AI Metrics Productivity Adoption CultureFinding balance in the era of tokenmaxxingJun 2, 2026A new trend has emerged in software development: ’tokenmaxxing’, where organizations track and reward raw AI token consumption via internal leaderboards to spur adoption. While this gamification can nudge AI-hesitant developers to experiment, treating token spend as a performance indicator is a dangerous trap. Read more
DORA MetricsQuick Check updatesApr 22, 2026The DORA Quick Check was recently updated to include deployment rework rate and the latest industry benchmarks. Measure your team’s software delivery performance and compare it to the rest of the industry by responding to multiple-choice questions. Read more
AI Adoption Culture ProductivityBalancing AI tensions: Moving from AI adoption to effective SDLC useMar 10, 2026While AI accelerates initial code generation and reduces start-up friction, it introduces hidden taxes like heavy verification overhead, skill degradation, and integration challenges. Leaders must adapt holistic metrics, review processes, and team training to ensure sustainable success. Read more
AI Education Learning UC BerkeleyManaging AI dependency: How students are establishing guardrails with AIFeb 17, 2026While AI makes challenging projects feel more accessible, it also sparks anxiety about becoming too dependent. Our research with UC Berkeley students found that students are establishing guardrails for themselves, treating AI as a support tool rather than a replacement for deep understanding. Read more
DORA CommunityDevOps Dozen Awards 2025Jan 15, 2026The DevOps Dozen Awards are an annual program organized by the Techstrong Group. They honor the most influential individuals, innovative tools, and impactful companies within the DevOps community. DORA and some of our sponsors were nominated as finalists for the awards. Read more
DORA CommunityDORA 2025: Year in reviewJan 7, 2026A look back at the highlights and community contributions from 2025. Read more
Metrics DORAA history of DORA’s software delivery metricsJan 2, 2026DORA’s software delivery performance metrics have evolved over time to reflect the changing technology landscape. Learn about the transition from the four keys to the current five-metric model. Read more
AI Education Learning UC BerkeleyAI 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
AI Education Learning Developer Experience UC BerkeleyHow customization supports developer engagementSep 23, 2025While AI coding assistants excel at mechanical tasks, research with UC Berkeley students reveals they can introduce friction and cognitive load during complex, interpretive work. By customizing AI tools to align with specific tasks and preferences, developers can reduce this friction and create a more efficient, satisfying development experience. 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
