Exceeds

MARCH 2026

artsymail.com Engineering AI Productivity Report

A focused summary of AI adoption, productivity lift, and code quality for the artsymail.com engineering team.

See how AI-active teams rank this week on the Exceeds Leaderboards.

The artsymail.com engineering team reports 83.8% AI adoption, 1.16× productivity lift, and 21.2% code quality across recent work.

These metrics track how AI integrates into delivery pipelines, how throughput changes when assistance is used, and the health of AI-supported code review outcomes.

What this report measures

We analyze commits and diffs to estimate AI adoption, productivity lift, and code quality for your engineering organization.

How to interpret these metrics

Use these signals to understand how AI assistance fits into day-to-day development, where enablement efforts drive throughput, and how review practices keep quality steady.

AI Adoption Rate

HIGH

83.8%

AI assistance is present in 83.8% of recent commits for artsymail.com.

AI Productivity Lift

MODERATE

1.16×

AI-enabled workflows deliver an estimated 16% lift in throughput.

AI Code Quality

LOW

21.2%

Review insights show 21.2% overall code health on AI-supported changes.

How is the artsymail.com team performing with AI?

The artsymail.com engineering team reports 83.8% AI adoption, translating into 1.16× productivity lift while sustaining 21.2% code quality. These outcomes suggest AI-supported reviews are embedded in day-to-day delivery without trading off reliability.

Manager Questions Answered

Real questions engineering leaders ask about AI productivity, with live benchmarks and company-specific data.

What's a good company AI adoption rate?

artsymail.com is at 83.8%. This is 40.0pp above the community median (43.8%)..

83.8%

Roughly in line43.8% Community Median

Spot squads sitting below the median and pair them with high-adoption champions to share workflows.

Does AI actually make developers faster?

artsymail.com operates at 1.16×. This is 0.03× above the community median (1.13×)..

1.16×

Roughly in line1.13× Community Median

Instrument reviewer assignment and AI summaries to trim the slowest merge steps and edge past the median.

How does AI affect code quality?

artsymail.com holds AI-assisted quality at 21.2%. This is 2.1pp below the community median (23.3%)..

21.2%

Roughly in line23.3% Community Median

Invest in AI-specific test checklists and shadow reviews to keep quality slightly ahead of peers.

How evenly is AI use distributed across our team?

AI impact is concentrated—85.3% of AI commits come from a few experts, raising enablement risk.

85.3%

Run prompt-sharing sessions, codify AI review checklists, and incentivize broad participation.

How can I prove AI ROI to executives?

artsymail.com has a solid ROI signal with room to strengthen either adoption, lift, or quality before presenting to executives.

Document case studies where AI accelerates delivery while maintaining quality, and expand playbooks across teams.

See how your full organization compares

Unlock personalized insights across all your repositories, teams, and contributors.

Securely connect Exceeds with your codebase to get commit-level insights on AI adoption and performance.

How Your Company Ranks

See how top engineering organizations compare across AI adoption, productivity lift, and code quality.

AI Adoption

% of commits with AI assistance

Companies in this quartile:

QU

quantstack.net

(87.6%)

ST

student.su

(87.6%)

DG

dglover.co

(21.5%)

MO

monade.li

(21.5%)

Top 25% of teams adopt AI in 65-75% of their commits.

Productivity Lift

Cycle-time improvement vs baseline

Companies in this quartile:

KO

konghq.com

(6.64×)

IN

inngest.com

(4.82×)

AC

acad.pucrs.br

(1.12×)

MC

mcornholio.ru

(1.12×)

Top performers sustain 1.5× cycle-time improvements over six months when embedding AI into workflows.

Code Quality

Post-merge defect rate

Companies in this quartile:

KO

konghq.com

(795.0%)

IN

inngest.com

(701.7%)

GZ

gzgz.dev

(20.0%)

GW

gwu.edu

(20.0%)

Top 25% maintain quality above 92% while expanding AI usage, pairing automation with rigorous guardrails.

Rankings based on aggregated Exceeds AI dataset of 1.2M commits across open-source and enterprise engineering teams (Q4 2025).

Top contributors

Top contributors combine high AI adoption and quality output. Encourage internal sharing of best practices.

MJ

Matt Jones

Commits88
AI Usage67.0%
Productivity Lift1.66x
Code Quality20.0%
DK

Daria Kozlova

Commits145
AI Usage87.3%
Productivity Lift1.31x
Code Quality20.0%
XA

xander-pero

Commits40
AI Usage46.0%
Productivity Lift1.29x
Code Quality100.0%
AR

artsyit

Commits660
AI Usage70.5%
Productivity Lift1.20x
Code Quality20.0%
OK

Oksana

Commits104
AI Usage90.9%
Productivity Lift1.13x
Code Quality20.0%

Encourage knowledge transfer from top AI users to others through internal mentoring or recorded "AI coding walkthroughs." Balanced adoption across the team typically improves overall performance by 12-15%.

Cross-Organization Network

Shared Repositories

10

oxaudo

artsy/force

artsy/metaphysics

+2 more

dariakoko

artsy/eigen

artsy/metaphysics

+2 more

Mitch-Henson

artsy/force

artsy/metaphysics

artsyit

artsy/eigen

artsy/metaphysics

+4 more

louislecluse

artsy/cohesion

narikazu

artsy/horizon

Activity

729 Commits

Your Network

15 People
iskounen
Member
ansor4
Member
brainbicycle
Member
starsirius
Member
dariakoko
Member
artsyit
Member
JanaeHijaz
Member
artsyjian
Member
narikazu
Member

Why these metrics matter for engineering managers

Faster delivery

1.4x lift → predictable roadmaps

Safer velocity

93% quality → lower rollback risk

Equitable gains

AI less dependency on heroes

Governance

Depth monitoring audit-ready

ExceedsExceeds AI

Turns these insights into daily coaching and automatic alerts, helping managers balance speed with sustainability.

See the truth of AI impact

Adoption + lift + quality in one view

Learn more

Know where to act first

Repo and role level "lift potential"

Learn more

Prove ROI

Export executive snapshots and benchmarks

Learn more