InfoQ Homepage Podcasts
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AI, ML, and Data Engineering InfoQ Trends Report 2025
In this episode, members of the InfoQ editorial staff and friends of InfoQ discuss the current trends in the domain of AI, ML and Data Engineering. One of the regular features of InfoQ are the trends reports, which each focus on a different aspect of software development. These reports provide the InfoQ readers and listeners with a high-level overview of the topics to pay attention to this year.
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Scaling Systems, Companies, and Careers with Suhail Patel
In this episode, Suhail Patel joins Thomas Betts for a discussion about growing yourself as your company grows. When he started at Monzo, Patel was one of four engineers on the then new platform team–there are now over 100 people. The conversation covers how to thrive when the company and the systems you’re building are going through major growth.
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Safely Changing Software to Avoid Incidents: a Conversation with Justin Sheehy
In this podcast, Michael Stiefel spoke with Justin Sheehy about how to safely put software into production without creating production incidents. Among the topics discussed were the futility of root cause analysis, and the importance of having a shared language for discussing incidents. This discussion included the need for software to be malleable as well as observable.
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Observability in Java with Micrometer - a Conversation with Marcin Grzejszczak
Marcin Grzejszczak, a veteran of observability spaces, discusses the current state of the space, including its evolution and the fine-grained details of how to instrument your system to capture all relevant information at every level - both inside services and between services communication.
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Why Rust Will Help You Deliver Better Low-latency Systems and Happier Developers
Andrew Lamb, a veteran of database engine development, shares his thoughts on why Rust is the right tool for developing low-latency systems, not only from the perspective of the code’s performance, but also looking at productivity and developer joy. He discusses the overall experience of adopting Rust after a decade of programming in C/C++.
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Engineering Leadership: Building Culture, Career Growth, and Ownership
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Thiago Ghisi about building engineering culture through leading by example, advancing careers by embracing "glue work" (non-technical but necessary tasks), taking full ownership of projects, and developing self-awareness to choose between technical and management career paths.
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Elisabeth Hendrickson on Systems Thinking for Quality Engineering
In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Elisabeth Hendrickson about using systems thinking to understanding relationships between problem elements rather than focusing on individual parts, and how quality engineering practices become even more critical in the age of AI where tools can accelerate code production but humans need to remain in charge of verification.
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Team Building in the Brave New World: Transforming Software Engineering Culture and Leadership
In this podcast, Shane Hastie, spoke to Duncan Grazier about transforming software engineering teams into polymorphic cultures where humans work alongside AI agents, requiring leaders to rethink career paths, focus more on communication and coaching skills, and navigate the implications of how the gap between junior and senior engineers rapidly closes due to AI augmentation.
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Building Human-Centered Engineering Cultures with Leadership, Diversity, and Trust
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Tara Hernandez about the importance of building generative cultures with strong leadership development, psychological safety, diversity, and transparency over simply chasing new technologies. Technology should be a means to solve meaningful human problems rather than an end in itself.
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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.