InfoQ Homepage Podcasts
About this Podcast
Intended for architects and senior developers.
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2025 Key Trends: AI Workflows, Architectural Complexity, Sociotechnical Systems & Platform Products
In this end-of-year panel, the InfoQ podcast hosts reflect on AI’s impact on software delivery, the growing importance of sociotechnical systems, evolving cloud realities, and what 2026 may bring.
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The Latest in OpenJDK and JCP Expert Group: Insights with Simon Ritter
In this episode, Simon Ritter, deputy CTO at Azul, sat down with podcast host Michael Redlich, lead editor of the Java topic at InfoQ, and discussed the latest features in OpenJDK and Ritter’s experiences serving on the JCP Expert Group since JDK 9. OpenJDK topics included: the six-month release cycle, Generational Shenandoah, JDK Flight Recorder, Project Leyden and Compact Object Headers.
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Building a More Appealing CLI for Agentic LLMs Based on Learnings from the Textual Framework
Will McGugan, the maker of Textual and Rich frameworks, speaks about the reasoning of developing the two two libraries and the lesson learned. Also, he shares light on Toad, his current project, which he envisions being a more visually appealing way of interacting with agentic LLMs through command line.
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Platform Engineering for AI: Scaling Agents and MCP at LinkedIn
QCon AI New York Chair Wes Reisz talks with LinkedIn’s Karthik Ramgopal and Prince Valluri about enabling AI agents at enterprise scale. They discuss how platform teams orchestrate secure, multi-agentic systems, the role of MCP, the use of foreground and background agents, improving developer experience, and reducing toil.
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Bridging the Open Source Gap: from Funding Paradoxes to Digital Sovereignty
Gabriele Columbro, managing director of the Linux Foundation Europe, discusses the differences in the open-source landscape between Europe, China and the US. Stressing that the open-source landscape is the last favorable ground for global innovation in the current geo-political landscape.
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About this Podcast
Discussions on intentional corporate culture and software management approaches.
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Trust-first Leadership and Building Great Teams
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Natan Žabkar Nordberg about how effective leadership requires treating people as whole humans, giving trust first, implementing guided autonomy with clear boundaries, and building diverse teams through shared experiences.
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From Code to Strategy: Drive Organizational Impact Through Strategic Conversations and User Focus
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Mark Allen about how engineers can expand their influence through strategic conversations, user-focused development practices, and excellence in incident management. Mark emphasizes the importance of building cross-organizational relationships and working on meaningful problems with positive impact.
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Productivity Through Play: Why Messing Around Makes Better Software Engineers
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Holly Cummins about productivity in creative knowledge work like software engineering. She talks about how "messing around and having fun" actually enhances problem-solving, while exploring the shift from coding to code management with AI tools and the importance of managing cognitive load in modern development practices.
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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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