Podcasts

Elena Samuylova on Large Language Model (LLM)-Based Application Evaluation and LLM as a Judge

In this podcast, InfoQ spoke with Elena Samuylova from Evidently AI, on best practices in evaluating Large Language Model (LLM)-based applications. She also discussed the tools for evaluating, testing and monitoring applications powered by AI technologies.

The Hidden Vulnerability of the Open Source Software Supply Chain: the Underlying Infrastructure

Software supply chain veteran Brian Fox unpacks the security implications of the new EU Cyber Resilience Act and its profound impact on open-source projects. He reveals the hidden infrastructure risks threatening open-source projects and shares insights for senior software leaders navigating this regulatory landscape.

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.

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.

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.

Leveraging AI Platforms to Improve Developer Experience – From Personal Hackathon to AI at Scale

In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Olalekan Elesin about how generative AI tools can elevate developer experience by enabling engineers to be more creative and productive. He stresses the need to manage expectations, develop prompt engineering skills, and maintain a focus on security and customer privacy when leveraging these tools in an enterprise setting.

Building Effective Engineering Teams and Avoiding Cargo Cult Practices

In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to David Guttman about building effective engineering teams, avoiding common pitfalls, critiques of cargo cult practices, building great engineering culture and the importance of individual accountability.

Developing Regulated Software at the Speed of Innovation: Insights from Erez Kaminski

In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Erez Kaminski about the challenges and importance of developing regulated software for safety-critical systems, emphasizing the need for validated DevOps and AI integration in industries like healthcare and automotive, while highlighting the balance between innovation, safety, and regulatory compliance.

Democratizing AI at Thomson Reuters: Empowering Teams and Driving Innovation

In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Maria Apazoglou, Head of AI, BI & Data Platforms at Thomson Reuters, about as her experience in building great teams and democratizing the use of large language models across the organization.

Spies, Lies, and Cybercrime: Insider Perspectives from a Former FBI Agent

In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Former FBI Operative Eric O’Neill about the growing threat of cyberattacks, cyber espionage and cybercrime, and how organizations and individuals can "think like a spy hunter" to better protect themselves.