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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.
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OTROS EPISODIOS EN ESTE PODCAST
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 co…
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 exper…
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…
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. Disco…
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,…
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