probabilistic-thinking

Core principle: Most real decisions happen under uncertainty. Probabilistic thinking replaces vague confidence with calibrated estimates. Bayesian thinking adds the discipline of updating those estimates as new evidence arrives — neither clinging to prior beliefs nor overreacting to new data.

Probability as Degree of Belief Probability isn't just for coin flips. It's a measure of how confident we are in any claim, given current evidence.

Base Rates Before estimating the probability of a specific event, find the base rate — how often does this type of event occur in a reference class?

Apply probabilistic and Bayesian thinking whenever the user needs to reason under uncertainty, compare risks, prioritize between options, update beliefs based on new evidence, or make decisions without complete information. Triggers on phrases like "what are the odds?", "how likely is this?", "should I be worried about X?", "which risk is bigger?", "does this data change anything?", "is this a signal or noise?", "what's the probability?", "how confident are we?", or any situation where decisions are being made based on incomplete or ambiguous evidence. Also trigger when someone is treating uncertain outcomes as certainties, or when probability language is being used loosely ("probably", "unlikely", "very likely") without quantification. Don't leave uncertainty unexamined. Source: andurilcode/skills.