Exceeds

MARCH 2026

geteppo.com Engineering AI Productivity Report

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

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

The geteppo.com engineering team reports 49.5% AI adoption, 0.58× productivity lift, and 11.4% 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

MODERATE

49.5%

AI assistance is present in 49.5% of recent commits for geteppo.com.

AI Productivity Lift

LOW

0.58×

AI-enabled workflows deliver an estimated 0% lift in throughput.

AI Code Quality

LOW

11.4%

Review insights show 11.4% overall code health on AI-supported changes.

How is the geteppo.com team performing with AI?

The geteppo.com engineering team reports 49.5% AI adoption, translating into 0.58× productivity lift while sustaining 11.4% 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?

geteppo.com is at 49.5%. This is 5.8pp above the community median (43.7%)..

49.5%

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?

geteppo.com operates at 0.58×. This is 0.55× below the community median (1.13×)..

0.58×

↓0.55× below1.13× Community Median

Pilot AI-assisted grooming, ticket triage, or incident retros to create visible productivity wins.

How does AI affect code quality?

geteppo.com holds AI-assisted quality at 11.4%. This is 11.9pp below the community median (23.2%)..

11.4%

↓11.9pp 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?

57.6% of AI commits come from the most active contributors.

57.6%

Pair top AI practitioners with adjacent squads and capture their prompts/playbooks for reuse.

How can I prove AI ROI to executives?

To prove ROI, geteppo.com needs steadier adoption, measurable lift, and consistent quality. The ingredients are forming but not yet executive-grade.

Start with a lighthouse project, measure cycle improvements end-to-end, and harden quality guardrails.

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:

RO

rockstarwizard.ninja

(1.00×)

.I

.ieselrincon.es

(1.00×)

DR

draad.nl

(-9.59×)

WG

wgu.edu

(-0.41×)

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.

VA

Vishal Agarwala

Commits11
AI Usage20.0%
Productivity Lift2.00x
Code Quality20.0%
EV

Emiel Verkade

Commits8
AI Usage26.0%
Productivity Lift1.67x
Code Quality20.0%
GH

Greg Huels

Commits18
AI Usage27.6%
Productivity Lift1.21x
Code Quality20.0%
TB

Tyler Buffington

Commits6
AI Usage20.0%
Productivity Lift1.17x
Code Quality20.0%
BL

Blake

Commits1
AI Usage20.0%
Productivity Lift1.17x
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

4

btthomas

Eppo-exp/eppo-docs

sgdreamer7

Eppo-exp/sdk-test-data

Eppo-exp/eppo-docs

greghuels

contentful/marketplace-partner-apps

Eppo-exp/sdk-test-data

+2 more

calculust

Eppo-exp/eppo-docs

tbuffington7

Eppo-exp/eppo-docs

aarsilv

No repositories listed

Activity

94 Commits

Your Network

14 People
aarsilv
Member
bertilhatt
Member
btthomas
Member
DemetriPananoss
Member
emielver
Member
greg.dale@geteppo.com
Member
greghuels
Member
MaloChevillotte
Member
rasendubi
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