Probabilistic Multi-Variant Reasoning: Turning Fluent LLM Answers Into Weighted Options

Probabilistic Multi-Variant Reasoning (PMR) is a method for making better decisions by treating large language models as scenario generators instead of simple answer machines. This approach involves prompting an AI to propose multiple distinct options for a problem, rather than just a single solution. For each option, you then ask the model to estimate a rough probability of success and outline the potential risks, costs, and benefits. This structured output allows human decision-makers to have a more informed debate, consciously weighing the different futures before committing to a path.