What the Dev?

What the Dev? is a podcast by the SD Times editorial team. We cover the biggest and newest topics in software development.

What the Dev? is a technology podcast hosted by SD Times, with 362 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

SD Times hosts What the Dev?, a technology show with 362 episodes published.

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  What the Dev?

  363: The Role of AI in Mainframe Modernization

  Aug 18, 202616 min

  Dave Rubinstein and Matt Whitbourne discuss the evolution and potential of mainframe modernization, particularly with the integration of AI. They highlight the long-standing challenge of maintaining legacy systems, such as COBOL, and the role of AI in enhancing innovation and efficiency. Whitbourne emphasizes the importance of understanding business logic before modernizing and the potential for AI to assist in this process. He also notes the benefits of AI in improving code serviceability, risk management, and compliance. The conversation underscores the need for a strategic approach to mainframe modernization, focusing on business goals and the unique characteristics of mainframe workloads.

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  What the Dev?

  362: The Disconnect Between AI-generated Code and Security

  Aug 11, 202626 min

  Dave Rubinstein interviews Ilya Kabanov, a former Google AI security manager, about the disconnect between AI's rapid code generation and security measures. Kabanoff, who leads the Weather Report and is a research affiliate at MIT, discusses the significant progress AI has made in writing functional code, citing a 4x increase in security over a year. However, security checks cost five times more than code writing, posing economic challenges. Kabanov emphasizes the need for education, understanding AI's limitations, and prioritizing fundamental security practices to ensure secure AI-generated code.

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  What the Dev?

  361: The AI Adoption Maturity Model (With Ipek Ozkaya of CMU SEI)

  Jul 21, 202619 min

  Dave and Ipek Ozkaya discuss the AI adoption maturity model created by Carnegie Mellon's Software Engineering Institute and Accenture. The model addresses issues like mismatched expectations, untested implementations, and misaligned applications that hinder AI investment returns. It includes eight core dimensions: organizational change, workforce and culture, workflow reengineering, risk and governance, data engineering, operations, technology ecosystem, and AI lifecycle engineering. The model progresses from exploratory AI to scaled AI, emphasizing the importance of strategic alignment, workflow reengineering, and ecosystem partnerships.

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  What the Dev?

  360: How do you nurture junior developers in an AI world? (With Barun Singh of Andela)

  Jun 30, 202616 min

  SD Times editor-in-chief Dave Rubinstein and Barun Singh of tech talent company Andela discuss the impact of AI on nurturing future developers. Singh emphasizes that while AI automates coding basics, core knowledge and critical thinking are still essential. He highlights the importance of code review, planning, and security, which require senior experience. Singh believes colleges should focus on foundational knowledge, and boot camps remain relevant due to their immersive learning approach. He notes a shift towards retraining existing talent rather than just recruiting new workers.

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  What the Dev?

  359: The Enduring Popularity of Postgres, and what lies ahead (With Snowflake's Craig Kerstiens)

  Jun 23, 202616 min

  In this episode, David Rubinstein talks with Craig Kerstiens, Snowflake's Director of Software Engineering on Postgres, about the enduring popularity of Postgres, a 30-year-old database technology, due to its reliability and recent innovations like JSON support and vector store databases. He highlighted the challenge of integrating operational (OLTP) and analytical (OLAP) data for AI applications, noting the importance of reducing latency and operational burden. Kerstiens introduced PG Lake, an open-source tool that embeds Iceberg in Postgres, simplifying data movement and querying. He also mentioned Snowflake's mirroring feature and the future of Postgres, emphasizing its continuous improvement and extension ecosystem.

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