What are the core components required to build a robust AI agent in 2026?

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. My 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. It 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