Exceeds

MARCH 2026

tngtech.com Engineering AI Productivity Report

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

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

The tngtech.com engineering team reports 81.1% AI adoption, 1.31× productivity lift, and 20.7% 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

81.1%

AI assistance is present in 81.1% of recent commits for tngtech.com.

AI Productivity Lift

MODERATE

1.31×

AI-enabled workflows deliver an estimated 31% lift in throughput.

AI Code Quality

LOW

20.7%

Review insights show 20.7% overall code health on AI-supported changes.

How is the tngtech.com team performing with AI?

The tngtech.com engineering team reports 81.1% AI adoption, translating into 1.31× productivity lift while sustaining 20.7% 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?

tngtech.com is at 81.1%. This is 37.4pp above the community median (43.7%)..

81.1%

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?

tngtech.com operates at 1.31×. This is 0.18× above the community median (1.13×)..

1.31×

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?

tngtech.com holds AI-assisted quality at 20.7%. This is 2.5pp below the community median (23.2%)..

20.7%

Roughly in line23.2% 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 usage is broad—top contributors represent 39.2% of AI commits.

39.2%

Keep rotating enablement leads and pair senior reviewers with new AI adopters to retain distribution.

How can I prove AI ROI to executives?

tngtech.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:

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:

IN

inngest.com

(701.7%)

ID

idesie.com

(649.2%)

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.

JK

Jonas Kellerer (TNG)

Commits23
AI Usage94.0%
Productivity Lift2.00x
Code Quality20.0%
MS

Markus Schüttler

Commits163
AI Usage92.0%
Productivity Lift2.00x
Code Quality20.0%
DH

Dominikus Hellgartner

Commits212
AI Usage92.0%
Productivity Lift1.90x
Code Quality20.0%
PB

Paul Bärnreuther

Commits70
AI Usage92.0%
Productivity Lift1.58x
Code Quality20.0%
RE

Rupert Ettrich

Commits29
AI Usage92.0%
Productivity Lift1.58x
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

8

marijnvg-tng

intel/AI-Playground

florianesser-tng

intel/AI-Playground

MartinVanIJcken

nhsuk/manage-vaccinations-in-schools

NHSDigital/manage-vaccinations-in-schools-testing

Unknown contributor

GenSpectrum/dashboard-components

rettrich-tng

knime/webapps-common

MUlfers

knime/webapps-common

Activity

1,002 Commits

Your Network

31 People
hvennekate
Member
hankem
Member
abraemer
Member
alexzurbonsen
Member
alistair-white-horne-tng
Member
TheOneFromNorway
Member
DanielHirschTNG
Member
David-Hickey-TNG
Member
Hellgartner
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