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Architecture Should Model the World as it Really is: a Conversation with Randy Shoup
In this podcast, Michael Stiefel spoke with Randy Shoup about how to evolve your software after a software failure, and how to improve the resilience of your software by modeling transient states using events and workflows. Software failure is inevitable, but learning from failure, including making the necessary changes to organizational culture, can make your software more resilient.
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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.
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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.
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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.
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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.
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Productivity Through Play: Why Messing Around Makes Better Software Engineers
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Holly Cummins about productivity in creative knowledge work like software engineering. She talks about how "messing around and having fun" actually enhances problem-solving, while exploring the shift from coding to code management with AI tools and the importance of managing cognitive load in modern development practices.
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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.
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Using AI Code Generation to Migrate 20000 Tests
In this podcast, Shane Hastie, Lead Editor for Culture & Methods spoke to Sergii Gorbachov, a staff engineer at Slack, about how they successfully used AI combined with traditional coding approaches to migrate 20,000 tests in 10 months, discovering that AI alone was insufficient and required human oversight and conventional tools to work effectively.
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Emerson Murphy-Hill on Engineering Productivity, Team Dynamics and Equity
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Emerson Murphy-Hill about how measuring developer productivity is tricky, why team dynamics and psychological safety matter more than things like meeting load, the impact of systemic bias and how new AI tools are shaping equity in engineering - sometimes helping, but sometimes risking new kinds of unfairness.
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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.