From answering to acting
An AI assistant answers a question or prepares a plan. A financial agent can also use tools to act toward a defined task. The difference is the ability to execute within an authorized scope, not simply the use of an AI model.
A price explanation, an order draft and a running trading agent are three different outputs. Knowing which one you requested is the first step to using the tool effectively.
The scope makes the job concrete
An agent needs a task, the information needed to evaluate it and permission to take a particular action. In trading, that means defining the assets, triggers, allocation and relevant execution limits.
A broad instruction such as “make money” leaves the important choices undefined. A strategy with a budget, clear conditions and review points is easier to inspect and operate.
How TRUE uses agents
TRUE combines market research with trading workflows and Agent Studio. Rule-based strategies specify triggers, actions and guardrails. Autopilot uses a risk profile and allocated capital.
Through MCP, a compatible assistant can create a draft agent. Funding, activation and the session permit are completed in TRUE. This keeps preparing a strategy distinct from authorizing it to trade.
Evaluate the behavior
Inspect the configuration and execution log. Check whether actions match the defined task, whether costs change the result and whether the original reason for the strategy still holds.
You can pause an agent to stop new positions, then review existing exposure separately. The practical value of agentic finance is that defined work can continue without repeating each instruction manually, while the scope remains something you can inspect and change.