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This report draws on data from 500+ teams and reveals that AI is delivering measurable velocity gains, but velocity alone isn't the story. Download now First name* Last name* Work email* Company name* Would you like a free demo of DX? Executive summary Engineering organizations have entered a critical transition phase, shifting their focus from measuring baseline AI adoption to evaluating concrete return on investment.

Below are several features of the DX Core 4 that are critical to success: Multi-dimensional. Multiple dimensions are needed to capture software development comprehensively because changes to one dimension, such as speed, may negatively affect others (e.g., quality or effectiveness). The DX Core 4 includes four counterbalanced dimensions with metrics that encompass DORA, SPACE, and DevEx. Supports all levels of the organization.

Atlassian (DX) has been named a Leader in the inaugural 2026 Gartner® Magic Quadrant™ for Developer Productivity Insight Platforms. We believe this recognition reflects our commitment to giving engineering leaders the evidence-based frameworks and capabilities they need to make smarter investments in their teams and in AI.

This post was originally published in Engineering Enablement, DX’s newsletter dedicated to sharing research and perspectives on developer productivity. Subscribe to be notified when we publish new issues. Over the past 16 months, DX has been running a longitudinal study on AI’s impact on engineering velocity across a sample of more than 400 engineering organizations. We found that as AI tool usage increased by an average of 65%, median PR throughput increased by just under 8%.

Welcome to the latest issue of Engineering Enablement, a weekly newsletter sharing research and perspectives on developer productivity. 🗓 Join Abi on March 19th for a live Q&A session. He will address some of the more pressing questions we’ve received around measuring AI impact, the impact of tool choice, and more. Register here. Social media and vendor marketing have set high expectations for AI, suggesting as much as 2-3x productivity gains.

Welcome to the latest issue of Engineering Enablement, a weekly newsletter sharing research and perspectives on developer productivity. 🗓 On November 13th, Abi and Laura are hosting a live discussion on running data-driven evaluations of AI engineering tools. Register to join here.

Welcome to the latest issue of Engineering Enablement, a weekly newsletter sharing research and perspectives on developer productivity. This week I read SWE-Lancer: Can Frontier LLMs Earn $1 Million from Real-World Freelance Software Engineering?, a new paper from OpenAI that evaluates how well frontier AI models perform on real-world software development tasks.

Welcome to the latest issue of Engineering Enablement, a weekly newsletter exploring the data behind world-class engineering organizations. If you want insights like this delivered to your inbox, subscribe here: This week I read Identifying Factors Contributing to “Bad Days” for Software Developers: A Mixed-Methods Study, a new paper from Microsoft that dives into what disrupts developers’ workdays.

Abi Noda: Okay. All right, let’s dive in. Michelle, really excited to have you on the show today. Thanks so much for your time. Michelle Swartz: Thanks, Abi. It’s a pleasure to be here. Abi Noda: I’ve been fascinated and inspired by the DevEx journey at American Express. And where I want to start today is by you sharing where does the DevEx focus and effort live within your organization today?

Expert Guide DORA, SPACE, and DevEx: Which framework should you use? In this guide from DX’s CTO, Laura Tacho, you’ll learn how to think about and apply the DORA, SPACE, and DevEx frameworks for developer productivity. Laura describes what each framework is and what it’s useful for, how to collect metrics, and the benefits and drawbacks of using it.