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Anthropics — Engineering Performance

AnthropicsEngineering capacity
+46engineers above headcount

11 engineers now deliver what 57 would have in Q1 2025.

Effective engineersReal engineers
Apr 2025Dec 2025Sep 2026
Where the work wentBiggest shift: Docs down 15 points
Features29%Maintenance4%Tests39%Docs7%Fixes21%

Performance snapshot

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

Avg. perf / dev / mo

+4410.9%

0.05 → 2.08 ETV

Active engineers

+450.0%

2.0 → 11.0

Features

+3.9pp

25.2% → 29.1%

vs. 500 OSS index

0.54x

0.05x → 0.54x · −46% below

Engineering capacity

Effective engineers behind Anthropics, against its pre-AI baseline. Each subject has its own: Anthropics's is 0.40 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.

Effective engineers
57engineer-equivalents
+46 engineers above real headcount
Real engineers
11engineers
active in the trailing 90 days
Capacity vs pre-AI
5.2x
per engineer, vs 0.40 pre-AI

Anthropics vs. 500 OSS Performance Index

Per-engineer ETV for Anthropics 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: Anthropics is 46% below the index (2.08 vs 3.85 ETV/dev/mo). At the start of the tracked period the gap was 95% below.

Anthropics
2.08ETV / dev / mo
−0.12 (−5.5%) past 90d
500 OSS Performance Index
3.85ETV / dev / mo
+1.66 (+75.8%) past 90d

Behind the numbers

Aug

Written summary of the work completed each month.

During August 2026, the team recorded 280 commits, delivering core enhancements across the buffa protocol buffer engine and tool execution runners across multiple SDKs. Delivery remained steady in line with the recent run rate, though the Fixes score rose to 16 (+104% vs 8-score 5-month average) while the Features score shifted to 19 (-42% vs 33-score 5-month average). Key improvements centered on memory bounds enforcement, shared descriptor pools, and multi-turn pause handling.

Highlights

  • Optimized macOS sandbox profile generation in ee6b2eba (Dylan) by folding literal deny paths into alternation regexes, reducing profile size from 960 KB to 71 KB for 800 children.
  • Introduced shared descriptor pool capabilities across `buffa-build` and code generator plugins in 03585645 (Harrison) and 41349983 (Harrison), eliminating per-package descriptor duplication.
  • Optimized constant generation in `buffa-codegen` via c7169eb4 (Tim) by emitting single byte-string literals for FILE_DESCRIPTOR_SET_BYTES, achieving up to 21x speedups and $O(1)$ token complexity.
  • Expanded marketplace integrations by onboarding plugins including scandit-sdk ed404106 (abibbs-ant), hubspot-sales 54055099 (tobin), gc-ai 588a12db (tobin), unstructured-foundation e7dc7006 (tobin), and dynatrace 4d2a5994 (tobin).

Observations

Based on 280 commits37.1 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.

buffa

Avg performance

6.01 ETV

per engineer per month

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

—

Work mix

Features

0%

Maint

0%

Tests

0%

Docs

0%

Fixes

0%

1 dev18 ETV−14% since Q1 2026Repository report

knowledge-work-plugins

Avg performance

1.51 ETV

per engineer per month

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

—

Work mix

Features

0%

Maint

0%

Tests

0%

Docs

0%

Fixes

0%

2 devs9 ETV+17207% since Q1 2026Repository report

claude-agent-sdk-python

Avg performance

1.47 ETV

per engineer per month

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

—

Work mix

Features

0%

Maint

0%

Tests

0%

Docs

0%

Fixes

0%

2 devs9 ETV+55850% since Q2 2025Repository report

sandbox-runtime

Avg performance

0.69 ETV

per engineer per month

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

—

Work mix

Features

0%

Maint

0%

Tests

0%

Docs

0%

Fixes

0%

2 devs4 ETV+117% since Q4 2025Repository report

anthropic-sdk-php

Avg performance

0.67 ETV

per engineer per month

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

—

Work mix

Features

0%

Maint

0%

Tests

0%

Docs

0%

Fixes

0%

1 dev2 ETV+3942% since Q4 2025Repository report

claude-code-action

Avg performance

0.57 ETV

per engineer per month

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

—

Work mix

Features

0%

Maint

0%

Tests

0%

Docs

0%

Fixes

0%

1 dev2 ETV+86% since Q2 2025Repository report

claude-plugins-community

Avg performance

0.04 ETV

per engineer per month

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

—

Work mix

Features

0%

Maint

0%

Tests

0%

Docs

0%

Fixes

0%

1 dev0 ETVRepository report

claude-plugins-official

Avg performance

0.03 ETV

per engineer per month

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

—

Work mix

Features

0%

Maint

0%

Tests

0%

Docs

0%

Fixes

0%

4 devs0 ETV−59% since Q4 2025Repository report

claude-code

Avg performance

0.01 ETV

per engineer per month

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

—

Work mix

Features

0%

Maint

0%

Tests

0%

Docs

0%

Fixes

0%

1 dev0 ETV−79% since Q2 2025Repository report

anthropic-sdk-python

Avg performance

0.00 ETV

per engineer per month

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

—

Work mix

Features

0%

Maint

0%

Tests

0%

Docs

0%

Fixes

0%

2 devs9 ETV+288% since Q2 2025Repository report

anthropic-sdk-typescript

Avg performance

0.00 ETV

per engineer per month

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

—

Work mix

Features

0%

Maint

0%

Tests

0%

Docs

0%

Fixes

0%

2 devs4 ETV−13% since Q2 2025Repository report

anthropic-sdk-csharp

Avg performance

0.00 ETV

per engineer per month

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

—

Work mix

Features

0%

Maint

0%

Tests

0%

Docs

0%

Fixes

0%

1 dev3 ETV−61% since Q4 2025Repository report

anthropic-sdk-go

Avg performance

0.00 ETV

per engineer per month

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

—

Work mix

Features

0%

Maint

0%

Tests

0%

Docs

0%

Fixes

0%

1 dev3 ETV+2048% since Q2 2025Repository report

anthropic-sdk-ruby

Avg performance

0.00 ETV

per engineer per month

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

—

Work mix

Features

0%

Maint

0%

Tests

0%

Docs

0%

Fixes

0%

1 dev3 ETV+130% since Q2 2025Repository report

anthropic-sdk-java

Avg performance

0.00 ETV

per engineer per month

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

—

Work mix

Features

0%

Maint

0%

Tests

0%

Docs

0%

Fixes

0%

2 devs2 ETV+252% 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

−98%

If performance per engineer more than doubled, each unit of engineering performance now costs approximately 98% 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

+485 engineers

At today's productivity, the current 11-person team delivers the performance equivalent of 496 engineers at the baseline 90-day rolling window (ending 2025-04-01). That's roughly 485 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.

buffa
CapEx %
0.0%
OpEx %
0.0%
sandbox-runtime
CapEx %
0.0%
OpEx %
0.0%
claude-plugins-official
CapEx %
0.0%
OpEx %
0.0%
claude-plugins-community
CapEx %
0.0%
OpEx %
0.0%
anthropic-sdk-python
CapEx %
0.0%
OpEx %
0.0%
claude-agent-sdk-python
CapEx %
0.0%
OpEx %
0.0%
anthropic-sdk-typescript
CapEx %
0.0%
OpEx %
0.0%
knowledge-work-plugins
CapEx %
0.0%
OpEx %
0.0%
anthropic-sdk-csharp
CapEx %
0.0%
OpEx %
0.0%
anthropic-sdk-go
CapEx %
0.0%
OpEx %
0.0%
anthropic-sdk-ruby
CapEx %
0.0%
OpEx %
0.0%
claude-code-action
CapEx %
0.0%
OpEx %
0.0%
anthropic-sdk-php
CapEx %
0.0%
OpEx %
0.0%
anthropic-sdk-java
CapEx %
0.0%
OpEx %
0.0%
claude-code
CapEx %
0.0%
OpEx %
0.0%
Total
CapEx %
0.0%
OpEx %
100.0%

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.

Iain McGinniss

74 ETV · 56% share

Qing Wang

7 ETV · 5% share

Ashwin Bhat

7 ETV · 5% share

Bryan Thompson

6 ETV · 5% share

Tobin South

6 ETV · 4% share

Robert Craigie

5 ETV · 4% share

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.

Q2'25—
Engineers
7
Cost / Perf Unit
0%
Engineers vs headcount
+1 engineer
Work mix
36% Features
Q3'25+127%
Engineers
9
Cost / Perf Unit
−43%
Engineers vs headcount
+9 engineers
Work mix
39% Features
Q4'25+4%
Engineers
12
Cost / Perf Unit
−27%
Engineers vs headcount
+6 engineers
Work mix
43% Features
Q1'26+274%
Engineers
16
Cost / Perf Unit
−74%
Engineers vs headcount
+52 engineers
Work mix
59% Features
Q2'26+46%
Engineers
18
Cost / Perf Unit
−80%
Engineers vs headcount
+81 engineers
Work mix
37% Features