What Happens When You Give your Agent Maximum Freedom

An AI model's training data has a far greater influence on its behavior than specific prompts or instructions. For instance, an agent will default to familiar coding patterns like sequential loops even when prompted to use parallel methods, because its training is a stronger prior. The most effective way to guide an agent is not by restricting it with prompts, but by allowing it to act freely within a sandboxed environment and then using runtime guards to catch and return errors for undesirable behavior. This approach leverages the model's deeply ingrained ability to process and correct errors, proving more effective than fighting against its training.