Exceeds

MARCH 2026

torontofilmschool.ca Engineering AI Productivity Report

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

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

The torontofilmschool.ca engineering team reports 97.6% AI adoption, 1.16× productivity lift, and 20.0% 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

97.6%

AI assistance is present in 97.6% of recent commits for torontofilmschool.ca.

AI Productivity Lift

MODERATE

1.16×

AI-enabled workflows deliver an estimated 16% lift in throughput.

AI Code Quality

LOW

20.0%

Review insights show 20.0% overall code health on AI-supported changes.

How is the torontofilmschool.ca team performing with AI?

The torontofilmschool.ca engineering team reports 97.6% AI adoption, translating into 1.16× productivity lift while sustaining 20.0% 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?

torontofilmschool.ca is at 97.6%. This is 53.8pp above the community median (43.7%)..

97.6%

↑53.8pp above43.7% Community Median

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

Does AI actually make developers faster?

torontofilmschool.ca operates at 1.16×. This is 0.03× above the community median (1.13×)..

1.16×

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?

torontofilmschool.ca holds AI-assisted quality at 20.0%. This is 3.3pp below the community median (23.3%)..

20.0%

↓3.3pp 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 impact is concentrated—99.8% of AI commits come from a few experts, raising enablement risk.

99.8%

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

How can I prove AI ROI to executives?

torontofilmschool.ca 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:

ID

idesie.com

(2904.2%)

IN

inngest.com

(1429.6%)

FM

fmease.dev

(87.5%)

DI

dimagi.com

(87.5%)

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.

JA

JAHHH204

Commits188
AI Usage28.0%
Productivity Lift2.00x
Code Quality20.0%
JO

JoshuaCTFS

Commits45
AI Usage98.0%
Productivity Lift1.16x
Code Quality20.0%
GU

Gurmin-S

Commits21
AI Usage20.0%
Productivity Lift1.02x
Code Quality20.0%
ZA

Zachmiller99

Commits13
AI Usage0.0%
Productivity Lift1.00x
Code Quality0.0%
ES

Estelle Schoeman

Commits1
AI Usage0.0%
Productivity Lift1.00x
Code Quality0.0%

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

2

slamdunkaroo

InteractivePixelStudios/What-The-Flock

Gurmin-S

InteractivePixelStudios/What-The-Flock

JoshCTFS

crazed6/CapstoneTFS_Fall2025

Will-LaBo

crazed6/CapstoneTFS_Fall2025

Ash88X

InteractivePixelStudios/What-The-Flock

Zachmiller99

InteractivePixelStudios/What-The-Flock

Activity

226 Commits

Your Network

9 People
EstelleSchoeman
Member
JoshCTFS
Member
Zachmiller99
Member
Ash88X
Member
alexander.baron@torontofilmschool.ca
Member
slamdunkaroo
Member
Gurmin-S
Member
jacob.sands@torontofilmschool.ca
Member
Will-LaBo
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