AI Education LearningAI as a tutorDec 12, 2025While critics worry students use AI to cheat, our research reveals something different: students are using AI to learn. At UC Berkeley, many students in technical fields are using AI to teach them rather than do for them: AI was a supplement to the role of professor, TA, or tutor. Read more
AI Metrics Culture SecurityUnderstanding builder intent in the AI eraOct 17, 2025As AI decouples roles from tasks, traditional developer personas are becoming less relevant. This article introduces the “Builder Mindset” framework, identifying four core intents—Founder, Optimizer, Accelerator, and Learner—to help teams design better AI-assisted experiences. Read more
Metrics AIChoosing measurement frameworks to fit your organizational goalsAug 6, 2025Measuring software development effectiveness requires choosing the right framework to match your organizational goals. This guide explores popular frameworks like SPACE, DevEx, and DORA, offering practical steps for selecting metrics and adapting your measurement strategy for the AI era. Read more
AI Metrics Trust Security CultureConcerns beyond the accuracy of AI outputJun 30, 2025While accuracy remains a key challenge, developers have broader concerns about generative AI, including data privacy, deskilling, and job displacement. This post explores these anxieties and offers five strategies to address them, such as clarifying acceptable use policies and emphasizing AI as a learning opportunity. Read more
AI Metrics Culture AdoptionHelping developers adopt generative AI: Four practical strategies for organizationsJan 31, 2025DORA research identifies four practical strategies to help organizations scale generative AI adoption from isolated experiments to widespread use. Key recommendations include increasing transparency about AI plans, addressing developer concerns, providing dedicated learning time, and establishing clear usage policies. Read more
AI Metrics ProductivityHow gen AI affects the value of development workDec 10, 2024DORA research reveals a paradox where developers using generative AI report higher satisfaction despite spending less time on work they consider valuable. We explore five dimensions of value—utilitarian, reputational, economic, intrinsic, and hedonistic—to understand how AI is reshaping the meaning of development work. Read more
AI Metrics Trust Productivity Adoption SecurityFostering developers' trust in generative artificial intelligenceSep 13, 2024Research shows that developers who trust generative AI tools are more productive and use them more frequently. We outline five strategies to foster this trust, including establishing clear policies, reinforcing feedback loops like code review, and encouraging experimentation without mandates. Read more
