minerva-hcs

Structured thinking for complex reasoning is a method that decomposes problems by explicitly tagging premises, constraints, biases, and ethical framing to enforce a consistent logic loop and enable robust decision making.

To apply mental models for far transfer, make the underlying logic explicit across domains using a structured reasoning loop that tracks simulation, optimization, and audience to guide robust decision making.

Structure an agent's reasoning loop by requiring explicit tags for premises, constraints, simulation, optimization, biases, audience, and ethical framing to govern the thought process and spot logical gaps.

Cognitive bias framing works with advanced problem decomposition by integrating ethical framing and audience tags into the structured reasoning loop, maintaining guardrails during complex tasks.

The best way to enforce consistent structured thinking in AI agents is applying a reasoning loop that requires explicit tagging of premises, constraints, simulation, and optimization to govern execution.

You should avoid using structured reasoning loops for problem solving when tasks require no deep reasoning or when the overhead of explicitly tagging premises, constraints, biases, and ethical framing provides no practical value.