Podcasts

If You Can’t Test It, Don’t Deploy It: The New Rule of AI Development?

Magdalena Picariello reframes how we think about AI, moving the conversation from algorithms and metrics to business impact and outcomes. She champions evaluation systems that don't just measure accuracy but also demonstrate real-world business value, and advocates for iterative development with continuous feedback to build optimal applications.

Effective Error Handling: a Uniform Strategy for Heterogeneous Distributed Systems

Jenish Shah, a back-end engineer focused on distributed systems at Netflix, provides more insights into how to handle failures in a distributed systems setup. He shares details on how he built a library that handles exceptions uniformly, regardless of the underlying communication protocol.

Cloud and DevOps InfoQ Trends Report 2025

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 creation process. These reports provide InfoQ readers with a high-level overview of key topics to watch and also help the editorial team focus on innovative technologies.

Mental Models in Architecture and Societal Views of Technology: a Conversation with Nimisha Asthagiri

In this podcast, Michael Stiefel spoke with Nimisha Asthagiri about the importance of system thinking, multi-agent systems, the consequences of society applying a technology into an area for which it was not designed, and whether we can ever have a healthy relationship with artificial intelligence.

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.