Engineering Enablement by DX

AI and productivity: A year-in-review with Microsoft, Google, and GitHub researchers

Engineering Enablement by DX

Show Notes

As AI adoption accelerates across the software industry, engineering leaders are increasingly focused on a harder question: how to understand whether these tools are actually improving developer experience and organizational outcomes. In this year-end episode of the Engineering Enablement podcast, host Laura Tacho is joined by Brian Houck from Microsoft, Collin Green and Ciera Jaspan from Google, and Eirini Kalliamvakou from GitHub to examine what 2025 research reveals about AI impact in engineering teams. The panel discusses why measuring AI’s effectiveness is inherently complex, why familiar metrics like lines of code continue to resurface despite their limitations, and how multidimensional frameworks such as SPACE and DORA provide a more accurate view of developer productivity.

The conversation also looks ahead to 2026, exploring how AI is beginning to reshape the role of the developer, how junior engineers’ skill sets may evolve, where agentic workflows are emerging, and why some widely shared AI studies were misunderstood. Together, the panel offers a grounded perspective on moving beyond hype toward more thoughtful, evidence-based AI adoption. Where to find Brian Houck: • LinkedIn: https://www.linkedin.com/in/brianhouck/ • Website: https://www.microsoft.com/en-us/research/people/bhouck/

Where to find Collin Green: • LinkedIn: https://www.linkedin.com/in/collin-green-97720378 • Website: https://research.google/people/107023

Where to find Ciera Jaspan: • LinkedIn: https://www.linkedin.com/in/ciera • Website: https://research.google/people/cierajaspan/

Where to find Eirini Kalliamvakou: • LinkedIn: https://www.linkedin.com/in/eirini-kalliamvakou-1016865/ • X: https://x.com/irina_kAl • Website: https://www.microsoft.com/en-us/research/people/eikalli

Where to find Laura Tacho: • LinkedIn: https://www.linkedin.com/in/lauratacho/ • X: https://x.com/rhein_wein • Website: https://lauratacho.com/ • Laura’s course (Measuring Engineering Performance and AI Impact) https://lauratacho.com/developer-productivity-metrics-course

In this episode, we cover: (00:00) Intro (02:35) Introducing the panel and the focus of the discussion (04:43) Why measuring AI’s impact is such a hard problem (05:30) How Microsoft approaches AI impact measurement (06:40) How Google thinks about measuring AI impact (07:28) GitHub’s perspective on measurement and insights from the DORA report (10:35) Why lines of code is a misleading metric (14:27) The limitations of measuring the percentage of code generated by AI (18:24) GitHub’s research on how AI is shaping the identity of the developer (21:39) How AI may change junior engineers’ skill sets (24:42) Google’s research on using AI and creativity (26:24) High-leverage AI use cases that improve developer experience (32:38) Open research questions for AI and developer productivity in 2026 (35:33) How leading organizations approach change and agentic workflows (38:02) Why the METR paper resonated and how it was misunderstood

Referenced: • Measuring AI code assistants and agents • Kiro • Claude Code - AI coding agent for terminal & IDE • SPACE framework: a quick primer • DORA | State of AI-assisted Software Development 2025 • Martin Fowler - by Gergely Orosz - The Pragmatic Engineer • Seamful AI for Creative Software Engineering: Use in Software Development Workflows | IEEE Journals & Magazine | IEEE Xplore • AI Where It Matters: Where, Why, and How Developers Want AI Support in Daily Work - Microsoft Research • Unpacking METR’s findings: Does AI slow developers down? • DX Annual 2026

More from Engineering Enablement by DX

Oct 16, 2026

As AI agents become more capable, context quality is increasingly the limiting factor in their performance. In this episode of Engineering Enablement, DX researcher Brian Houck by his CAFE(S) is joined by co-authors Max Kanat-Alexander (Capital One), Eirini Kalliamvakou (DX), and Margaret-Anne Storey (University of Victoria) to discuss CAFE(S), a new framework for improving context quality. The panelists introduce the five dimensions of CAFE(S): Clarity, Actionability, Fidelity, Efficiency, and Security. They walk through common context failures, how poor context accrues technical and cognitive debt, what it costs in developer productivity and operating spend, how AI is changing the skills engineers need, and why context review could become as important as code review.

Oct 2, 2026

Meta researcher Moritz Beller joins Brian Houck to discuss how Meta measures developer productivity. Moritz explains diff authoring time and how Meta uses it to evaluate tools and guide engineering decisions. They explore how AI is changing engineers’ work and revealing gaps in traditional metrics. They also revisit Moritz’s “Mind the Gap” study and discuss the promise and risks of AI agents for testing.

Sep 11, 2026

In this episode of Engineering Enablement, Robert Lucero, Chief Architect at Okta, joins host Brian Houck to discuss how agentic AI is changing identity and access management. They explore how organizations should define agent identities, why authentication and authorization remain foundational, and how sandboxing, fine-grained permissions, and just-in-time access can enable agents to operate autonomously without creating unacceptable risk. Robert shares what Okta has learned from driving AI adoption among security-minded engineers, what makes a repository ready for AI agents, and why strong testing, CI, and review processes matter even more as AI generates more code. They also discuss AI’s role in software validation, the need for human judgment, and whether AI will ultimately give the advantage to security teams or attackers.

Aug 26, 2026

Max Kanat-Alexander is an Executive Distinguished Engineer at Capital One, where he helps lead developer experience and AI-assisted software development. In this episode of Engineering Enablement, Max joins Brian Houck to discuss how AI is changing software development and why strong engineering fundamentals matter more than ever. They explore how engineering skills are evolving, why AI can amplify weaknesses in the development lifecycle, and how teams should rethink code review, quality, and testing. Max also shares how leaders can assess whether their organizations are ready for more advanced AI workflows and why developing the next generation of senior engineers remains one of the biggest open questions in software engineering.

Aug 14, 2026

AI adoption among software developers is approaching 100%, AI-authored code now makes up more than half of merged code, and developers report saving more time with AI every quarter. But those gains aren’t translating evenly into better outcomes. In this episode of Engineering Enablement, host Brian Houck, Distinguished Scientist at DX, sits down with Justin Reock, Deputy CTO at DX, to unpack findings from DX’s latest AI Impact Report. They explore where AI is improving engineering velocity and developer experience, where concerns are emerging around PR size, change confidence, and failure rates, and why rising AI spend has yet to produce a comparable increase in innovation. They also discuss how AI is changing the meaning of code maintainability and where developers’ AI-driven time savings may actually be going.

See all episodes →