Method Prescription Patterns
Method Prescription guides how the model transforms inputs into conclusions. It controls decomposition, sequencing, iteration, and verification. These patterns are used when the task is clear but the quality and reliability of reasoning matter.
Alternative Enumeration
Explicitly requires the model to surface multiple viable approaches to a task before committing to one, preventing premature convergence on a single solution.
Hierarchical Decomposition
Explicitly requires the model to break a concept into its immediate constituent parts, increasing structural resolution through containment rather than variation.
Dependency Decomposition
Solves complex problems by progressively establishing prerequisite answers, so later steps become solvable using the smallest amount of help required.
Stepwise Decomposition
Explicitly requires the model to solve a task by producing ordered intermediate steps, preventing premature answers and making the reasoning process visible.
Multi-Path Reasoning
Deliberately generates multiple independent reasoning paths for the same task and delays commitment to a final answer until those paths can be compared or aggregated.
Semantic Lifting
Forces the model to move a problem to a higher semantic level before reasoning, replacing a detail-heavy instance with a more general concept, principle, or canonical representation.