Featured
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
Research & Insights
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
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
Building better software faster: Leading in the age of AI
Learn how to measure AI's real impact on developer productivity with proven frameworks. Get actionable strategies to move beyond hype and drive measurable improvements in your engineering organization.
Laura Tacho
CTO
How Faire's platform team built an AI code review agent
A closer look at how Faire is putting AI to work beyond just code generation.
Justin Reock
Deputy CTO
Unpacking METR’s findings: Does AI slow developers down?
A new study found developers were slower with AI coding tools than without. In this candid interview, METR study participant Quentin Anthony reveals why, and shares tips for using AI more effectively.
Kali Watkins
Product Marketing
How to introduce AI impact metrics into an engineering organization
Engineering leaders are under pressure to measure the impact of AI tools, but doing it wrong can backfire. This guide shares four best practices for introducing AI metrics in a thoughtful way.
Laura Tacho
CTO
Where does the time go?
If developers are saving time with AI, where does the time go?
Laura Tacho
CTO
Measuring AI in software teams: Trends we’re beginning to see
Early trends on how AI is reshaping software development, and how leaders can measure what matters to drive real impact.
Abi Noda
CEO
Data collection methodologies for measuring AI impact
There are three complementary data collection methods that, together, offer a well-rounded approach to measuring the impact of AI tooling.
Laura Tacho
CTO
METR’s study on how AI affects developer productivity
In this study, developers were 19% slower when using AI.
Abi Noda
CEO
AI: a complete paradigm shift, or just another dev tool?
A straightforward answer: it's both.
Laura Tacho
CTO
Takeaways: How to measure engineering productivity in the AI era
DX CEO and CTO Abi Noda and Laura Tacho discuss how to measure AI’s impact in engineering, track AI-generated code, safeguard quality, and more.
Brook Perry
Marketing
Using DX as a Director of Engineering at Adyen
A Director of Engineering at Adyen uses DX to align with Product, influence platform roadmaps, and drive data-driven decisions across teams.
Kali Watkins
Product Marketing
How can you measure AI's impact on your organization?
Despite AI's impact on how developers work, the core objectives remain the same: delivering working software that solves real problems
Laura Tacho
CTO
Introducing the AI Measurement Framework
A research-based approach for measuring the impact of AI in your organization.
Laura Tacho
CTO
How Snowflake’s DevProd team operates
The communication channels, rhythms, and principles that made Snowflake’s DevProd team one of the most trusted teams in the company.
Kali Watkins
Product Marketing
Applying the DORA metrics
DORA metrics can guide performance improvements, if you understand their context and limits.
Laura Tacho
CTO
AI acceptance rate: Easy to measure, easy to misuse
The question is no longer does AI work; it’s how well, and for whom, and where is the most value being created?
Laura Tacho
CTO