About this episode

Mik Kersten discusses the challenges of turning AI output into business value and the need for organizations to adapt their structures and planning methods.

What if optimizing for AI output is actually slowing your company down? When code becomes nearly free to produce, the organizations still measuring productivity by output are solving the wrong problem. In this episode, Mik Kersten, author of “Project to Product” and the forthcoming “Output to Outcome,” shares why the real challenge of the AI era isn’t generating more code — it’s building organizations that can turn that output into customer and business value. Drawing on Carlota Perez’s model of technological revolutions and the theory of constraints, Mik explains how AI has removed the output bottleneck that software organizations were built around, and where the new constraints now live. He introduces three core models from the book — the outcome loop, the product operating model, and the outcome tree — as a framework for adapting how organizations plan, fund, and deliver value. Mik also addresses one of the most pressing decisions leaders face today: whether to cut headcount based on AI productivity gains, and why doing so without outcome visibility is a dangerous bet. The conversation covers how organizational structure, decision-making accountability, and leadership roles…

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