Announcing my new book, Frictionless
A clear, practical system for improving developer experience. Learn how to measure DevEx, identify friction, and drive lasting change—based on insights from Frictionless.
Abi Noda
CEO
All posts
Do newer AI-native IDEs outperform other AI coding assistants?
Claude Code and Cursor are associated with higher PR throughput, but org size and company stage play a big role.
Laura Tacho
CTO
AI-assisted engineering: Q4 impact report
Data and insights from 400+ organizations navigating their AI transformation.
Laura Tacho
CTO
The AI Strategy Playbook: What engineering leaders need to know about driving AI impact
Why some teams see 20-point jumps in productivity while others see performance decline
Justin Reock
Deputy CTO
Technical leadership: How to enable high-performing engineering teams
Technical leadership shapes developer experience through clarity, reduced cognitive load, and shorter feedback loops. Discover what separates effective tech leads from managers.
Taylor Bruneaux
Analyst
Meetings and interruptions are still the biggest obstacles for developers, even with AI
AI is not a silver bullet for productivity.
Justin Reock
Deputy CTO
Takeaways: How engineering leaders are planning AI budgets for next year
The current baseline for AI investment, why multi-vendor strategies are the norm, and which metrics leaders can use to demonstrate ROI on AI tools.
Autumn Faust
Community Insights
How are engineering leaders approaching 2026 AI tooling budgets?
Nearly half of engineering leaders are dedicating 1–3% of their 2026 budgets to AI tools, prioritizing measurable ROI, multi-vendor flexibility, and productivity gains.
Laura Tacho
CTO
Introducing Team SLAs
SLAs allow you to set up goals around specific performance metrics and see how your team is performing relative to them.
Josh Beitler
Product manager
What the 2025 DORA Report means for your AI strategy
DORA’s 2025 State of AI-Assisted Engineering Report reveals how AI is reshaping software delivery—amplifying both good and bad practices.
Laura Tacho
CTO
Three metrics for measuring the impact of AI on code quality
AI coding assistants promise speed, but are they sacrificing quality? Discover three key metrics for measuring the impact of AI on quality.
Kali Watkins
Product Marketing
AI’s impact on quality: A volatile, uneven landscape
DX data shows AI’s impact on code quality varies widely—reinforcing the need for leaders to measure outcomes within their own organizations.
Justin Reock
Deputy CTO
New in DX: major upgrades to DX AI
Here’s what’s new with DX AI.
Leo Epstein
Product Marketing
Our commitment to data neutrality
DX is doubling down on third-party data connectors and reporting capabilities.
Abi Noda
CEO
How 18 companies measure AI’s impact in engineering
The real metrics that GitHub, Google, Dropbox, and 15 other companies use to measure AI impact.
Laura Tacho
CTO
AI cuts onboarding time in half for new hires in the enterprise
Data from DX shows that engineers who use AI daily reach onboarding milestones nearly twice as fast as non-users.
Laura Tacho
CTO
How to optimize your AI tool rollout with data
This guide outlines the steps to get more from your AI investment and drive meaningful adoption, using data from DX.
Kali Watkins
Product Marketing
Takeaways: The evolving role of DevProd teams in the AI era
DX CEO and CTO Abi Noda and Laura Tacho discuss the “new mandate” for DevProd teams—what they should be focused on right now to remain relevant and impactful.
Kali Watkins
Product Marketing
Does tenure change how developers benefit from AI tools?
Data from 16,301 developers shows that while tenure still matters, AI levels the playing field.
Laura Tacho
CTO