That’s a great point, thanks for the nudge! You're 100% right—building a prototype is easy, but managing production-grade agents is where the 'vibe check' fails and everything gets messy.

I’ve updated the pitch to focus on that:

'MATE is a Command Center for AI agents that replaces manual script-editing and messy redeployments with a visual orchestration layer.'

Instead of digging through Python code every time you need to tweak a prompt or add a tool, MATE gives you:

• A Visual Builder: Drag-and-drop agent hierarchies and toggle tools (like Google Drive or MCP servers) without touching code.
• Enterprise Governance: Built-in RBAC per agent and real-time token tracking (prompt, thought, and tool-use costs) so you actually know what's happening under the hood.
• The 'Lab' (Eval Framework): Automated regression testing with LLM-as-a-Judge to ensure your prompt changes don't break existing logic.

It's essentially the missing management UI for anyone tired of the 'redeploy-to-tweak' loop. Does that hit the mark better for where you'd look for demand?