Discussion: AI Agent Observability and Developer Experience

Title: Why your CLI Agents need more than just a Terminal Output As we shift from simple LLM completions to complex agentic workflows like Claude Code and Aider, we’re hitting a new bottleneck: observability. When an agent executes a multi-step plan, tracking the 'why' behind a specific file change through a scrolling terminal is inefficient. We are essentially moving back to a 'print-statement' era of debugging. To build more reliable autonomous systems, we need tools that can visualize these execution paths in real-time. I’ve been experimenting with an 'Agent Flow Visualizer' that parses CLI output to generate logic maps. This allows developers to spot infinite loops or logic errors at a glance. How are you all tracking the internal state of your local AI agents? Is terminal logging enough, or do we need a dedicated visual UI for agentic logic?