?? As AI agents grow more complex, debugging multi-agent workflows and ensuring post-launch observability will become critical.

Two powerful tools—Microsoft AGDebugger and AgentOPS—complement each other to provide a full lifecycle management solution for AI agents.

?? AGDebugger: Interactive Debugging for Multi-Agent Systems

Enables real-time debugging and intervention in agent conversations, allowing developers to:

?? Pause, reset, and edit agent messages mid-execution

?? Visually track agent interactions with conversation mapping

?? Test and refine workflows before deployment

?? Integrate seamlessly with Microsoft’s AutoGen framework

?? AgentOps: Observability & Monitoring for Deployed Agents

Once agents are in production, AgentOps provides deep insights into performance, errors, and costs:

?? Automatic event tracking across LLMs, tools, and actions

?? Real-time monitoring of execution logs and agent errors

?? Cost and token usage analytics for optimization

?? Multi-agent support, including AutoGen, CrewAI, and more

?? How They Work Together

● Use AGDebugger during development to interactively test and refine agent workflows.

● Deploy with confidence, knowing that the logic has been debugged.

● Monitor and optimize with AgentOps, gaining visibility into real-world agent performance.

?? Limitation:

? AGDebugger requires defining an AutoGen AgentChat team, meaning it won’t work natively with other multi-agent frameworks like CrewAI, LangChain's LangGraph, or OS-Copilot.

? AgentOps supports AutoGen natively and can be integrated with AutoGen agents using just a few lines of code

? Theoretically, one could wrap other agent systems in an AutoGen-compatible interface so that AGDebugger can process their messages.

?? DM me to get access to the feature comparison matrix.

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?? Agentic Systems are the future of AI - AI Agent Ops Framework? (AOF) Unlocks the Potential

? Join the industry's dedicated AI Agent Ops Linkedin Group: https://Linkedin.com/groups/6592276