Speaker: Pilar Fernández Gallego.
Abstract: Debates about the future of generative AI increasingly focus on its capacity to reshape economic and social structures by making complex, effort-intensive tasks more accessible, automated, and scalable. As with previous technological revolutions, these shifts challenge long-standing mechanisms of validation, expertise, and signaling, generating significant short-term disruption while redefining how value and competence are recognized.
This transformation is particularly evident in software engineering, where AI coding agents have rapidly evolved into essential tools for everyday development. Far from merely assisting with syntax, these systems can execute complex workflows, support decision-making, and significantly enhance productivity. Consequently, the role of the developer is undergoing a fundamental shift: core competencies are moving away from routine code production toward higher-level capabilities such as system design, problem framing, and the critical evaluation and integration of AI-generated outputs.
This raises important questions about the future of the profession. Will the growing reliance on AI tools create barriers for junior developers, who traditionally build expertise through hands-on coding experience? Or will it instead redefine pathways to expertise, placing greater emphasis on conceptual understanding and architectural thinking? In this evolving landscape, expertise is not disappearing but being reconfigured, potentially becoming even more critical as developers are required to guide, supervise, and contextualize increasingly autonomous systems.