How Much Memory Does Your Agent Actually Need?

The ideal amount of memory for an AI agent is a "dose" of learned guidelines that must be calibrated to the specific model's capabilities. Powerful models thrive when given the entire set of self-distilled strategies, while less capable models are overwhelmed and perform better with a smaller, more targeted selection of guidelines. This memory is implemented by injecting these lessons into the agent's context at inference time, improving performance without costly model retraining. Interestingly, some models that are already near their performance ceiling show no measurable gain, highlighting that memory is not a universal fix for all agents.