boxBot: An Open-Source Smart Speaker Powered by Claude and Hailo AI
A developer known as FunScore645 built boxBot, a smart speaker that uses Claude for agent-driven hardware control instead of rigid rules. The project is open-sourced at github.com/dv-hart/boxbot and is still a work in progress but already useful for daily family tasks.
Hardware and Build
The hardware stack includes:
- Raspberry Pi (model not specified)
- Hailo AI accelerator (for edge inference, presumably)
- Respeaker microphone array
- Raspberry Pi camera
- Waveshare display
- Speakers
The enclosure is handcrafted from walnut, with passive cooling—the developer used Claude to calculate thermal loads and dissipation rates for the design.
Agent-Driven Architecture
Instead of complex conversation rules, the agent (likely Claude-based) controls the hardware directly through a custom Python SDK. Key capabilities:
- Dynamic muting: The agent decides when to mute the mic to ignore background noise or side conversations.
- Barge-in handling: Agent-driven logic manages interruptions without explicit rules.
- Multi-channel response: Can reply via voice or WhatsApp, chosen by the agent.
- Widget-based display: The screen uses a JSON widget framework—the agent reads and manipulates widgets via JSON without screenshots.
Skill System and Flexibility
The agent uses a small set of tools, with most logic routed through Python scripts and the boxBot SDK. Skills are defined in Markdown files. Example: when the developer added a family calendar event, his wife wanted a text notification. He added one line in a .md file, and the agent updated the calendar skill to send a WhatsApp message automatically on new events.
Memory and Security
The developer mentions a custom memory system and security considerations (camera+mic in a living room) but deferred details to comments. The agent is tightly coupled with hardware for security.
Who It's For
Developers interested in building AI-driven hardware projects with agent-controlled peripherals and open-source foundations.
📖 Read the full source: r/ClaudeAI
👀 See Also
Local 35B MoE Model Drops Agent OS Code Failure Rate to 0%
A developer reports that switching a multi-agent system's runtime to Qwen 3.6 35B A3B (MoE, 3B active params) eliminated code failures, achieving 100% success rate through a 5-layer validation gate.
Ninetails Memory Engine V4.5: Int8 Quantization + LRU Cache Cuts Local MCP Memory to 60MB
The Ninetails Memory Engine V4.5 uses Int8 scalar quantization and LRU cache eviction to reduce vector storage from 6KB to 1.5KB per embedding, keeping the entire engine at 40-60MB RAM. It combines 70% vector similarity with 30% BM25 search in a fully local SQLite implementation.
Claude Code skill combines DeepMind Aletheia and Anthropic harness approaches
A Claude Code skill implements a Planner→Generator→Evaluator→Reviser pipeline that synthesizes DeepMind's Aletheia math research agent with Anthropic's multi-agent coding architecture, adding blind pre-analysis where the evaluator reasons about correct approaches before seeing candidate code.
ComfyUI Skill Enables AI Agents to Queue and Batch Image Renders via Natural Language
A new open-source skill allows OpenClaw agents to construct ComfyUI workflows, submit jobs, and manage renders through natural language commands like 'Make 50 variations of this concept with different seeds' or 'Compare these 4 prompts side by side at 1024x1024'.