Aviation 200+ engineers

Leading Aviation Company

A flag-carrier airline transformed engineering decisions with AI attribution and delivery metrics.

AI Engineering Intelligence
Q1 2026
Prompt to merge -39%
before 6.2h
after 3.8h
Rework rate -50%
before 22%
after 11%
AI lift on velocity +100%
before 0%
after 28%
12-week trend trending up
"AI code attribution changed the conversation with leadership. We now defend our roadmap with actual numbers on AI lift, rework rate, and prompt-to-merge time instead of gut feel."

VP of Engineering

Leading Aviation Company

The Challenge

With 200+ engineers spread across mission-critical systems, leadership needed hard numbers to justify continued investment in AI coding tools. Gut-feel arguments did not survive contact with the CFO, and there was no way to compare AI lift across teams or repositories.

The Solution

iftrue connected every GitHub repo and Jira board to a unified AI-impact view. Prompt-to-merge time, rework rate, and velocity lift are now tracked per team and per AI assistant, turning quarterly roadmap defenses into data walkthroughs instead of debates.

The Results

Tracked over two quarters of AI tool deployment.

Prompt to merge

-39%
Before 6.2h
After iftrue 3.8h

Median time from first AI prompt to merged PR.

Rework rate

-50%
Before 22%
After iftrue 11%

Half as many PRs require significant post-merge rework.

AI lift on velocity

+100%
Before 0%
After iftrue 28%

Measured sprint velocity gain attributable to AI assistants.

Ready to transform your engineering organization?

Start your journey to data-driven engineering management. Book a demo to see how iftrue can help your team.