The DevEx leader’s guide to scaling AI adoption
This guide helps DevEx leaders navigate the AI transformation by breaking down:
Real-world stories from Meta and Google on scaling AI productivity
A practical framework to measure and map your AI maturity across the SDLC
Survey data from 400+ teams on how AI isused across coding, planning, and release
The DevEx leader’s guide to scaling AI adoption
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Survey results
We gathered data reaching a broad cross-section of leaders across company sizes, industries, and technical roles.
You’ll find the research broken down by:
Org size insights
Role and AI tool insights
Survey results by AI score and SDLC stage
Real stories from the enterprise
Learn how DevEx leaders from the large SaaS enterprises are scaling their AI workflows to boost productivity, including:
How Meta is transforming software testing with AI-powered bug hunters
How Google uses AI to speed up code migrations by 50%
How both are shifting the conversation from innovation to bottom-line results
5 common pitfalls of AI adoption
Many teams are adopting AI in the most superficial way possible. We break down the most common pitfalls of AI adoption, including:
Using AI without context
Lack of DevEx enablement
Shallow experimentation without a strategy
1
Using AI without context
2
Lack of DevEx enablement
3
Failure to integrate AI into workflows
4
No feedback or iteration loop
5
Shallow experimentation without a strategy
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More resources
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Quickstart metrics guide: DSAT
This guide will show you why DSAT matters, how to measure it, and how to improve it with practical actions and automation.