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GenAI Security: Defending Against Deepfakes and Automated Social Engineering
In this episode, QCon AI New York 2025 Chair Wes Reisz speaks with Reken CEO and Google Trust & Safety founder Shuman Ghosemajumder about the erosion of digital trust. They explore how deepfakes and automated social engineering are scaling cybercrime and argues defenders must move beyond default trust, utilizing behavioral telemetry and game theory to counter attacks that simulate human behavior.
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Looking for Root Causes is a False Path: A Conversation with David Blank-Edelman
In this podcast, Michael Stiefel spoke with David Blank-Edelman about the relationship between software architecture and site reliability engineering. Site reliability engineering can give architecture vital feedback about how the system actually behaves in production. Architects and designers can then learn from their failures to improve their ability to build systems that can evolve.
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How to Use Apache Spark to Craft a Multi-Year Data Regression Testing and Simulations Framework
Vivek Yadav, an engineering manager from Stripe, shares his experience in building a testing system based on multi-year worth of data. He shares insights into why Apache Spark was the choice for creating such a system and how it fits in the "traditional" engineering practices.
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Cloud Security Challenges in the AI Era - How Running Containers and Inference Weaken Your System
Marina Moore, a security researcher and the co-chair of the security and compliance TAG of CNCF, shares her concerns about the security vulnerabilities of containers. She explains where the issues originate, providing solutions and discussing alternative routes to using micro-VMs rather than containers. Additionally, she highlights the risks associated with AI inference.
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Architecture Should Model the World as it Really is: a Conversation with Randy Shoup
In this podcast, Michael Stiefel spoke with Randy Shoup about how to evolve your software after a software failure, and how to improve the resilience of your software by modeling transient states using events and workflows. Software failure is inevitable, but learning from failure, including making the necessary changes to organizational culture, can make your software more resilient.
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Using Brain Science to Communicate and Lead Technical Teams Effectively
In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Charlotte de Jong Schouwenburg about how understanding brain science and emotional intelligence can help engineers and technical leaders improve communication, manage conflict, and build stronger teams.
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Building Engineering Culture Through Autonomy and Ownership
In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Marcos Arribas about building and scaling engineering culture as an organisation grows, emphasizing autonomous teams, ownership mentality, progressive feature rollouts with flags, small pull requests, strategic AI adoption, and the importance of hiring junior engineers for long-term organizational growth.
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How Blameless Culture Transforms Engineering Teams
In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Tameem Hourani about building a blameless engineering culture through radical transparency, focusing on system resilience over individual blame, and creating high-performing teams that can embrace change and learn from failures.
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The Myth of 100% Utilization: The Neuroscience of Productive Teams
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Shannon Mason about optimizing team productivity by understanding the neuroscience behind cognitive load, distinguishing between beneficial "slack time" and detrimental "idle time", and how the pursuit of maximum utilization that leads to burnout and poor decision-making.
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Why Software Development Sucks And 7 Mental Models To Help Fix It
Shane Hastie, Lead Editor for Culture & Methods, spoke to Thanos Diacakis about how teams often struggle with software delivery. He proposes a shift in mental models and a four-step framework to systematically improve software development by focusing on bottlenecks, balancing different types of work beyond just feature delivery, and investing 20-30% of effort in improving how the team works.