What the Dev?

Dave welcomes Cassie Shum, RelationalAI adviser Cassie Shun, former VP ecosystem, product engineering there and formerly at Thoughtworks, to discuss the evolving role of developers in the era of AI. Shum highlights that while AI handles commoditized coding, developers are still essential for design patterns, testing and validation. She identifies two types of organizations: those with weak foundations and those with strong ones. Shum emphasizes the importance of documenting architectural inte...

Dave and Sreenivasan Rajagopal discuss the rising costs of AI in organizations, emphasizing the role of the Tokenomics Foundation, a Linux foundation formed by industry leaders, including Broadcom. Sreenivasan explains that AI spend is often exceeding budgets quickly, and the foundation aims to measure and optimize AI investments. They highlight Broadcom's Value Ops AI Tokenomics, which integrates AI costs into infrastructure management, focusing on governance, security, and value realization...

Dave Rubinstein interviews Gavriel Cohen, creator of NanoClaw, about the state of the project, an open-source multi-agent orchestration tool released in February. NanoClaw quickly gained popularity, with over 30,000 stars and 13,000 forks on GitHub, and a community of 5,000 in Discord. Cohen emphasizes the project's focus on agent isolation, credential management, and policy enforcement to prevent agents from going rogue. He discusses the importance of continuous testing and end-to-end framew...

Dave Rubinstein discusses with Tim Qi, lead data analyst at Linear, how AI is changing who builds software. Linear's study found that AI is accelerating team velocity and changing behavior on platforms. Companies are adopting AI in two main ways: top-down, tightly controlled rollouts, and bottom-up, allowing experimentation. Training varies, often evolving with use cases. AI adoption is similar across company sizes. The study also revealed that AI tools are making previously cumbersome tasks ...

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, r...