ToolExperimental

Multi-AI-Agent-Systems-with-crewAI

Name: Multi-AI-Agent-Systems-with-crewAI
Rating: 3.0 (166 reviews)
Author: akj2018

by akj2018

Notebook demos for multi-agent workflows using crewAI agents

Jupyter Notebook

Updated May 24, 2024

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Overview

Demonstrates building multi-agent workflows using crewAI agents to automate multi-step business tasks. Uses role-specific autonomous agents that hand off subtasks and coordinate via a notebook-driven orchestration pattern. Includes practical examples like resume tailoring, website design, and customer support flows to show agent delegation and chaining. This approach aligns with the agent-service mesh pattern.

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Why It Matters

As agents delegate work to one another, you need reproducible patterns for coordination and handoffs to spot failure modes and measure reliability. This notebook-style framework surfaces orchestration and delegation patterns that are the first step toward collecting agent interaction logs and track records. Until trust and A2A evaluation tooling are widespread, concrete examples like these make agent-to-agent evaluation and reputation engineering actionable. See how emergence-aware monitoring can help observe these interactions: Emergence-Aware Monitoring Pattern.

Best For

Practitioners prototyping multi-step agent pipelines who want hands-on examples of role-based delegation and orchestration with crewAI. See the Tool Use Pattern for practical integration approaches. For patterns on how to manage and register agents within a system, consider the Agent Registry Pattern.