Building a personal AI ecosystem across a smart mirror, laptop and portable mini-robot, what is possible with the OpenAI API?

API Feedback
1

Hi everyone,
I’m exploring an idea for a personal AI ecosystem and I’m trying to understand what is currently possible with the OpenAI API before I start building.
The idea isn’t to create several separate AI products. I want to build one personal assistant that can exist across multiple devices, with each device serving a different purpose.
For example, I imagine:
A smart mirror at home that I can talk to in the morning, which knows my schedule, the weather and my wardrobe and can suggest what to wear.
The assistant interacting with things around the house, such as a coffee machine.
A very small portable AI device/mini robot that I could carry in my bag or even like a keychain. I could talk to it naturally, and it could communicate with my laptop or other devices.
If I’m away from home and suddenly remember that I need to finish some code or send an email, I could tell my mini-robot and have it trigger an authorised action on my laptop.
If I’m a few minutes away from home, I could ask it to prepare something for my arrival, such as interacting with my smart home or ordering something.
So the basic vision is:
One AI assistant → multiple physical interfaces → authorised actions in the digital and physical world.
I’m particularly interested in whether the same assistant could maintain its identity, memory and context across all these devices. I don’t want the mirror, phone, laptop and robot to feel like completely separate assistants.
I have a few main questions:

  1. Architecture:
    Would you normally have each device communicate independently with OpenAI, or have one central backend that connects the different devices to the AI?
  2. Actions & security:
    What is the recommended way to let an AI securely perform authorised actions on a laptop or smart-home devices? My ideal model would be:
    AI decides what action is needed → permission layer verifies it → authorised device performs it.
  3. Voice & hardware:
    For a small custom robot, what is currently the recommended approach for natural, real-time voice conversation with the OpenAI API?
  4. Memory & cost:
    How would you handle persistent memory/context across devices, and how would you keep API costs manageable for something that is intended to be available throughout the day?
    A little context about me: I’m not a developer, software engineer, or hardware engineer. I’m a product designer fascinated by smart homes and AI interacting with the physical world. I expect to build prototypes with the help of AI tools and, where necessary, engineers I can find to work with me.
    So I’d really appreciate answers in relatively simple language. I want technically accurate answers, but please don’t assume I already understand software architecture or engineering terminology. If you use a technical term, a short explanation would be very helpful.
    I’m thinking of starting with something much smaller—a smart mirror prototype—and potentially expanding from there.
    I’d especially love to hear from people who have built custom hardware, voice agents, multi-device assistants, or OpenAI integrations.
    Thanks!
2

This is actually a pretty interesting idea, and I think it’s very doable with the OpenAI API. I’d probably avoid making each device its own separate assistant. Instead, have one central backend that all the devices connect to, so the mirror, laptop, and robot can share the same context and memory.

The devices can basically act as different interfaces the mirror for visual/voice interaction, the laptop for more advanced tasks, and the robot for a physical/portable experience.

The main thing I’d pay attention to is permissions. I wouldn’t let the AI directly control everything on your devices. Put a layer in between that decides what the AI is actually allowed to do, especially for things like sending emails, accessing files, or controlling smart-home devices.

I’d start with the mirror first and get the voice, memory, and tool integration working reliably. Once that foundation is solid, connecting the laptop and robot should be much easier.