Patrick Debois

This talk proposes that context is the new code in software development, shifting focus from writing explicit code to generating and managing contextual information for AI agents. It outlines a "context development life cycle" analogous to the DevOps infinity loop, encompassing generation, testing, distribution, and observation of context. The core idea is that by engineering and refining context, developers can significantly improve the performance and reliability of AI-driven development processes.

This talk outlines four key patterns emerging in AI-native development, shifting the developer's role beyond traditional coding. As AI tools evolve from simple code generation to complex agent teams, developers are transitioning into roles like managers, specifiers, discoverers, and knowledge curators. This evolution signifies a move towards more strategic and less purely executional work, fundamentally changing the software development lifecycle.

This talk explores how Generative AI and agents will fundamentally reshape organizational structures, moving beyond simple co-pilot roles to become integrated team members and even peers. It examines the potential for AI to automate tasks, influence decision-making, and alter the very nature of work, prompting a re-evaluation of human roles and skills within companies. The discussion touches on the evolution from individual AI assistance to team-level AI integration and the broader implications for organizational design and the future of employment.