AI-native companies win on speed, scale, and resilience. This episode shows how leaders can transform their organisations by adopting agentic and generative AI across engineering, data and analytics.
Sam and Julian describe the move from early experimentation to agent-driven workflows - coding agents, automated research and context-aware copilots that materially expand output.
They explain why CDOs must lead this shift, how knowledge curation becomes as important as code, and why strong context and testing frameworks separate real productivity from noise.
The conversation also outlines the risks of delaying adoption, the challenges of building in-house without constant model updates and the opportunity for every function - from engineering to operations - to augment human capability.
The guidance is clear: target high-value use cases, choose tools that learn your business, and build a culture that embraces continuous reinvention.