Doing What They Say, Not What They Reason: Locating the Faithfulness Gap in LLM Agents

Researchers have developed a method to measure whether AI agents actually follow their stated reasoning when making decisions, using a controlled Texas Hold'em poker simulation to test for consistency. This study addresses a critical gap in LLM reliability, as agents often diverge from their documented process during complex tasks. By creating a standardized environment to track these discrepancies, the findings help developers identify why models sometimes ignore their own logic, which is essential for improving the predictability of autonomous agents in social and strategic simulations.