Application of AI Agents
Last updated
Last updated
Building upon the foundation of , QuantDAO's team plans to actively deploy multi-modal AI agents to assist in making data-driven decision making. As these agents, whether introduced by the team or contributed by DAO members or other third parties, act as autonomous systems designed to enhance decision-making processes. This can allow the organization more advanced and specific modeling scenarios, enabling the DAO to dynamically adapt to ever-changing market conditions.
For example, Agents that are well trained to emphasize the paradigms of QuantDAO can be helpful in continuously and actively making asset suggestions prior to and during voting eras, such as giving alerts or suggesting the of assets.
Informed Governance
Members can rely on precise, autonomously data-backed recommendations, improving the quality and consistency of decisions in real-time.
Efficiency
Automated analysis and conclusions can be retrieved or requested on-demand enabling faster and more agile participation (ie, "Agent, does $TOKEN_A still make sense for the DAO in the current market and regulatory landscape after event X?").
Scalability
As the DAO grows, AI agents handle increasing complexity, ensuring governance remains effective even as more moving parts within the protocol must be considered (such as in the case of effects).
For example, in a scenario where a relatively high-risk investment is proposed, these agents could evaluate historical performance of similar assets, simulate potential outcomes, and generate a detailed risk-reward profile, maintaining appropriate risk tolerance.
