The Shift's Big Interview #1: Mik Kersten on the new operating model for AI-native companies

The rise of AI necessitates a fundamental shift in organizational operating models, moving from a focus on maximizing software output to optimizing for business and customer outcomes. As AI-driven tools significantly amplify development capacity, the primary constraint for organizations shifts from developer productivity to organizational bottlenecks, such as decision-making speed and feedback loops. To thrive, companies must adopt an "outcome loop" that connects strategy and budgeting directly to measurable results, enabling rapid hypothesis testing and iterative development. While AI-native organizations like Cognition AI demonstrate the potential for this model, legacy enterprises face the challenge of reconfiguring their structures to avoid becoming slow-moving entities that struggle to adapt. Ultimately, engineering leaders must evolve from managing headcount to orchestrating systems of humans and agents, ensuring that increased technical output translates into tangible, sustainable business value rather than organizational bloat.