AI Safety

Research and practices aimed at ensuring AI systems behave as intended, avoid harmful outputs, and remain under human control. In the agent context, AI safety covers output filtering, action approval gates, alignment with user intent, and preventing misuse. Especially important for agents that take real-world actions like sending emails, modifying data, or executing code.