How do you make an LLM agent actually learn from its own runs—successes and failures—without retraining? Google Research proposes ReasoningBank, an AI agent memory framework that converts an agent’s own interaction traces—both successes and failures—into reusable, high-level reasoning strategies. These strategies are retrieved to guide future decisions, and the loop repeats so the agent self-evolves. […]
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