Suppose a startup is testing a new customer acquisition strategy. Instead of launching a full-blown marketing campaign, it starts small, running a limited ad campaign with basic content to gauge audience engagement. As it iterates, it scales up what works and swiftly pivots away from what doesn’t. This approach allows it to quickly identify what works and adjust before scaling up.

This form of recursive de-risking flips traditional planning on its head. Rather than following a linear path from problem identification to market delivery, this approach emphasizes continuous cycles of identifying and mitigating risks. By focusing on the most significant unknowns early and testing them in the cheapest way possible, you generate rapid feedback that guides the next steps, reducing the chances of costly mistakes later on.

Recursive de-risking is a type of adaptive cycle akin to an OODA loop, where every action is part of an ongoing process of learning and adaptation. When risks could be existential, focusing the loop on risk directly addresses what is most likely to require a response. Each iteration provides new information that refines the system's behavior, leading to more resilient outcomes.

To apply recursive de-risking, start by identifying a goal or project with a high likelihood of failure. Sketch out a rough plan, and immediately focus on the biggest unknown or risk. Take the smallest, most cost-effective step to test that risk. Gather feedback, learn from it, and use that insight to adjust your approach. Repeat this process until you've built confidence and reduced uncertainty. This cycle doesn’t guarantee success but enables you to adapt to the challenges most likely to stand in your way.

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