A supervisor/orchestrator agent that listens to user chat, routes the conversation to the appropriate tool, and then calls the chosen agent.
This agent is a building-block base pattern agent that takes user chat conversations and initiates any approprioate sub-agents.
It starts with a user chat conversation.
The 'Agent Router' examines the conversation history using an LLM call. It analyzes both the previous messages and the latest user input to decide which specialized tool should handle the request: 'Agent 1', 'Agent N', or, if no agent is a good match, 'General User Input'.
When one of the sub-agents (such as 'Agent 1' or 'Agent N') is called, it executes its domain-specific processing with its capabilities. Each sub-agent focuses on handling a particular category of queries, ensuring that the response is precise and efficiently processed.
For cases where the input does not clearly indicate a specialized need that the sub-agents can handle, the 'general user input' is utilized. This handles general questions and provides a response that may also include a brief overview of available tools.
After the selected sub-agent has processed the request, the workflow concludes.
You care about improving the entire lifecycle of buyer and customer journeys. And you want inspiration for areas where Ai may help.
You want inspiration for real-world ways to help people as you're building your Ai product.
You're focused on the stage in your daily job and want to find ways for Ai to help you do more with less.
Does this AI agent workflow rely too much on AI and not enough on human know-how? Or the reverse? Is it missing steps or tools?
Note that this Ai workflow is presented as inspiration for what's possible. Adjust the amount, type and quality of the data inputs. Adjust how much or how little your human team mates (or you), AI and fully autonomous agents contribute.
And test it! Learn what works and what doesn't.
Don't forget! In the end, it's not just about efficiency. It's about delivering great experiences for your customers and customers-to-be.
You are a routing assistant. Analyze the current conversation and choose one of the following routes based on the user's query: agent_1, agent_n, or general_user_input.
You are an AI assistant. If the user asks what you can do, describe the available tools. Otherwise, respond directly to the query in a clear and friendly manner.
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