You Don't Need Another Device

Every few months, a new startup announces dedicated AI hardware - a pendant, a pin, a standalone device designed specifically for AI interaction. The pitch is compelling: purpose-built hardware optimized for AI workflows.

The reality is less exciting. Your Mac already has everything you need.

What Apple Silicon Already Provides

Apple's M-series chips include a Neural Engine that handles ML inference efficiently. An M2 MacBook Air can run 7B parameter models locally at conversational speeds. An M4 Pro or Max handles much larger models comfortably. The unified memory architecture means the GPU and CPU share the same memory pool, which is ideal for ML workloads.

You also get a high-quality microphone, speakers for voice output, a screen for visual feedback, and direct access to all your apps and files. A dedicated device would need to replicate all of this or connect back to your Mac anyway.

The Integration Problem

Dedicated AI hardware faces a fundamental challenge: your work lives on your computer. Your files, your apps, your browser sessions, your development environment - it's all on your Mac. A separate device either needs to access all of that remotely (adding latency and complexity) or it can only handle a subset of tasks.

An AI agent running natively on your Mac has direct access to everything. It can open apps, read files, interact with the accessibility API, and respond to voice input - all without network round trips.

When Dedicated Hardware Makes Sense

There's one valid use case: always-on ambient computing. A device that's listening and available even when your laptop is closed. But for active work sessions, which is when you actually need an AI agent most, your Mac is right there. Running the agent on it directly is simpler, faster, and cheaper than adding another device to your desk.

Fazm is an open source macOS AI agent. Open source on GitHub.