Setting targets for developer productivity metrics
In this episode, Abi Noda is joined by Laura Tacho, CTO at DX, engineering leadership coach, and creator of the Core 4 framework. They explore how engineering organizations can avoid common pitfalls when adopting metrics frameworks like SPACE, DORA, and Core 4.Laura shares a practical guide to getting started with Core 4—beginning with controllable input metrics that teams can actually influence. The conversation touches on Goodhart’s Law, why focusing too much on output metrics can lead to data distortion, and how leaders can build a culture of continuous improvement rooted in meaningful measurement.Where to find Laura Tacho: • LinkedIn: https://www.linkedin.com/in/lauratacho/• Website: https://lauratacho.com/Where to find Abi Noda:• LinkedIn: https://www.linkedin.com/in/abinoda In this episode, we cover:(00:00) Intro: Improving systems, not distorting data(02:20) Goal setting with the new Core 4 framework(08:01) A quick primer on Goodhart’s law(10:02) Input vs. output metrics—and why targeting outputs is problematic(13:38) A health analogy demonstrating input vs. output(17:03) A look at how the key input metrics in Core 4 drive output metrics (24:08) How to counteract gamification (28:24) How to get developer buy-in(30:48) The number of metrics to focus on (32:44) Helping leadership and teams connect the dots to how input goals drive output(35:20) Demonstrating business impact (38:10) Best practices for goal settingReferenced:DX Core 4 Productivity FrameworkEngineering Enablement PodcastDORA’s software delivery metrics: the four keysThe SPACE of Developer Productivity: There’s more to it than you thinkDevEx: What Actually Drives ProductivityDORA, SPACE, and DevEx: Which framework should you use?Goodhart's law Nicole Forsgren - Microsoft | LinkedInCampbell's law Introducing Core 4: The best way to measure and improve your product velocityDX Core 4: Framework overview, key design principles, and practical applicationsDX Core 4: 2024 benchmarks - by Abi Noda
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43:26
The AI adoption playbook: Lessons from Microsoft's internal strategy
Brian Houck from Microsoft returns to discuss effective strategies for driving AI adoption among software development teams. Brian shares his insights into why the immense hype around AI often serves as a barrier rather than a facilitator for adoption, citing skepticism and inflated expectations among developers. He highlights the most effective approaches, including leadership advocacy, structured training, and cultivating local champions within teams to demonstrate practical use cases. Brian emphasizes the importance of honest communication about AI's capabilities, avoiding over-promises, and ensuring that teams clearly understand what AI tools are best suited for. Additionally, he discusses common pitfalls, such as placing excessive pressure on individuals through leaderboards and unrealistic mandates, and stresses the importance of framing AI as an assistant rather than a replacement for developer skills. Finally, Brian explores the role of data and metrics in adoption efforts, offering practical advice on how to measure usage effectively and sustainably.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 Abi Noda:• LinkedIn: https://www.linkedin.com/in/abinoda In this episode, we cover:(00:00) Intro: Why AI hype can hinder adoption among teams(01:47) Key strategies companies use to successfully implement AI(04:47) Understanding why adopting AI tools is uniquely challenging(07:09) How clear and consistent leadership communication boosts AI adoption(10:46) The value of team leaders ("local champions") demonstrating practical AI use(14:26) Practical advice for identifying and empowering team champions(16:31) Common mistakes companies make when encouraging AI adoption(19:21) Simple technical reminders and nudges that encourage AI use(20:24) Effective ways to track and measure AI usage through dashboards(23:18) Working with team leaders and infrastructure teams to promote AI tools(24:20) Understanding when to shift from adoption efforts to sustained use(25:59) Insights into the real-world productivity impact of AI(27:52) Discussing how AI affects long-term code maintenance(29:02) Updates on ongoing research linking sleep quality to productivityReferenced:DX Core 4 Productivity FrameworkEngineering Enablement PodcastDORA MetricsDropbox Engineering BlogEtsy Engineering BlogPfizer Digital InnovationBrown Bag Sessions – A GuideIDE Integration and AI ToolsDeveloper Productivity Dashboard Examples
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29:10
Gene Kim on developer experience and AI engineering
In this episode, we’re joined by author and researcher Gene Kim for a wide-ranging conversation on the evolution of DevOps, developer experience, and the systems thinking behind organizational performance. Gene shares insights from his latest work on socio-technical systems, the role of developer platforms, and how AI is reshaping the shape of engineering teams. We also explore the coordination challenges facing modern organizations, the limits of tooling, and the deeper principles that unite DevOps, lean, and platform engineering.Mentions and links:Phoenix ProjectDecoding the DNA of the Toyota Production SystemWiring the Winning OrganizationETLS VegasFind Gene on LinkedInDiscussion points:(0:00) Introduction(2:12) The evolving landscape of developer experience(10:34) Option Value theory, and how GenAI helps developers(13:45) The aim of developer experience work(19:59) The significance of layer three changes(23:23) Framing developer experience(32:12) GenAI’s part in ‘the death of the stubborn developer”(36:05) GenAI’s implications on the workforce(38:05) Where Gene’s work is heading
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38:40
Getting Airbnb’s Platform team to drive more impact: Reorganizing, defining strategy, and metrics
In this episode, Airbnb Developer Productivity leader Anna Sulkina shares the story of how her team transformed itself and became more impactful within the organization. She starts by describing how the team previously operated, where teams were delivering but felt they needed more clarity and alignment across teams. Then, the conversation digs into the key changes they made, including reorganizing the team, clarifying team roles, defining strategy, and improving their measurement systems. Mentions and linksFollow Anna on LinkedInFor A deeper look into how our Engineers and Data Scientists build a world of belonging, check out The Airbnb Tech BlogDiscussion points:(0:00) Intro(1:40) Skills that make a great developer productivity leader(4:36) Challenges in how the team operated previously(10:49) Changing the platform org’s focus and structure(16:04) Clarifying roles for EM’s, PM’s, and tech leads(20:22) How Airbnb defined its infrastructure org’s strategy(28:23) Improvements they’ve seen to developer experience satisfaction(32:13) The evolution of Airbnb’s developer experience survey
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32:58
You have developer productivity metrics. Now what?
Many teams struggle to use developer productivity data effectively because they don’t know how to use it to decide what to do next. We know that data is here to help us improve, but how do you know where to look? And even then, what do you actually do to put the wheels of change in motion? Listen to this conversation with Abi Noda and Laura Tacho (CEO and CTO at DX) about data-driven management and how to take a structured, analytical approach to using data for improvement.Mentions and Links:Measuring developer productivity with the DX Core 4Laura’s developer productivity metrics courseDiscussion points:(0:00) Intro(2:07) The challenge we’re seeing(6:53) Overview on using data(8:58) Use cases for data-engineering organizations(15:57) Use cases for data - engineering systems teams(21:38) Two types of metrics - Diagnostics and Improvement(38:09) Summary
This is a weekly podcast focused on developer productivity and the teams and leaders dedicated to improving it. Topics include in-depth interviews with Platform and DevEx teams, as well as the latest research and approaches on measuring developer productivity. The EE podcast is hosted by Abi Noda, the founder and CEO of DX (getdx.com) and published researcher focused on developing measurement methods to help organizations improve developer experience and productivity.
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