InfoQ Homepage Engineering Culture Podcast Content on InfoQ
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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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Craig McLuckie on Culture as a Team's Operating System in the AI Era
In this podcast, Shane Hastie, Lead Editor for Culture & Methods spoke to Craig McLuckie, co-creator of Kubernetes and CEO of Stacklok, about the impact of AI coding tools on open source communities and engineering teams, designing deliberate organisational culture, and navigating evolving career paths for engineers in the age of AI.
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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.