• Investigate mechanisms for the agent to learn from its mistakes
  • Design a feedback system that captures failed task summaries
  • Implement context injection of previous failures for better future performance
  • Develop a self-correction loop that allows agents to retry tasks with improved approaches
  • Create metrics to measure learning effectiveness over time
  • Test self-correction mechanisms with the gauntlet testing framework