InfoQ Homepage Artificial Intelligence Content on InfoQ
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Governance in the Age of AI: a Conversation with Sarah Wells
In this podcast, Michael Stiefel spoke to Sarah Wells about the relationship of governance to software architecture. Governance enables teams to work effectively by establishing procedures that minimize system complexity, improve security, and reduce repetitive tasks. Targeted checklists help engineers by reducing the stress over these procedures.
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Requirements Analysis for Architects: a Conversation with Sonya Natanzon
Michael Stiefel spoke to Sonya Natanzon, about the intersection of technical and social aspects of software architecture. Understanding the business and how a company operates is more important than the specific technologies used. Effective requirements analysis requires focusing on problems to be solved that describe good and bad outcomes, rather than statements of need or solution statements.
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Chasing Efficient Java Development: from 1BRC to Developing Hardwood AI Natively
Gunnar Morling, technologist at Confluent and Java Champion, shares his experiences with building high-performance applications in Java, especially in the data space. He shares insights from experiments with building durable execution engines, bootstrapping, and AI natively developing Apache Hardwood - a minimal dependencies Java parser for Apache Parquet.
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Engineering Stable, Secure and Scalable Platforms: a Conversation with Matthew Liste
In this podcast, Michael Stiefel spoke to Matthew Liste about building and managing software platforms. Platform services act as the basis for application development, and must always be stable, secure, and scalable. Scaling these systems is particularly difficult because unknown resource contention often causes them to break.
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Context Engineering with Adi Polak
In this episode, Thomas Betts and Adi Polak talk about the need for context engineering when interacting with LLMs and designing agentic systems. Prompt engineering techniques work with a stateless approach, while context engineering allows AI systems to be stateful.
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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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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.