If you’ve searched “how to build an AI agent” or “how to create AI agents”, most guides assume you’ll write code, wire up APIs, and host infrastructure.
On Zo Computer, you can build useful AI agents with plain English. An agent is just an instruction + a schedule + a place to put the output.
This tutorial shows how to build a practical agent end-to-end, without coding.
What you’ll build
A scheduled agent that:
runs every morning
summarises the top items on Hacker News
emails you the results
Once you’ve built one agent, you can reuse the same pattern for anything: monitoring a webpage, drafting daily notes, preparing meeting briefs, and more.
Prerequisites
A Zo Computer account
A destination for the output (email or SMS)
Step 1: Create a new agent
Open the Agents page in Zo and create a new scheduled agent.
You’ll set:
Schedule: when it should run (for example, every day at 8:00am)
Instruction: what it should do
If you want your AI to run a reusable workflow you’ve saved, your instruction can simply be “Run prompt …”.
Step 2: Write an instruction that actually works
Most agent failures are just ambiguous instructions.
A good instruction has:
Goal — what success looks like
Inputs — what to read (webpages, files, calendars, etc.)
Output format — bullets, table, a short email, etc.
Where to save/send — file path, email, or SMS
Here’s a solid starting instruction for this tutorial:
Every morning, read the Hacker News front page and pick the 10 most interesting items for someone who builds software. For each item: include title, link, and a 1–2 sentence summary. Then email me the list.
Keep it short, but specific.
Step 3: Choose your delivery method (email vs files)
You have three common patterns:
Email: best for daily digests and summaries you want pushed to you
SMS: best for short alerts
Files: best when you want persistent state, or another agent will use the output later
For more examples of “file-based agents”, see the tutorial on automating tasks with AI.
Step 4: Test the agent once (before scheduling it)
Before you let something run unattended, do a dry run:
run it once manually
check the output quality
tighten the instruction until it’s reliably good
If the output is too long, constrain it (for example: “keep it under 200 words” or “exactly 10 bullets”). If it’s too vague, add a rubric (for example: “bias toward new developer tools, infra, and AI”).
Step 5: Make it robust (so it keeps working)
A few small instruction tweaks make agents much more reliable:
Be explicit about links: “Always include the URL.”
Bound the work: “Process at most 10 items.”
Prevent spam: “If nothing noteworthy, send a 1-sentence email saying ‘no updates’.”
Avoid hallucinated sources: “Only summarise links you actually fetched.”
Step 6: Save your instruction as a reusable prompt (optional)
If you find yourself iterating on an instruction, save it as a prompt so you can reuse it and version it.
Then your agent instruction becomes stable and short:
Run
prompt Prompts/daily-news-digest.prompt.md.
Step 7: Iterate: upgrade from “digest” to “workflow”
Once you can build one no-code AI agent, you can combine tools and apps into larger workflows. Examples:
meeting prep: pull today’s calendar and write briefs
monitoring: check a webpage and alert you if a phrase appears
content: draft a daily status update from a notes file
If you want a more general pattern (and more examples), see:
https://www.zo.computer/tutorials/how-to-automate-tasks-with-ai
https://docs.zocomputer.com/agents
Summary
You now have a repeatable template for how to build an AI agent without coding:
create an agent
write a precise instruction
choose delivery (email/SMS/files)
test once, then schedule
iterate and extract prompts for reuse