{
  "$type": "site.standard.document",
  "bskyPostRef": {
    "cid": "bafyreiakrylewnrr7chgcm3mr3ynzrcfg75yzxgbmsfyng4pjcfzomtmpe",
    "uri": "at://did:plc:pgryn3ephfd2xgft23qokfzt/app.bsky.feed.post/3mnyy5czk37z2"
  },
  "path": "/t/what-are-the-core-components-required-to-build-a-robust-ai-agent-in-2026/175643#post_4",
  "publishedAt": "2026-06-11T08:33:11.000Z",
  "site": "https://discuss.huggingface.co",
  "tags": [
    "aidenai.io",
    "AidenAI-IO/aiden-hardware-demo | DeepWiki"
  ],
  "textContent": "I guess what’s usually being omitted is the action layer. Most frameworks treat tool use as an API call, then the agent sends a request, and gets a response. That works quite well for software tools, but it breaks down when the agent needs to interact with a device or an app for instance.\n\nMy team actually has been building a physical AI agent device at Aiden (aidenai.io) that approaches this (quite) a bit differently. Instead of installing software on the host device or requiring API access, the device connects as a standard USB HID peripheral ( same protocol as a keyboard and mouse). It captures the screen via HDMI, processes full-duplex audio on-device, and sends keyboard/mouse/touch inputs back to the host. So, the host has no idea there’s an AI agent on the other end. It basically only sees a keyboard and a mouse. This sidesteps the biggest production friction for computer use agents: permissions, installs, and API negotiation. If a human can use the device, then the agent can use it too.\n\nIt is built on Luckfox Pico Zero (RV1106) with a Go-based LLM agent runtime. Full architecture at AidenAI-IO/aiden-hardware-demo | DeepWiki , more that happy to discuss the design decisions if useful",
  "title": "What are the core components required to build a robust AI agent in 2026?"
}