Ep. #88, Metrics Are Good, Actually with Charity Majors

On episode 88 of o11ycast, Ken Rimple and Jessica Kerr speak with Charity Majors about the shifting role of observability in modern software development. From AI-assisted instrumentation to reducing developer cognitive load, the episode examines how teams can move from reactive monitoring to continuous learning. It’s a deep dive into observability as a sense-making practice, not just a tooling problem.

On episode 87 of o11ycast, Ken Rimple and Jessica Kerr sit down with Lada Kesseler to explore how experienced engineers can work effectively with AI coding assistants. They discuss why AI feels like a fast, noisy black box, and how patterns like semantic zooming, feedback loops, testing, and observability can help developers stay in control. This episode is a deep dive into using AI without sacrificing clarity, quality, or trust.

In episode 86 of o11ycast, Ken Rimple and Jessica Kerr sit down with Amarilis Campos from Nubank. They explore how Brazil’s largest digital bank uses observability to build resilience and autonomy at scale. Amarilis shares how Nubank’s culture of “acting like owners, not renters” and its journey from metrics and logs to tracing with Honeycomb helped the company grow to over 100 million customers.

In episode 85 of o11ycast, Dr. Cat Hicks unpacks AI’s impact on software teams from a psychological and social-science perspective. Along with Ken, Jess, and Austin, she explores how AI magnifies long-standing tensions between solitary and collaborative models of development, and how fears about AI often reflect deeper issues like undervaluing collaboration or having unrealistic productivity expectations. The discussion also explores empathy, theory of mind, and pluralistic ignorance, highlighting why developers may prepare more for AI than for each other.

In episode 84 of o11ycast, Ken Rimple and Martin Thwaites welcome Maddy Montaquila, lead PM for .NET Aspire at Microsoft. This episode dives into the "magic" of Aspire, exploring how it streamlines the developer experience from frictionless app startup to telemetry-rich development. Discover how Aspire makes telemetry a first-class citizen, simplifying debugging and enhancing observability for modern applications.

In episode 83 of o11ycast, the Honeycomb team chats with Dan Ravenstone, the o11yneer. Dan unpacks the crucial, often underappreciated, role of the observability engineer. He discusses how this position champions the user, bridging the gap between technical performance and real-world customer experience. Learn about the challenges of mobile observability, the importance of clear terminology, and how building alliances across an organization drives successful observability practices.

In episode 82 of o11ycast, Ken and Jess chat with Morgante Pell, the visionary behind Grit, an AI-powered agent designed to automate developer toil and technical debt. The discussion covers the evolution of AI in coding, the challenges of building and deploying AI agents, the future of combining code awareness with production awareness, and Grit’s acquisition by Honeycomb.

In episode 81 of o11ycast, Charity Majors and Martin Thwaites dive into a lively discussion with Hazel Weakly and Matt Klein on the evolving landscape of observability. The guests explore the concept of observability versioning, the challenges of cost and ROI, and the future of observability tools, including the potential convergence with AI and business intelligence.

In episode 80 of o11ycast, Ken Rimple and Jessica Kerr chat with Kent Beck about the emerging world of AI-assisted coding. Beck shares his experiences with "augmented coding," discussing the benefits, challenges, and the evolving relationship between developers and AI agents. They explore how these tools are changing software development practices and what it means for the future of coding.

In episode 79 of o11ycast, Hamel Husain joins the o11ycast crew to discuss the challenges of monitoring AI systems, why off-the-shelf metrics can be misleading, and how error analysis is the key to making AI models more reliable. Plus, insights into how Honeycomb built its Query Assistant and what teams should prioritize when working with AI observability.