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About this Podcast
Intended for architects and senior developers.
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A Java Performance Quest: Taming Unsafe Code, Embracing Idiomatic Style & Debugging the Linux Kernel
In this podcast, Jaromir Hamala, a seasoned Java engineer specialising in high-throughput data systems, shares his thoughts on how developers can tackle high-performance software development. He touches on the benefits of modern Java that allow writing idiomatic Java code while remaining "mechanically sympathetic", and also on his experience debugging a Linux kernel bug.
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Engineering Stable, Secure and Scalable Platforms: a Conversation with Matthew Liste
In this podcast, Michael Stiefel spoke to Matthew Liste about building and managing software platforms. Platform services act as the basis for application development, and must always be stable, secure, and scalable. Scaling these systems is particularly difficult because unknown resource contention often causes them to break.
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Context Engineering with Adi Polak
In this episode, Thomas Betts and Adi Polak talk about the need for context engineering when interacting with LLMs and designing agentic systems. Prompt engineering techniques work with a stateless approach, while context engineering allows AI systems to be stateful.
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Andres Almiray on How to Release Any Software to Any OS with JReleaser
Andres Almiray, a serial open-source contributor and the creator of JReleaser, discusses the project's state, noting that the tool is usable across any ecosystem, not just Java. He also touches on the Common House Foundation's mission.
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Mindful Leadership in the Age of AI
In this episode, Thomas Betts and Sam McAfee discuss how AI hype is reshaping organizational behavior, why many companies struggle with experimentation, and how unclear decision structures create friction. They explore psychological safety and mindful leadership as essential foundations for healthier, more effective engineering cultures.
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About this Podcast
Discussions on intentional corporate culture and software management approaches.
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Technology Radar and the Reality of AI in Software Development
Shane Hastie, Lead Editor for Culture & Methods spoke to Rachel Laycock, Global CTO of Thoughtworks, about how the company's Technology Radar process captures technology trends around the globe. She is sceptical of the current AI efficiency hype, emphasizing that real value of generative AI tools lies in solving complex problems like legacy code comprehension rather than just writing code faster.
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Using AI Code Generation to Migrate 20000 Tests
In this podcast, Shane Hastie, Lead Editor for Culture & Methods spoke to Sergii Gorbachov, a staff engineer at Slack, about how they successfully used AI combined with traditional coding approaches to migrate 20,000 tests in 10 months, discovering that AI alone was insufficient and required human oversight and conventional tools to work effectively.
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Technical Leadership: Building Powerful Solutions with Simplicity and Inclusion
In this podcast, Shane Hastie, Lead Editor for Culture & Methods spoke to Bhavani Vangala about creating powerful yet simple technology solutions, taking a balanced approach to AI tools, fostering inclusive team environments, and empowering women in tech leadership through focusing on strengths rather than societal constraints.
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Achieving Sustainable Mental Peace in Software Engineering with Help from Generative AI
Shane Hastie spoke to John Gesimondo about how to leverage generative AI tools to support sustainable mental peace and productivity in the complex, interruption-prone world of software engineering by developing a practical framework that addresses emotional recovery, overcoming being stuck, structured planning and communication, maximizing flow, and fostering divergent thinking.
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Taming Flaky Tests: Trisha Gee on Developer Productivity and Testing Best Practices
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke with Trisha Gee about the challenges and importance of addressing flaky tests, their impact on developer productivity and morale, best practices for testing, and broader concepts of measuring and improving developer productivity.
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