Manual Training

Manual training in Cod3x allows users to directly influence their agents' learning processes by providing explicit feedback, thereby aligning the agents' behaviors with your preferences.

Methods of Manual Training:

1. Memory Storage Commands:

   • User Directive: Users can append instructions like "store this in your memory" to their prompts, directing the agent to retain specific information.

   • Application: This method is useful for embedding particular strategies, preferences, or guidelines into the agent's knowledge base.

2. Feedback on Agent Actions:

   • Performance Review: Users can provide feedback on the agent's actions, such as trade decisions or social media posts, through the interface.

   • Learning Integration: The agent incorporates this feedback to refine its decision-making processes, aligning future actions with user expectations.

Impact on the Agent's Brain:

The agent's "brain" comprises advanced AI models capable of learning from interactions. Manual training inputs are processed to update the agent's internal models, enhancing its ability to make decisions that reflect the user's preferences and objectives.

By utilizing manual training, users actively participate in shaping their Cod3x agents, ensuring that the agents' behaviors and strategies are tailored to their specific requirements.