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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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WebAssembly on the JVM: Feature Evolution, Performance, and the Transition to Endive
Andrea Peruffo discusses the evolution of WebAssembly beyond the browser and its growing role on the server-side JVM. He covers performance advancements in Wasm runtimes, moving from interpreters to efficient JIT compilation, and explores real-world production use cases ranging from edge computing platforms to modular plugin architectures.
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Rethinking Data: Moving from the Traditional Three-Tier Web Stack to Client-Side Event Sourcing
Johannes Schickling explores how he moved beyond the traditional three-tier web stack to a local-first approach. He shares his experience transitioning from Prisma to developing Overtone—a music curation app leveraging client-side event sourcing and SQLite. The discussion highlights the trade-offs between event sourcing and CRDTs.
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Strands Agents with Clare Liguori
Thomas Betts talks with Clare Liguori, the technical lead on the open source Strands Agents SDK. The conversation covers how Strands Agents has grown from a Python SDK to a full agent harness running in production. Liguori shares some lessons learned from building agents at scale, shifting to a model-driven architecture, and what comes next as the LLMs that underpin agents continue to improve.
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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.