InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
-
[Video Podcast] Agentic Systems without Chaos: Early Operating Models for Autonomous Agents
In this episode, Shweta Vohra and Joseph Stein explore what changes when software systems start planning, acting, and making decisions on their own. The conversation distinguishes truly agentic use cases from traditional automation and looks at how architects and engineers should think about boundaries, orchestration, and system design in this new environment.
-
Mindful Leadership in the Age of AI
In this episode, Thomas Betts and Sam McAfee discuss how AI hype is reshaping organizational behavior, why many companies struggle with experimentation, and how unclear decision structures create friction. They explore psychological safety and mindful leadership as essential foundations for healthier, more effective engineering cultures.
-
[Video Podcast] AI Autonomy is Redefining Architecture: Boundaries Now Matter Most
This conversation explores why generative AI is not just another automation layer but a shift into autonomy. The key idea is that we cannot retrofit AI into old procedural workflows and expect it to behave. Once autonomy is introduced, systems will drift, show emergent behaviour, and act in ways we did not explicitly script.
-
[Video Podcast] Frictionless DevEx with Nicole Forsgren
In this episode, Thomas Betts talks with Dr. Nicole Forsgren, the author of Accelerate and one of the most prominent and important minds in DevOps and developer productivity. The conversation is about identifying and removing developer friction, the subject of her new book, Frictionless.
-
Developers Can Improve the ESG Aspects of Software by Tackling Early Ethical Debt
Erica Pisani, host of the Performance and Sustainability track at QCon London 2025, reflects on lessons from assembling the track and from attending the talks. She touches on the importance of the environmental and social aspects of software and hints at how developers can improve them through small steps in the architecture and practices of software development.
-
Building a Product-First Engineering Culture in the Age of AI
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Zach Lloyd about building a product-first engineering culture, and the critical importance of developers learning to effectively use AI tools while maintaining responsibility for code quality and understanding fundamental programming principles.
-
Technology Radar and the Reality of AI in Software Development
Shane Hastie, Lead Editor for Culture & Methods spoke to Rachel Laycock, Global CTO of Thoughtworks, about how the company's Technology Radar process captures technology trends around the globe. She is sceptical of the current AI efficiency hype, emphasizing that real value of generative AI tools lies in solving complex problems like legacy code comprehension rather than just writing code faster.
-
Achieving Sustainable Mental Peace in Software Engineering with Help from Generative AI
Shane Hastie spoke to John Gesimondo about how to leverage generative AI tools to support sustainable mental peace and productivity in the complex, interruption-prone world of software engineering by developing a practical framework that addresses emotional recovery, overcoming being stuck, structured planning and communication, maximizing flow, and fostering divergent thinking.
-
Adam Sandman on Generative AI and the Future of Software Testing
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Adam Sandman about how generative AI is transforming software development and testing by automating mundane tasks, enabling faster prototyping, and collapsing traditional roles into broader generalist positions, while also highlighting challenges like increased defects and ethical concerns.
-
Claire Vo on Building High-Performing, Customer-Centric Teams in the Age of AI
In this podcast, Shane Hastie, Lead Editor for Culture & Methods spoke to Claire Vo, Chief Product and Technology Officer at LaunchDarkly, about building high-performing, customer-centric teams, fostering a culture of experimentation, and preparing for the future of AI-driven software development.