Building an AI Support Team Multi Agent Systems, Roles & Workflow Orchestration Explained class 3

Description

“Multi-Agent AI Architecture: From Roles to Real-World Deployment” “Designing Collaborative AI Agents for Customer Support” “Step-by-Step Guide to Multi-Agent Systems in AI Workflows” “How to Orchestrate AI Agents for Seamless Customer Support” “End-to-End Deployment of AI Support Teams Using MAS” Introduction to Multi-Agent Systems (MAS) Definition of MAS Importance in AI and customer support Real-world applications Understanding Multi-Agent Architecture What is multi-agent architecture Types of architectures (centralized, decentralized, hybrid) Components of an architecture Defining Roles in MAS Role-based design Example roles in a customer support AI team Role assignment strategies Task System Orchestration How tasks are assigned and coordinated Workflow management for AI agents Handling dependencies and conflicts Designing Specialized Agents How to design agents with expertise Natural language processing, recommendation engines, and monitoring agents Learning and adaptation in specialized agents Deploying an AI Support Team End-to-End Integration with existing systems Real-time communication and collaboration among agents Monitoring, feedback loops, and continuous improvement Challenges and Best Practices Scalability, reliability, and security Ensuring ethical AI behavior Metrics for measuring team success Future of MAS in Customer Support Trends and innovations Impact of generative AI and autonomous agents Conclusion Recap of MAS, roles, orchestration, specialized agents, and deployment Call to action / next steps