Exceeds

MARCH 2026

nasa.gov Engineering AI Productivity Report

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

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

The nasa.gov engineering team reports 49.3% AI adoption, 1.01× productivity lift, and 10.7% 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

MODERATE

49.3%

AI assistance is present in 49.3% of recent commits for nasa.gov.

AI Productivity Lift

LOW

1.01×

AI-enabled workflows deliver an estimated 1% lift in throughput.

AI Code Quality

LOW

10.7%

Review insights show 10.7% overall code health on AI-supported changes.

How is the nasa.gov team performing with AI?

The nasa.gov engineering team reports 49.3% AI adoption, translating into 1.01× productivity lift while sustaining 10.7% 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?

nasa.gov is at 49.3%. This is 5.5pp above the community median (43.7%)..

49.3%

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?

nasa.gov operates at 1.01×. This is 0.12× below the community median (1.13×)..

1.01×

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?

nasa.gov holds AI-assisted quality at 10.7%. This is 12.5pp below the community median (23.3%)..

10.7%

↓12.5pp below23.3% 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 usage is broad—top contributors represent 33.5% of AI commits.

33.5%

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

How can I prove AI ROI to executives?

To prove ROI, nasa.gov 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:

DI

dimagi.com

(87.5%)

PO

postgresql.org

(87.5%)

BL

bloq.com

(21.4%)

DA

daimond113.com

(21.4%)

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

Productivity Lift

Cycle-time improvement vs baseline

Companies in this quartile:

HR

hrvy.uk

(1.01×)

EM

emillon.org

(1.01×)

RO

rockstarwizard.ninja

(1.00×)

.I

.ieselrincon.es

(1.00×)

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.

ZB

Zach Boquet

Commits11
AI Usage96.0%
Productivity Lift2.00x
Code Quality20.0%
BW

Bryan Wexler

Commits22
AI Usage66.0%
Productivity Lift2.00x
Code Quality20.0%
EE

eereiter

Commits23
AI Usage94.0%
Productivity Lift2.00x
Code Quality100.0%
BA

Benjamin Auer

Commits121
AI Usage92.0%
Productivity Lift2.00x
Code Quality20.0%
CD

Chris Durbin

Commits164
AI Usage91.9%
Productivity Lift2.00x
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

30

Unknown contributor

nsidc/earthaccess

saraqzhang

GEOS-ESM/GEOSadas

GEOS-ESM/GEOSgcm_App

JosephVolosin

NASA-AMMOS/aerie

indiejames

nasa/harmony

nasa/Common-Metadata-Repository

Unknown contributor

GEOS-ESM/GEOSgcm_App

mason-t-yates

nasa/cumulus

Activity

1,371 Commits

Your Network

74 People
atrayano
Member
zhaobin74
Member
dccutrig
Member
DuJuan
Member
jlucas9
Member
rjbrown2
Member
gmao-yzhu
Member
zoghbi-a
Member
alexandr.v.semenov@nasa.gov
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