InfoQ Homepage Podcasts
About this Podcast
Intended for architects and senior developers.
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How Will We Train Developers If AI Does the Routine Work: A Conversation with Scott Hanselman
In this podcast, Michael Stiefel spoke to Scott Hanselman about developing new software engineers when artificial intelligence agents are doing most of the work on which junior developers were trained. Hanselman suggests the software industry should adopt a preceptorship model similar to the nursing profession.
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Scott Jenson on Evolving Desktop OS, Local-First, & Agentic UX
In this episode, Scott Jenson, a veteran UX designer known for his work on the Macintosh, Google Maps, and Chrome, examines the long-term stagnation of desktop operating systems and the limitations of current mobile and cloud-centric models.
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The Human Edge: Why Brownfield Codebases Need Mob Programming, Not Just AI Vibes
Asgaut Mjølne Söderbom and Ola Hast discuss the evolution of their software engineering practices past continuous deployment and pair engineering. The conversation continues where it left off in the previous episode and focuses on the experiments in adopting Claude Code and the reasons why they consider it good for everything else, but not coding.
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Will Agentic AI Bring Fantasia’s Sorcerer's Apprentice to Life?: A Conversation with Tracy Bannon
In this podcast, Michael Stiefel spoke to Tracy Bannon about the role of artificial intelligence in software and the attendant risks in the areas of security, software development, and society at large. While it might be reasonable to assume a certain amount of trust within a software ecosystem, the risks escalate when the boundary between two software ecosystems is crossed.
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Cloud and DevOps InfoQ Trends Report 2026: AI, Resilience, Platforms, FinOps, and Sovereignty
In this episode of the podcast, members of the InfoQ editorial staff and friends of InfoQ will discuss current trends in the cloud and DevOps domains as part of our annual trends report. These reports provide InfoQ readers with a high-level overview of key topics to watch. This podcast offers a chance to hear our raw conversation and the stories shared by our expert practitioners.
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About this Podcast
Discussions on intentional corporate culture and software management approaches.
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Signals and Levers: Building Thriving Engineering Organizations
In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Elisabeth Hendrickson and Joel Tosi about systems thinking as a lens for software delivery, the cultural "levers" leaders and teams can pull to shape organizations, and building thriving, sustainable teams amid AI-driven change.
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Personality Over Skillset: How Adam Wachtel Builds Engineering Teams
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Adam Wachtel, CTO at Click Boarding, about hiring for personality and problem-solving over pure skillset, turning around a platform and team in crisis, and how AI is reshaping team size and composition without ending SAAS.
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Founders, Friction, and Focus: Building Engineering Teams at Early-Stage Startups
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to David Gudeman about the unique culture of early-stage startup engineering, how founder personality quirks and premature process impositions can derail teams, and how engineers can build influence and make deliberate career choices without formal power.
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Culture & Methods Trends 2026: The Human Side of AI Engineering
This is the Engineering Culture Trends Report for 2026. Featuring a panel of QCon speakers and InfoQ contributors, they discussed AI adoption maturity and risk, the transformation of engineering team structures and roles, and the human dimensions of software development that must not be lost in 2026.
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Formal Methods for Every Engineer in an AI-Powered Future
In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Gabriela Moreira about making formal methods accessible through the Quint specification language, how AI is dramatically lowering the barrier to entry for formal specification and model-based testing, and why defining correct system behaviour remains essential human work in an AI-driven world.
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