AgentSight: System-wide AI agent tracing and monitoring with eBPF (github.com)

AgentSight has introduced a revolutionary system-wide monitoring tool for AI agents that utilizes eBPF (extended Berkeley Packet Filter) technology, enabling developers to trace and analyze the behavior of AI models like Claude Code and Gemini CLI. This tool captures detailed interactions with the operating system, including process executions, file operations, and network activity, without requiring any SDK integration or modifications to the existing codebase. By performing kernel-level monitoring, AgentSight ensures comprehensive visibility and accountability, even for closed-source command-line interfaces. The significance of AgentSight lies in its ability to provide insights into the operational behavior of AI agents, filling a crucial gap left by application-level tools that often miss subprocess activities and other system-level interactions. This is especially important as AI systems grow more autonomous, necessitating robust monitoring to ensure transparency and security. With features such as live session monitoring and SQLite storage for session data, AgentSight empowers developers to better understand the dynamics of AI operations, paving the way for safer, more efficient AI deployments at scale.