InfoQ Homepage Artificial Intelligence Content on InfoQ
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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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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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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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The Java Ecosystem Remains Ever-Green by Continuously Adapting to Developers' Needs
Kevin Dubois and Thomas Vitale, two cloud-native enthusiasts in the Java ecosystem, discuss the evolution of frameworks and tooling that has led to increased development and developer joy. They cover everything from Testcontainers to incorporating LLMs in existing applications, as well as how to ensure the code quality remains high, even with the proliferation of code generation tooling.
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Mandy Gu on Generative AI (GenAI) Implementation, User Profiles and Adoption of LLMs
In this podcast, Mandy Gu from Wealthsimple discusses how to establish AI programs in organizations and implement Generative AI (GenAI) initiatives, and the relationship between user profiles and adoption of LLMs.
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Technical Leadership: Building Powerful Solutions with Simplicity and Inclusion
In this podcast, Shane Hastie, Lead Editor for Culture & Methods spoke to Bhavani Vangala about creating powerful yet simple technology solutions, taking a balanced approach to AI tools, fostering inclusive team environments, and empowering women in tech leadership through focusing on strengths rather than societal constraints.
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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.
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Taming Flaky Tests: Trisha Gee on Developer Productivity and Testing Best Practices
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke with Trisha Gee about the challenges and importance of addressing flaky tests, their impact on developer productivity and morale, best practices for testing, and broader concepts of measuring and improving developer productivity.
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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.
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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.