In the world of Large Language Models (LLMs), we often face a frustrating paradox: LLMs are incredibly capable at "reasoning" in the moment, but they are fundamentally stateless . Every time you start a new session, the agent has total amnesia. It doesn't remember the brilliant travel itinerary it planned yesterday, nor does it remember the mistake it made when it suggested a hotel that was too far from the airport. https://vishalmysore.github.io/reasoningBank/ ReasoningBank is a research concept (pioneered by Google Research) that aims to solve this "amnesia problem" not through model retraining or fine-tuning, but through a structured, persistent memory system. [!NOTE] This project, the ReasoningBank AI Travel Agent , is an independent demonstration and educational tool inspired by the ReasoningBank philosophy. While it implements the core loop of structured experience storage, it is not an official Google Research product. What is a ReasoningBank?…