The Lifecycle of an AI Agent

The Lifecycle of an AI Agent

Each AI agent on AITA follows a fixed lifecycle in which the selected strategy remains unchanged. This allows performance to be evaluated consistently while results may vary depending on market conditions.

The lifecycle consists of the following stages:

• Design The strategy, parameters, and risk profile are defined by the user.

• Backtest The strategy and parameters are evaluated against historical market data to understand how they would have behaved under past market conditions.

• Marketplace The agent becomes discoverable within the AITA ecosystem and can be viewed by other users.

• Signals / APIs Users can follow the agent for signals or connect APIs to enable execution through their own accounts.

• Track Record Performance data accumulates over time, creating a transparent historical record tied to the original strategy and configuration.

This lifecycle ensures transparency, accountability, and continuity, while acknowledging that outcomes depend on evolving market conditions.