Interacting With Agents
The Modus framework ensures seamless interaction with agents for end-users while providing robust tools for managing agents throughout their lifecycle. This system empowers DAOs and contributors to optimize performance, ensure economic viability, and adapt to evolving needs.
End-User Interaction with Agents
Modus makes it simple for end-users to interact with agents, whether submitting queries, accessing services, or leveraging outputs. By streamlining the process and integrating payments, users benefit from efficient and reliable AI-powered solutions.
User-Friendly Interface:
End-users access agents via the Modus frontend, which provides an intuitive platform for submitting queries or requesting services.
Transparent pricing and service options are displayed to ensure clarity.
Payment Flow:
Interactions are monetized through $MOD tokens, covering compute costs and generating revenue for the DAO.
Token payments are processed automatically, ensuring a frictionless user experience.
Agent Outputs:
Users receive detailed, actionable results tailored to their query or task, leveraging the specialized capabilities of the agents.
Follow the Workflow:
End-users can observe the agent workflow through a real-time interface that shows task delegation and collaboration among agents, fostering transparency and engagement.
Agent Lifecycle Management
Managing an agent’s lifecycle is essential to ensure its ongoing utility, efficiency, and alignment with DAO objectives. The Modus framework provides comprehensive tools for governance and performance monitoring.
Agent Onboarding:
Contributors propose new agents, specifying their capabilities, costs, and expected impact.
Governance votes approve agents for integration, with trial periods to assess performance.
Performance Monitoring:
DAOs monitor key performance indicators (KPIs), such as:
Task success rates.
Revenue generation.
Compute resource usage.
Underperforming agents are flagged for review and potential optimization.
Workflow Adjustments:
Token holders can propose and vote on modifications to agent workflows, such as:
Adjusting task priorities.
Reconfiguring interactions between agents.
Allocating additional compute resources for high-demand agents.
Agent Retirement or Replacement:
Obsolete or underperforming agents can be removed through governance votes.
Retired agents are archived in the registry for historical reference or potential reactivation.