O11ycast

On episode 93 of o11ycast, Ken Rimple and Martin Thwaites sit down with Mike Goldsmith to explore how teams can control telemetry costs without sacrificing the data they need to understand their systems. They discuss choosing the right signals, reducing repetitive logs, building more efficient OpenTelemetry Collector pipelines, and using dynamic sampling to preserve valuable traces while cutting unnecessary volume.The post appeared first on Heavybit.

On episode 92 of o11ycast, Ray Myers joins Ken and Jess to explore how observability, reliability engineering, and formal software engineering practices are becoming even more important as AI coding agents take on larger roles in development. Rather than viewing AI as a replacement for established engineering disciplines, Ray argues that techniques like continuous delivery, testing, specifications, and formal verification provide the confidence needed to safely harness AI-generated code.The post appeared first on Heavybit.

On episode 91 of o11ycast, Ken Rimple and Jess Kerr sit down with Janaki Vivrekar. Janaki shares how Amplitude is building AI-powered analytics agents, why evaluation frameworks are becoming essential to AI product development, and how teams can use observability techniques to improve agent performance over time. The conversation explores eval-driven development, production feedback loops, and the challenges of helping AI systems reason about complex business data.The post appeared first on Heavybit.

Cory Ondrejka, CTO of OneBrief and author of the Outcome Engineering manifesto, breaks down agentic AI and why engineers must become outcome-focused. He discusses using AI to explore codebases, runtime validation, observability as proof, and reframing who can deliver software. Conversation highlights the manifesto’s principles, governance shifts, and practical approaches for rapid, measurable experimentation.

On episode 89 of o11ycast, Ken Rimple and Charity Majors are joined by Bryan Cantrill. They dive into the origins of observability, the realities behind AI productivity gains, and the tension between cloud convenience and infrastructure control. The discussion highlights how major tech shifts often look obvious only in hindsight.The post appeared first on Heavybit.

In this engaging discussion, Charity Majors, Co-founder and CTO of Honeycomb, explores the evolving landscape of observability in software development. She delves into how AI is transforming cloud expectations and emphasizes the importance of structured events and logs for meaningful insights. Charity argues for a shift from traditional metrics to continuous learning cycles, advocating for rapid deployments to enhance organizational learning. With her insights into the Dev–Prod feedback loop, she highlights how observability is a crucial sense-making practice in tech.

Lada Kesseler, a seasoned software developer known for her expertise in extreme programming and AI-assisted coding, joins the conversation to explore navigating the complexities of AI coding assistants. They delve into the AI black box phenomenon, discuss semantic zooming for clarity, and emphasize the importance of high-level tests and feedback loops in managing agent behavior. Lada shares her successful experiences with AI in frontend development and offers practical tips for maintaining relevance in AI-generated documentation while ensuring effective collaboration.

Amarilis Campos, a product and engineering leader at Nubank, shares insights on scaling Brazil’s largest digital bank to over 100 million customers. She discusses fostering a culture of ownership and psychological safety, which empowers teams to make decisions. Amarilis explains how moving from metrics and logs to Honeycomb tracing enhances observability, allowing greater autonomy and efficiency. The conversation includes how observability tools track customer journeys and the importance of performance, AI, and tailored telemetry in meeting diverse business needs.

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.

Maddy Montaquila, Lead PM for .NET Aspire at Microsoft, shares insights on making developer experiences smoother. She delves into how Aspire simplifies app setup and enhances telemetry, making debugging easier. The conversation covers integrating OpenTelemetry with tools like Blazor and MAUI, while also discussing real-world challenges and hilarious demo moments. Montaquila emphasizes the importance of user feedback and the community, spotlighting initiatives like 'Aspire Fridays' to engage developers and enhance their coding journeys.