This framework assesses candidate suitability for technical roles, suggesting implications for professional evaluations.
A rigorous metaprompt specification that instructs AI systems to conduct evidence-anchored assessments of candidate suitability for competitive technical positions. This framework enforces epistemic discipline through evidence-limitation constraints, distinguishing between "Not Evidenced" and "Absent" capabilities. Includes structured gap analysis, competitive positioning rubrics, and application materials generation pipeline. Compliant with CARP v1.0, CEPM, and Furlow License v2.0. Validated against the requirements of competitive AI safety and intelligence analyst roles; extensible to any high-stakes professional evaluation context requiring evidence-bounded work sample portfolios.
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Ariel J. Furlow (2026) studied this question.
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