The MiroFlow workflow is divided into five key stages:
- Intent Recognition and Query Enhancement: Use LLM to analyze user input and clarify task intent
- Planning and tasking: Master Intelligence to develop an execution plan
- Assignment to sub-intelligence: Assigning specialized tasks to domain-specific sub-intelligences
- Access to tools via MCP server: Connection Modeling Context Protocol Server Calls to External Tools
- Result synthesis and output alignment: Specialized summary process to consolidate results and ensure output quality
This layered design achieves modular processing of complex tasks and improves the reliability and scalability of the system.
This answer comes from the articleMiroFlow: a framework for building, managing and scaling AI intelligencesThe
May not be reproduced without permission:AI productivity tools " What are the key steps involved in the MiroFlow workflow?
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