Show HN: Agent Multiplexer – manage Claude Code via tmux (github.com)

Agent Multiplexer (amux) has been introduced as a tool to streamline the management of multiple Claude Code agents via tmux, enabling these agents to run in parallel without user intervention. This innovative solution captures session snapshots every 60 seconds, automatically handling issues like low context (below 20%), session crashes, and input waiting times. By injecting environmental variables and providing a shared global memory file, amux allows agents to coordinate tasks seamlessly without requiring explicit programming. This tool is significant for the AI/ML community as it enhances the operational efficiency of complex AI workflows, fostering better coordination among agents. The self-healing capabilities, orchestration, and ease of access through a minimalist code base (a single Python file) empower developers to manage extensive AI tasks with reduced overhead. The integration of a built-in kanban board, automatic task claiming, and seamless session linking further positions amux as a comprehensive framework for orchestrating AI processes, making it a valuable asset for developers seeking to leverage Claude Code's potential in distributed environments.