Hangar DX Podcast

"We can be in a flow state running in the wrong direction. Unless you can tie all your actions back to your strategic imperative, you might look back in five years and think: That was fun, but could I have gotten further?"In this episode of the HangarDX podcast, Ankit Jain, co-founder and CEO of Aviator, talks to Steve Pereira, lead consultant at Visible Value Stream Consulting and co-founder of the Flow Collective, to discuss where AI is genuinely moving the needle versus just generating more code to review, how to think about context switching and flow state when AI makes task-switching cheaper than ever, and how teams can use value stream mapping as a framework for getting AI adoption right.00:00 Introduction to Developer Experience and Value Stream Mapping05:20 Understanding Value Stream Mapping in Practice08:09 The Impact of AI on Value Stream Flow17:06 Context Switching and Flow State in Software Development27:48 Intentionality in Context Switching and Flow State35:07 Value Stream Mapping as a Superpower for AI Success📫 Sign up to our email list for more podcasts, articles, events, and other updates: https://www.aviator.co/podcast✏️ Subscribe for more videos: @Aviator-Co🙌 Join a curated community of senior engineers and engineering leaders focused on developer experience and solving productivity challenges at scale! Check out our upcoming off-the-record online sessions where vetted, experienced professionals can exchange ideas and share hard-earned wisdom: https://dx.community/

“Our internal target is to 2X our impact with AI over one year. Unlike some more outlandish mandates, that one is both aspirational and achievable,” says Emily Nakashima, SVP of Engineering at Honeycomb.In this episode of The Hangar DX podcast, Emily shares how Honeycomb approached AI adoption at scale and why they try not to focus on metrics that can be gamed but rely more on self-reporting by developers. Emily also discusses:- Why flattening org charts is a short-term optimization that will cost companies later- How Honeycomb issued a company-wide 2X mandate and what actually happened when they did- Why the "buffet phase" of AI tool adoption is over and what a structured rollout looks like- Why self-reporting beats hard metrics when measuring AI's impact on your team- Why observability is more critical than ever in a world of non-deterministic AI-generated code- Why AI SRE tools demo well but often fall short, and what they need to actually work00:00 Introduction to Developer Experience and AI02:19 Emily's Journey in Engineering and Leadership05:15 Navigating Career Growth in Engineering06:28 Cultural Shifts in Engineering Management09:50 The Evolving Role of Engineering Managers12:59 Upskilling in the Age of AI17:50 AI Strategy and Product Development at Honeycomb21:38 Measuring AI Impact and Productivity28:09 The Future of Observability and AI in EngineeringAbout Emily NakashimaEmily serves as SVP of Engineering at Honeycomb. A former manager and engineering leader at multiple developer tools companies, including Bugsnag and GitHub, Emily is passionate about building best-in-class, consumer-quality tools for engineers. She has a background in product engineering, performance optimization, client-side monitoring, and design.About Hangar DX (dx.community)The Hangar is a community of senior DevOps and senior software engineers focused on developer experience. This is a space where vetted, experienced professionals can exchange ideas, share hard-earned wisdom, troubleshoot issues, and ultimately help each other in their projects and careers.

"The future is already here, it's just unevenly distributed.", says Ryan J. Salva, Google and GitHub dev tools veteran. Ryan also shares:How OpenAI nearly took down GitHub's servers and how that incident seeded the creation of Copilot The five stages of autonomous engineering and why most teams are stuck between stage three and fourWhy DevOps and SRE are the next untouched frontier of AIThe three-step playbook for rolling out AI tools across large engineering teams without regressing on qualityWhy context, not the model, is the most important investment in AI-assisted development.About Ryan J. SalvaRyan is an experienced developer, product manager, and founder with 25 years of experience building developer tools at startups, Microsoft. GitHub, and now Google. Ryan leads product teams responsible for developer onboarding, code authoring, build and deployment systems, logging, observability, and end-to-end developer experiences. About Hangar DX (https://dx.community/)The Hangar is a community of senior DevOps and senior software engineers focused on developer experience. This is a space where vetted, experienced professionals can exchange ideas, share hard-earned wisdom, troubleshoot issues, and ultimately help each other in their projects and careers.We invite developers who work in DX and platform teams at their respective companies or who are interested in developer productivity.

“Engineers don’t always like merge queue because they have to wait longer for their PRs to merge. But the trade-off is that the quality of those merges will be higher, and the company will have less downtime and outages,” says Jon Block, founder of LowRouchAdvisor. Using a merge queue is like wearing a seatbelt, he adds, the only responsible thing to do for large engineering organizations that ship products that matter.Jon also shares best practices and lessons learned about scaling build and deploy from his 26 years of experience. Chapters00:00 Introduction to Developer Experience and Scaling Repositories01:37 Managing Repositories in Large Organizations05:24 Monorepo vs. Multirepo: Pros and Cons07:53 Challenges of Merge Queues and Deployment at Scale13:02 GitHub Merge Queue Limitations and Solutions15:36 Batching, Stability, and Deployment Strategies19:16 Train Method of Deployment and Rollbacks22:37 Build Systems, Bazel, and Build Avoidance23:20 Impact of Flaky Tests and Automation28:46 Adopting Merge Queues and Cultural Challenges34:11 AI in Development: Opportunities and Risks37:41 Closing Remarks and ResourcesAbout Jon BlockJon Block has spent 26 years in software engineering, nearly all of it at high-growth startups. He has served as VP of Engineering and CTO multiple times and today advises engineering organizations through his firm, Low Touch Advisors.About Hangar DX (https://dx.community/)The Hangar is a community of senior DevOps and senior software engineers focused on developer experience. This is a space where vetted, experienced professionals can exchange ideas, share hard-earned wisdom, troubleshoot issues, and ultimately help each other in their projects and careers.We invite developers who work in DX and platform teams at their respective companies or who are interested in developer productivity.Verify AI CodeAI writes code faster than humans can review it. Aviator Verify provides compliance-grade verification through spec-driven development. Ship faster with complete audit trails. https://verify.aviator.co/

The way that AI is changing software engineering is a bigger shift than object-oriented programming, the internet, and Agile together.", says Dave Farley, author of Continuous Delivery and Modern Software Engineering.Dave also shares why programming languages were designed to help engineers decompose problems into smaller chunks, the three fundamental problems of AI coding, why verification becomes the bottleneck in AI-assisted coding, and why engineering discipline, test-driven development, and behavior-driven development matter even more in this new era.00:00 Introduction to Developer Productivity and Experience02:13 Dave Farley's Journey in Software Engineering08:23 The Impact of AI on Software Development11:00 AI Tools and Their Role in Coding16:39 The Importance of TDD and BDD in AI Development20:37 Testing and Feedback Loops in AI Programming25:30 Navigating Ambiguity in Specifications29:29 Future of Software Architecture with AI34:55 Adapting to AI in Software Engineering Practices37:28 Conclusion and Future PerspectivesAbout Dave Farley Dave is a pioneer of continuous delivery, a thought leader and expert practitioner in CD, DevOps, TDD, and software design, and shares his expertise through his consultancy, YouTube channel ‪@ModernSoftwareEngineeringYT‬ , books, and training courses. Dave co-authored the definitive book on Continuous Delivery and has published Modern Software Engineering. About Hangar DX (https://dx.community/)The Hangar is a community of senior DevOps and senior software engineers focused on developer experience. This is a space where vetted, experienced professionals can exchange ideas, share hard-earned wisdom, troubleshoot issues, and ultimately help each other in their projects and careers.We invite developers who work in DX and platform teams at their respective companies or who are interested in developer productivity.More: https://dx.community/

One of the most common mistakes organizations make is equating platform engineering with a piece of software. Backstage is the most visible example. Teams adopt it and declare that they now “have a platform.”In this episode of the HangarDX podcast, Ankit Jain, co-founder and CEO of Aviator, talks with Ajay Chankramath, founder & CEO of Platformetrics, about what platform engineering really means in practice.Ajay discusses why platform engineering should be treated as a set of capabilities rather than a tool, how domain-driven platform engineering connects business intent to infrastructure, why “vibe coding” infrastructure with AI is risky, and how engineering leaders should think about ROI, observability, and supervised AI as adoption accelerates.00:00 Introduction to Developer Experience and Platform Engineering01:35 Defining Platform Engineering and Its Evolution05:59 Backstage is not Platform Engineering12:37 Understanding Maturity in Platform Engineering18:21 Domain-Driven Platform Engineering Explained26:16 The Impact of AI on Platform EngineeringAbout Ajay ChankramathAjay has 3+ decades of technology leadership experience and is currently the CEO of platformetrics. He is the co-author of Effective Platform Engineering. His current interests are around improving developer productivity using domain-driven platform engineering.About Hangar DX (https://dx.community/)The Hangar is a community of senior DevOps and senior software engineers focused on developer experience. This is a space where vetted, experienced professionals can exchange ideas, share hard-earned wisdom, troubleshoot issues, and ultimately help each other in their projects and careers.We invite developers who work in DX and platform teams at their respective companies, or who are interested in developer productivity.

“How much productivity is AI actually giving your engineering teams?” is the wrong question.In this episode of the HangarDX podcast, Ankit Jain, co-founder and CEO of Aviator, talks with Yegor Denisov-Blanch, researcher at Stanford University, about how engineering productivity is actually measured—and what the data says about AI’s impact on software teams.Yegor shares insights from large-scale studies on developer output, why early AI productivity claims were overstated, how high-performing teams compound their gains, why some teams see no benefit at all, and what engineering leaders should (and shouldn’t) measure when rolling out AI across the software development lifecycle.00:00 Introduction to Developer Productivity Research06:12 Research Methodology and Expert Evaluations10:35 Impact of AI on Developer Productivity18:56 Invisible Contributions and Team Dynamics24:59 Navigating Speed in Startups vs. Enterprises26:34 The Role of AI in Productivity Gains28:24 Measuring AI Usage and Results30:14 Experimentation and Adaptation in AI33:40 Understanding Ghost Engineers38:07 Remote Work and Performance DynamicsAbout Yegor Denisov-BlanchYegor helps software engineering teams make better decisions with data.Currently he is a researcher at Stanford University. Previously, Yegor led digital transformation at DHL, and was a national champion Olympic weightlifter. About Hangar DX (https://dx.community/)The Hangar is a community of senior DevOps and senior software engineers focused on developer experience. This is a space where vetted, experienced professionals can exchange ideas, share hard-earned wisdom, troubleshoot issues, and ultimately help each other in their projects and careers.We invite developers who work in DX and platform teams at their respective companies, or who are interested in developer productivity.

What happens when a single engineer’s side project turns into a company-wide AI platform used by every department—engineering, product, marketing, finance, customer support, and sales?In this episode of the Hangar DX Podcast, Block’s VP of Engineering Angie Jones shares the inside story of how Block deployed AI agents across the entire organization in just eight weeks.She reveals how an internal tool called Goose—originally built by one engineer—became one of the first-ever MCP clients, exploded as an open-source project, and evolved into a general-purpose agent powering workflows across the company.We also dig into security and governance, adoption strategies, and practical lessons that every platform team can learn from.00:00 Introduction to AI Transformation at Block04:18 Building Goose: The AI Agent08:50 Adoption Across Departments11:59 Scaling MCP Servers13:17 Technical Challenges with MCPs16:33 Governance and Security of MCPs17:35 Tool Overload and Centralization Strategies20:09 Overcoming Cold Start Problems23:34 Evolving Goose for Different Departments25:58 Open-Source and Internal Development28:05 Measuring Success in AI Initiatives30:02 Recommendations for AI Adoption33:19 Future Predictions and InitiativesAbout Angie JonesAngie Jones is the Vice President of Engineering, AI Tools & Enablement at Block, Inc.She is an award-winning teacher and international keynote speaker and holds more than 25 patents for inventions in the areas of virtual worlds, collaboration software, social networking, smarter planet, and software development processes.About Hangar DX (https://dx.community/)The Hangar is a community of senior DevOps and senior software engineers focused on developer experience. This is a space where vetted, experienced professionals can exchange ideas, share hard-earned wisdom, troubleshoot issues, and ultimately help each other in their projects and careers

"Measuring developer productivity is fundamental now that we're observing the largest change in software engineering in a decade. I'm happy we have our traditional productivity metrics in a good place so we can better observe the effect of AI." Moritz Beller is a software engineering researcher at Meta, and in this episode of the Hangar DX podcast, he talks to Ankit Jain, CEO and co-founder of Aviator, about how Meta came up with their foundational metric DAT - Diff Authoring Time, why time is one of the least gameable metrics, how AI-assisted development changes the meaning of “productivity,” and why investments in tooling drive far more value than surface-level optimizations.00:00 Introduction 01:04 Understanding Developer Insights at Meta04:42 Defining Diff Authoring Time (DAT)07:48 Evolution of DAT: From Version 1 to 611:17 Telemetry and Data Collection for Productivity14:01 Challenges in Measuring Software Engineering Productivity15:56 Impact of AI on Software Development Metrics17:48 Case Studies: Productivity Gains from Metrics22:26 Counterintuitive Findings in Productivity Metrics24:43 The Challenges of Measuring Productivity30:04 Qualitative Feedback and Developer Insights33:28 Advice for Engineering Leaders on Data-Driven Practices35:14 Future of Productivity Measurement in Software EngineeringAbout Moritz Beller Moritz is a software engineering researcher at Meta. In 2024, she began a part-time Master’s of Engineering in Software Engineering at the University of Auckland, researching the impact of AI on the profession itself. His interest lies in creating and empirically evaluating tools that help developers be more productive.About Hangar DX (https://dx.community/)The Hangar is a community of senior DevOps and senior software engineers focused on developer experience. This is a space where vetted, experienced professionals can exchange ideas, share hard-earned wisdom, troubleshoot issues, and ultimately help each other in their projects and careers.We invite developers who work in DX and platform teams at their respective companies or who are interested in developer productivity.