Stage 3: Expand + Master Plan — Voice-First Agent Architecture

**1. The unified router eliminates the triple-classifier problem.** Three intent classifiers with incompatible taxonomies is the root cause of inconsistent voice behavior across devices. One server-side router, shared by all clients, fixes this permanently. The ~55 merged intents cover all existing use cases. **2. Mac Ear Daemon is the single biggest UX improvement.** Eliminating the phone dependency for voice interaction changes the relationship with the mesh. Walk to the desk, say "status", get a spoken briefing. No phone required. mlx-whisper on M2 handles transcription locally with no API cost. **3. Voice memory closes the biggest persistence gap.** Every other interaction channel (text prompts, Discord, code, Obsidian) is persisted. Voice isn't. Storing transcripts in Supabase + RAG++ means "we discussed this earlier" works across modalities. This is a force multiplier for the entire knowledge system. **4. The ElevenLabs integration is already production-ready.** Voice ID configured, API key active, streaming playback works in iOS. Extending this to Mac1 TTS is ~20 lines of Python (HTTP POST + audio playback). **1. Whisper on Mac1 competes for compute.** Mac1 is already running: 7 LaunchAgents, Xcode builds, SSH tunnels, the pane orchestrator, and terminal Claude sessions. Adding continuous audio capture + Whisper inference adds CPU/memory pressure.