Our multi-agent system starts with a supervisor agent that orchestrates tasks, understands user intentions, and delegates to specialized sub-agents, ensuring high accuracy and reliability.

Companies are focusing on workflows and multi-agent systems to mimic human decision-making processes in AI.

In healthcare, multi-agent orchestrators can significantly improve productivity and reduce costs by streamlining complex workflows.

AI agents can navigate multiple systems, understand context, and execute tasks that previously required human intervention, marking a significant shift in back-office operations.

An agent is something a human can delegate tasks to, and we're aiming for agents to handle more complex tasks over time.

Manus operates as a multi-agent AI system, coordinating a team of sub-agents to complete various tasks, from travel planning to financial analysis, rather than relying on a single neural network.

The distinction between workflows and agents is crucial; workflows are pre-orchestrated by code, while agents operate more autonomously and can adapt their actions based on the situation.

AI agents are being developed to automate workflows, such as filling out construction permit applications, but they still face skepticism regarding their reliability in enterprise settings.

The technology behind this AI agent is a multi-agent system that utilizes a core react-like loop and various tools to assist users in coding tasks.