Exceeds

MARCH 2026

flowfoundation.org Engineering AI Productivity Report

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

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

The flowfoundation.org engineering team reports 93.3% AI adoption, 1.49× productivity lift, and 27.3% 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

93.3%

AI assistance is present in 93.3% of recent commits for flowfoundation.org.

AI Productivity Lift

HIGH

1.49×

AI-enabled workflows deliver an estimated 49% lift in throughput.

AI Code Quality

LOW

27.3%

Review insights show 27.3% overall code health on AI-supported changes.

How is the flowfoundation.org team performing with AI?

The flowfoundation.org engineering team reports 93.3% AI adoption, translating into 1.49× productivity lift while sustaining 27.3% 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?

flowfoundation.org is at 93.3%. This is 49.6pp above the community median (43.7%)..

93.3%

↑49.6pp above43.7% Community Median

Keep codifying prompts and monitoring adoption so the lead over peers is sustainable.

Does AI actually make developers faster?

flowfoundation.org operates at 1.49×. This is 0.36× above the community median (1.13×)..

1.49×

↑0.36× 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?

flowfoundation.org holds AI-assisted quality at 27.3%. This is 4.1pp above the community median (23.2%)..

27.3%

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 impact is concentrated—82.1% of AI commits come from a few experts, raising enablement risk.

82.1%

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

How can I prove AI ROI to executives?

flowfoundation.org combines strong adoption, lift, and quality control—making the ROI story executive-ready.

Link these metrics to deployment frequency and incident cost to convert engineering wins into business KPIs.

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:

ID

idesie.com

(2904.2%)

IN

inngest.com

(1429.6%)

PR

prefeitura.rio

(87.4%)

NA

naduni.local

(87.4%)

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.

JB

Jan Bernatik

Commits41
AI Usage90.7%
Productivity Lift1.96x
Code Quality75.4%
BM

Bastian Müller

Commits3
AI Usage36.0%
Productivity Lift1.62x
Code Quality76.0%
ZZ

zzggo

Commits123
AI Usage94.0%
Productivity Lift1.55x
Code Quality20.0%
AH

Alex Hentschel

Commits188
AI Usage93.7%
Productivity Lift1.40x
Code Quality89.7%
TB

Tim Barry

Commits222
AI Usage91.3%
Productivity Lift1.19x
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

5

bthaile

onflow/FRW-Extension

Unknown contributor

onflow/cadence

jordanschalm

onflow/flow-go

tim-barry

onflow/flow

onflow/flow-go

sisyphusSmiling

onflow/docs

manny-yes

onflow/flow

onflow/flow-go

Activity

518 Commits

Your Network

12 People
AlexHentschel
Member
turbolent
Member
sisyphusSmiling
Member
greg.santos@flowfoundation.org
Member
han.zhang@flowfoundation.org
Member
j1010001
Member
jordanschalm
Member
joseph.sprowes@flowfoundation.org
Member
manny-yes
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"

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Prove ROI

Export executive snapshots and benchmarks

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