Show HN: Process Mining for AI Agent Systems

As AI agents become more complex and are increasingly deployed locally, understanding their execution patterns and debugging their behavior becomes critical. AgentFlow provides process mining capabilities specifically designed for agent systems, allowing developers to visualize and analyze the flow of multi-step agent operations in real-time.

This is particularly valuable for local LLM deployments where you need to trace agent decision-making, identify bottlenecks, and optimize agent-to-tool interactions without sending execution traces to external services. AgentFlow on GitHub enables full visibility into how your agents are performing and behaving.

For practitioners building sophisticated local agent systems using tools like LangChain or LlamaIndex with local models, having comprehensive observability is essential for production reliability. AgentFlow's process mining approach provides insights that go beyond simple logging, helping you understand not just what happened, but why.

Source: Hacker News · Relevance: 7/10