1 min read
Building Multi-Agent Systems with AutoGen and Azure
Instead of a single LLM handling all tasks, multi-agent systems divide work among specialized agents that communicate and coordinate to achieve goals.
Multi-Agent
9 articles
1 min read
Building AI Agents with AutoGen and Azure OpenAI
AutoGen enables building sophisticated AI systems that can decompose complex tasks and collaborate to find solutions.
1 min read
Multi-Agent Systems: Orchestrating Specialized AI Agents
Multi-agent architectures shine for tasks requiring diverse expertise: research reports, code reviews, complex analysis, and creative projects. The key is…
1 min read
Building Multi-Agent Systems with Semantic Kernel
Define clear responsibilities for each agent to avoid confusion and improve reliability. Multi-agent architectures excel at complex workflows where…
1 min read
Advanced Agent Patterns: Complex Multi-Agent Systems
Choose the right execution pattern based on task complexity and agent capabilities.
1 min read
Multi-Agent Frameworks: Orchestrating AI Agent Collaboration
Multi-agent systems unlock sophisticated automation capabilities. Start with simple patterns and evolve complexity as needed.
1 min read
CrewAI Introduction: Role-Based Multi-Agent Framework
I started experimenting with CrewAI because I wanted clearer role definitions in multi-agent workflows. CrewAI's focus on roles, goals, and agent…
1 min read
AutoGen Introduction: Microsoft's Multi-Agent Framework
I've used AutoGen to prototype multi-agent workflows that handle planning, tool use, and execution. This practical introduction focuses on the patterns that…
1 min read
Multi-Agent Systems: Orchestrating Specialized AI Agents
Complex enterprise tasks benefit from specialization. In my work, coordinating small specialist agents led to clearer reasoning, easier testing, and more…