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Context is the Key to the Agentic Architecture Revolution: A Conversation with Baruch Sadogursky
Michael Stiefel spoke to Baruch Sadogursky about software architecture in the age of agentic AI. LLM can function, albeit stochastically, as reasoning machines capable of interpreting human ambiguity. With the appropriate rigorous context artifacts to control the LLM’s reasoning, software specifications can become the source of truth, while the code becomes a disposable intermediate language.
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From Java EE to Quarkus and LLMs: Adam Bien’s Playbook for Boring, Future‑Proof Systems
Adam Bien, an independent consultant and pioneer of zero dependencies in the enterprise world of Java, highlights the benefits of consistently using standards, regardless of whether they involve Java or existing patterns. He argues that by doing so, he managed to future-proof the systems he built, preparing them for the cloud era and even for the AI-Native era.
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Roq: Leveraging Quarkus to Build Static Sites at the Speed of Go
Andy Damevin, a developer who worked on Quarkus for almost a decade, talks about Roq, a project that started as an experiment to try to see if it’s possible to build a static web site generator on top of quarkus. He touches on the rationale for choosing Java and Quarkus, how to migrate to Roq, and the platform's future.
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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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The AI Joy Gap: Why Some Developers Thrive While Others Struggle
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Michael Parker, VP of Engineering at TurinTech AI, about bringing joy back to software development in the AI era, the emerging role of "factory architects" who orchestrate AI agents rather than write code directly, and the cultural divide between AI hype and the reality developers face on legacy codebases.
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Tiger Teams, Evals and Agents: The New AI Engineering Playbook
In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Sam Bhagwat, co-founder and CEO of Mastra, about building and sustaining open source communities, the emerging discipline of AI engineering and evals, and how cross-functional Tiger Teams are key to shipping agentic applications.
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Information Flow: The Hidden Driver of Engineering Culture
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Adrian Peryer about Ron Westrum's organizational culture continuum, the role of information flow in shaping team culture, and how leaders can develop requisite imagination to detect weak signals.
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Beyond Code: How Engineers Need to Evolve in the AI Era
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Ben Greene about embracing AI in software engineering, expanding beyond pure technical skills to understand business context, and prioritizing human empathy in increasingly automated systems.
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The Technical Founder's Path: Code, Leadership, and Balance
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Trisha Ballakur about transitioning from coder to startup CEO, balancing technical leadership with business development, and avoiding burnout on the journey.