Don’t measure AI Code Percentage on its own
What AI code percentage can help explain, and why it makes a poor optimization target.
A collection of ideas, evidence, and conversations about how developers work—and how to make that work better.
What AI code percentage can help explain, and why it makes a poor optimization target.
Brian interviews Meta researcher Moritz Beller about diff authoring time, experiments, AI, and software testing.
Where CAFE(S) fits alongside established approaches to engineering measurement and AI evaluation.
A practical introduction to evaluating the information we give AI agents.
Brian joins Max Kanat-Alexander, Eirini Kalliamvakou, and Margaret-Anne Storey to introduce a framework for evaluating agent context.
What happens when agents inherit the context problems that people have been compensating for.
Brian interviews Robert Lucero about agent identities, permissions, AI readiness, and the engineering practices that support safe autonomy.
Quoted on the difference between producing more code and achieving better engineering outcomes.
Using the TRUCE framework to ask what changes when AI writes more of our code.
Brian interviews Max Kanat-Alexander about engineering fundamentals, code review, and preparation for more capable AI workflows.
Statistical ways to understand how confidently teams can forecast delivery.
Examining how the relationship between cycle time and throughput varies across organizations.
Why industry trends can help interpret improvement even when organizations are different.
Brian and Justin Reock discuss AI adoption, engineering throughput, code quality, and the gap between faster work and better outcomes.
Brian interviews Tim Bozarth about EngThrive, shifting bottlenecks, and measuring engineering through outcomes.
The knowledge, confidence, and shared ownership we risk losing when we rethink code review.
How developer metrics can reveal the effects of changes far beyond our tools.
A conversation with Ankit Jain on meaningful AI measurement, engineering outcomes, and the emerging field of agent experience.
A case for evaluating AI through the organization’s ability to deliver valuable work.
Justin Reock and Brian discuss agent experience, engineering measurement, context, and the human costs of AI-assisted work.
A research roundup on how faster code generation changes the rest of the delivery process.
Three examples of measurement guiding meaningful changes to engineering work.
A panel with leaders from Etsy, Twilio, GitHub, Google, and Microsoft on AI, technical debt, engineering roles, and adoption.
How to interpret established engineering outcomes as AI changes the work underneath them.
How Microsoft combines outcome measures and diagnostics to improve engineering speed, ease, quality, and wellbeing.
Reflections from the SPACE authors on how the framework has held up in practice.
Brian hosts Abi Noda for a fireside discussion of DX research on AI adoption, throughput, and shifting development bottlenecks.
An accessible introduction to research challenging familiar assumptions about AI and developers.
Looking at how developers’ reported time savings change as AI use matures.
An interview about EngThrive, gaming alignment, and using metrics to improve the engineering environment.
How growing AI fluency changes developers’ responsibilities and professional identity.
Maps developers’ demand for AI support across daily tasks, including the work they want to delegate and the boundaries they want to preserve.
Uses the SPACE framework to examine where AI changes developers’ work and how team culture shapes those benefits.
A framework for evaluating the clarity, actionability, fidelity, efficiency, and security of context given to AI agents.
How increasing AI fluency changes the work developers do and how they understand their craft.
Examines recurring assumptions about generative AI through evidence from software engineering research.
An APAC session with Justin Reock and Eirini Kalliamvakou about context quality and effective AI agents.
A panel with engineering leaders from Uber, SAP, Morgan Stanley, Thoughtworks, and Moderne on verification, cost, and scaling AI development.
A research roundtable with Laura Tacho, Ciera Jaspan, Collin Green, and Eirini Kalliamvakou on AI adoption and engineering outcomes.
Explores how personalized AI agents can turn workplace telemetry into practical productivity support while respecting users’ preferences and privacy.
A conversation with Abi Noda about leadership advocacy, local champions, and practical ways to help developers adopt AI.
Studies how gaps between developers’ ideal and actual workweeks relate to satisfaction and productivity, and where AI assistance could help.
Distinguished Paper Award
A fireside conversation with Nachiappan Nagappan about engineering metrics, developer toil, and AI across the development lifecycle.
A discussion with Abi Noda about using SPACE and interpreting PR throughput as part of engineering measurement.
Examines daily work rhythms and how evening activity relates to developers’ perceived productivity and stress across work settings.
An on-site conversation with Baruch Sadogursky about SPACE and developer productivity engineering.
Surveys developers about the AI assistance they want and the reliability and workflow concerns that limit adoption.
Combines digital activity and self-reports to investigate burnout among cybersecurity incident responders and opportunities for organizational support.
Investigates links between developer experience and outcomes for individual developers, teams, and organizations.
How human factors, focused work, and multidimensional measurement shape engineering productivity as AI changes developer workflows.
Applying SPACE to developer experience, collaboration, and wellbeing as teams introduce AI tools.
Explores the benefits and tensions of hybrid engineering work through a survey spanning 28 companies and seven countries.
A discussion of wellbeing, focus time, collaboration, and how Microsoft approached productivity during remote and hybrid work.
Evaluates whether automatically protecting calendar time can improve workers’ focus, perceived performance, and experience of work.
Coverage of research and observations on developer productivity at Microsoft.
A short research briefing on how workspace design can support collaboration and individual work.
A short research briefing on differences in remote-work experiences and what they mean for wellbeing and productivity.
Synthesizes research on hybrid work across individuals, teams, organizations, and society.
Shows how the same conditions of pandemic remote work could help some developers while creating significant challenges for others.
Compares developers’ and managers’ views of productivity and quality and introduces the TRUCE framework for software quality.
An interview about the engineering systems and productivity work supporting Microsoft developers.
Brian presents Happy and productive hybrid developers: How to have it all! within a research session on remote and hybrid work.
A conversation with Jaime Teevan about remote work, social connection, onboarding, and measuring developer productivity holistically.
Studies the challenges of remote onboarding and the importance of helping new developers build social connections with their teams.
Introduces a multidimensional framework for understanding developer productivity and choosing measures that reflect how engineering work happens.
Brings together Microsoft research on the rapid shift to remote work and its implications for future work practices.
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