Risk in the Risk in the Risk: Recursive Risk Discovery as a Polymath's Converted Function (The Advocatus Diaboli)
Sheldon K Salmon (Mr. AI/ON) · Zenodo (CERN European Organization for Nuclear Research) · 2026
This paper documents a specific cognitive profile and the recursive risk-decomposition method built on top of it, in my own account. The profile includes a measured extreme of visual imagery vividness (hyperphantasia, VVIQ 78/80, ~95th percentile) and a persistent, self-constructed spatial environment used for active reasoning rather than memorization. The method, "risk in the risk in the risk," extends the established premortem technique (Klein, 2007) past its normal single-pass stopping point, recursing failure analysis down to root causes before proposing a mitigation. I present two worked case studies (a generic-object teardown and a spacecraft-design exercise) demonstrating the method's transfer to an unfamiliar domain, and a professional track record (600+ built frameworks, concentrated in document red-teaming) as evidence the underlying operation is domain-general rather than subject-specific. I explicitly do not claim the vividness score explains or validates the method, and I do not claim domain expertise in any field the method could be applied to. The paper's central limitation, named directly rather than obscured, is that every claim currently rests on my own self-report, and Section 7 specifies what independent validation would need to look like before that changes.