The mental model that makes everything else on Zo make sense, and the first three things to do. This is an on-ramp, not documentation. For mechanics, the official docs are the source of truth: https://docs.zocomputer.com/llms.txt
The mental model: your own server, your files, your AI
Most AI products are a chat window attached to someone else's computer. Zo flips that. Zo is your computer: a real, always-on server in the cloud that belongs to you, with an AI that lives on it and works for you.
Three pieces, and the relationships between them are the whole model:
1. Your server. A persistent Linux machine that stays on when you close the tab. It can run programs, host websites, serve APIs, and execute scheduled work at 3am while you sleep. Anything a normal server can do, yours can do.
2. Your files. A real filesystem that persists forever. Notes, code, data, documents. This matters more than it sounds: files are how your AI remembers. A chat conversation evaporates; a file stays. People who get good at Zo quickly learn to ask the AI to write things down: project notes, decisions, instructions for next time. Your file system becomes a long-term memory that every future conversation can draw on.
3. Your AI. An assistant with hands. It does not just answer questions about your server and files; it operates them. It can write and run code, create and edit files, build a website and host it, set up a recurring job, connect to your other accounts. You describe outcomes; it does the work on your machine.
Put together: you own a computer that an AI can operate, and everything you build accumulates there. Day 30 builds on day 1, because it is all still on the machine.
A few words you will see immediately, in one line each (the docs cover all of them properly):
- Skill: a saved procedure your AI can perform on request.
- Automation: work that runs on a schedule without you asking.
- Site: web pages your server hosts for the world.
- Service: a program that runs continuously on your server.
- Persona: a configured version of your AI with its own instructions and access.
When to use which is a judgment call, and we have a whole guide for it: Skill vs Automation vs Site vs Service.
Make it yours: two setup steps
Two settings decide how Zo feels day to day and what it costs, and both are worth doing before you build anything. The exact buttons live in the official Zo docs (https://docs.zocomputer.com/llms.txt); here is what they are and why they matter.
Bring your own subscription. This is the setting that changes the economics, and the one most people miss before deciding Zo is "too expensive." By default the AI runs on metered Zo credits. Instead, you can point Zo at a plan you already pay for: connect your Claude or ChatGPT (Codex) subscription, or bring your own provider API key (Anthropic, OpenAI, OpenRouter, and others). Model usage then bills against that plan, not Zo credits. If you already pay for Claude or ChatGPT, do this first. It lives in Settings, under AI and then Providers, with a Bring Your Own Key area for raw API keys.
Connect a way to talk to it. Zo is most useful when you can reach it from your pocket, not just the web app. Start with SMS: connect your phone number and you can text your AI like a person and get answers anywhere. That is the primary channel, and the one to set up first. If you live in another app, Zo also connects to Telegram, Discord, and Slack; treat those as secondary and add whichever one you already use. All of them live in Settings, under Channels.
The first three things to do
Do these in order. Each one teaches you a layer of the model by using it.
1. Give it your context
The highest-leverage first move is to tell Zo who you are, in a file it can reread in every future conversation. Create one:
"Create a folder called
contextand inside it writeabout-me.md: who I am, what I'm working on right now, the people and projects that come up often, and how I like you to work with me. Ask me questions first, then write the file."
Then open the file it made. This teaches the most important lesson on day one: the output of a conversation can be a durable thing on your machine, not just text in a chat, and a file about you is memory every later session can draw on.
Keep it as a living document, not a one-time dump. A strong personal context file grows a few parts over time: who you are and what you do, what you are building now, the people and organizations that recur, and your preferences for how the AI should communicate and work. Later, each individual project gets its own briefing file too, the same idea scoped to the project; the Classified Method guide goes deep on that. From here on, end work sessions with "write down what we decided in the right file."
2. Connect one integration you actually use
Pick the one account you touch daily, usually email or calendar, and connect it. Then ask for something useful:
"Look at my calendar for this week and write a plain-English summary of where my time is going."
This teaches the second lesson: Zo is more useful the more of your real life it can reach. You do not need to connect everything on day one. One real integration doing one real job beats ten connected and idle.
3. Schedule one small automation
Take something you would want every day or every week and put it on a schedule:
"Every weekday at 8am my time, check my calendar and email, and send me a short morning brief."
Say "my time" and name your timezone. Scheduling has sharp edges around timezones, and you will care about them eventually: Automations That Fire.
This teaches the third lesson: your computer works when you are not there. That is the moment Zo stops feeling like a chatbot and starts feeling like staff.
Where to go next
- Mechanics, settings, how anything on the platform works: the official Zo docs, starting at https://docs.zocomputer.com/llms.txt
- How to think about building bigger things: The Classified Method
- Stuck: ask Friday, or post in #help-and-support.