59| Get Better at Getting Better: Leveraging AI to Elevate Human Learning [with Nathen Harvey]

AI is everywhere. And its use and capabilities are accelerating every day. But is AI actually helping us get better at getting better? Or is it just amplifying the friction, bottlenecks, and complexity that already exists in our workflows and processes?In this episode, Nathen Harvey, leader of the DORA Research team at Google, explores how AI is reshaping not just how we work, but how we can use it to elevate human work, collaborate as teams, and reach better outcomes.Drawing on new findings from the DORA 2025 report on AI-assisted software development, we dig into what truly drives high performance – regardless of your industry or work – and how AI can either accelerate learning or amplify bottlenecks.If you lead or work on any kind of team you’ll discover how to use AI thoughtfully, so it supports learning and strengthens the people-centered learning culture you’re trying to build.YOU’LL LEARN:How AI accelerates learning—or intensifies friction—based on how teams use itWhy AI magnifies what already exists, and why stronger human learning habits matter more than stronger toolsThe seven DORA team archetypes—and how to quickly spot strengths, gaps, and next steps for more effective collaborationHow to use team characteristics to target where AI (or any tech) will truly move the needle and support continuous improvementHow the Toyota Production System / lean principle of jidoka—automation with a human touch—guides us to use AI to elevate human capability, not replace itABOUT MY GUEST:Nathen Harvey, Developer Relations Engineer, leads the DORA team at Google Cloud. DORA enables teams and organizations to thrive by making industry-shaping research accessible and actionable. Nathen has learned and shared lessons from some incredible organizations, teams, and open source communities. He is a co-author of multiple DORA reports on software delivery performance and is a sought after speaker in DevOps and software development. IMPORTANT LINKS:Full episode show notes with links to other podcast episodes and resources: ChainOfLearning.com/59 Check out my website for resources and ways to work with me KBJAnderson.comConnect with Nathan Harvey: linkedin.com/in/nathen Follow me on LinkedIn: linkedin.com/in/kbjandersonLearn more about DORA: dora.dev/publications Join the DORA community: dora.community Download my free KATALYST™ Change Leader Self-Assessment: KBJAnderson.com/katalyst Learn more about my coaching, trusted advisor partnerships, and leadership learning experiences: KBJAnderson.com TIMESTAMPS FOR THIS EPISODE:03:04 What DORA is and how it’s used as a research program for continuous improvement04:31 AI’s primary role in software development as an amplifier where organizations are functioning well and where there’s friction05:53 Using AI to generate more code in software engineering07:03 Danger of creating more bottlenecks when you try to speed up processes07:44 Importance of a value stream to understand the customer journey10:41 How value mapping creates visibility across silos so others see different parts of the whole process10:55 The process of gathering information for the State of AI Assisted Software Development report12:20 Finding seven team characteristics based on a survey of 5,000 respondents and learning how to leverage the results to improve performance14:18 Examples of several team characteristics and how it applies over various industries16:33 The negative impact of focusing on the wrong process that impacts the throughput17:00 Focusing at different types of waste to prevent undue pressure on people17:51 What DORA has found in having a tradeoff in having fast and stable production pushes vs. working slow and rolling back changes18:50 Three big things you need to improve throughput and quality19:44 Why the legacy bottleneck team archetype is unstable with elevated levels of friction21:22 Why harmonious high achievers deliver sustainable high quality work without the burnout22:37 How the report findings are being used to help improve organizations23:42 Seven capabilities of the DORA AI Capabilities Model in amplifying the impact of AI adoption to improve team and product performance26:27 The capability of executing in small batches to see the process through to fruition28:52 How to leverage AI to elevate human work vs machine work30:58 The benefits of AI in making new skills accessible, but does not make anyone experts in a specific skill31:44 Leveraging AI to help you complete tasks that would’ve taken longer32:43 Using AI to elevate creative thinking, but doesn’t replace your thoughts33:56 Ability to ask AI “dumb” questions to improve collaboration across teams34:49 Creating an experiential learning experience where there's not a step-by-step path on how to reach outcomes37:08 Importance of collaboration when moving from point A to point B37:35 The difference between trainers and facilitators39:03 Using the DORA report to form a hypothesis for ...