Exceeds

MARCH 2026

php.net Engineering AI Productivity Report

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

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

The php.net engineering team reports 81.8% AI adoption, 1.63× productivity lift, and 19.9% 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

81.8%

AI assistance is present in 81.8% of recent commits for php.net.

AI Productivity Lift

HIGH

1.63×

AI-enabled workflows deliver an estimated 63% lift in throughput.

AI Code Quality

LOW

19.9%

Review insights show 19.9% overall code health on AI-supported changes.

How is the php.net team performing with AI?

The php.net engineering team reports 81.8% AI adoption, translating into 1.63× productivity lift while sustaining 19.9% 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?

php.net is at 81.8%. This is 38.2pp above the community median (43.7%)..

81.8%

Roughly in line43.7% Community Median

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

Does AI actually make developers faster?

php.net operates at 1.63×. This is 0.50× above the community median (1.13×)..

1.63×

↑0.50× above1.13× Community Median

Double down on automation around QA and release prep to compound the gains already in flight.

How does AI affect code quality?

php.net holds AI-assisted quality at 19.9%. This is 3.3pp below the community median (23.2%)..

19.9%

↓3.3pp below23.2% Community Median

Add structured AI code review rubrics and require human sign-off for critical surfaces.

How evenly is AI use distributed across our team?

AI impact is concentrated—89.1% of AI commits come from a few experts, raising enablement risk.

89.1%

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

How can I prove AI ROI to executives?

php.net 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:

CA

cancun.tecnm.mx

(87.3%)

MO

momentohq.com

(87.3%)

UB

ub.edu

(21.2%)

RO

rossabaker.com

(21.2%)

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

Productivity Lift

Cycle-time improvement vs baseline

Companies in this quartile:

IN

inngest.com

(4.82×)

U.

u.nus.edu

(2.87×)

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:

GZ

gzgz.dev

(20.0%)

GW

gwu.edu

(20.0%)

DR

draad.nl

(-82634.9%)

IN

inria.fr

(-2424.6%)

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.

GP

Gina Peter Banyard

Commits618
AI Usage90.1%
Productivity Lift1.93x
Code Quality20.0%
BR

Ben Ramsey

Commits10
AI Usage29.4%
Productivity Lift1.56x
Code Quality20.0%
LU

Luffy

Commits40
AI Usage35.8%
Productivity Lift1.43x
Code Quality20.0%
MS

Martin Samesch

Commits3
AI Usage20.0%
Productivity Lift1.10x
Code Quality20.0%
ST

Saki Takamachi

Commits52
AI Usage36.6%
Productivity Lift1.10x
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

13

mmalferov

ramsey/web-php

saundefined

ramsey/web-php

ramsey/php-src

+3 more

SakiTakamachi

schneems/php-src

ramsey/php-src

+3 more

Unknown contributor

php/doc-en

DanielEScherzer

php/php-src

php/web-php

+2 more

philip

ramsey/web-php

Activity

647 Commits

Your Network

25 People
ae@php.net
Member
bukka
Member
NattyNarwhal
Member
DanielEScherzer
Member
dstogov
Member
edorian
Member
ericmann
Member
felipensp
Member
Girgias
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