InfoQ Homepage Engineering Culture Podcast Content on InfoQ
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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