Podcasts

How Will We Train Developers If AI Does the Routine Work: A Conversation with Scott Hanselman

In this podcast, Michael Stiefel spoke to Scott Hanselman about developing new software engineers when artificial intelligence agents are doing most of the work on which junior developers were trained. Hanselman suggests the software industry should adopt a preceptorship model similar to the nursing profession.

Will Agentic AI Bring Fantasia’s Sorcerer's Apprentice to Life?: A Conversation with Tracy Bannon

In this podcast, Michael Stiefel spoke to Tracy Bannon about the role of artificial intelligence in software and the attendant risks in the areas of security, software development, and society at large. While it might be reasonable to assume a certain amount of trust within a software ecosystem, the risks escalate when the boundary between two software ecosystems is crossed.

Strands Agents with Clare Liguori

Thomas Betts talks with Clare Liguori, the technical lead on the open source Strands Agents SDK. The conversation covers how Strands Agents has grown from a Python SDK to a full agent harness running in production. Liguori shares some lessons learned from building agents at scale, shifting to a model-driven architecture, and what comes next as the LLMs that underpin agents continue to improve.

From MCP and Vibe Coding to Harness Engineering: How AI Native Engineering Evolved in One Year

Birgitta Böckeler, Distinguished Engineer at Thoughtworks, returns to discuss the rapid evolution of AI in software delivery. She touches on the evolution from vibe coding, the changing tools landscape and the more autonomous agents that, besides higher velocity, introduce higher risk.

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.