025-04-01). That's roughly 390 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.

Agents-for-net82.8%17.2%
DeepSpeed75.6%24.4%
TypeScript73.6%26.4%
FluidFramework73.4%26.6%
vscode70.7%29.3%
fluentui69.4%30.6%
semantic-kernel66.4%33.6%
PowerToys64.3%35.7%
playwright55.2%44.8%
terminal54.6%45.4%
markitdown17.2%82.8%
Total70.2%29.8%

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
Q2'251620%+10 engineers
32% Features
Q3'25170+12%−9 engineers
36% Features
−7%
Q4'25166−14%+39 engineers
27% Features
+27%
Q1'26173−46%+169 engineers
38% Features
+67%
Q2'26157−55%+216 engineers
40% Features
+9%