If you’re searching for “ChatGPT Tasks”, you’re usually trying to do one simple thing: tell an AI to run something later (or repeatedly) without you remembering to ask.
Zo’s equivalent is an Agent: a scheduled instruction that runs on your server, with access to your files, tools, and connected apps.
What “ChatGPT Tasks” usually means (in practice)
Most “AI tasks” people want are boring-but-important repeats:
A daily briefing (calendar, email, priorities)
A weekly status report based on a folder of notes
Monitoring something on the web and alerting you when it changes
Turning a recurring workflow into a button you never have to think about
The hard part isn’t the prompt. It’s making it:
automatic (runs on a schedule)
reliable (doesn’t drift or forget the details)
grounded (reads real data: your files, webpages, calendar, etc.)
Prerequisites
A Zo Computer.
Optional: connected accounts (Google Calendar, Gmail, etc.) if your task needs them.
Step 1: Create an Agent
Open the Agents page and create a new agent with:
Schedule: when it should run (daily, weekdays, weekly, etc.)
Instruction: what to do (be precise; see templates below)
Delivery: where the output should go
Email for longer summaries you want archived
SMS for short alerts you need immediately
Files if you want durable state (for example, write a report to disk, then another workflow uses it)
Agents overview: https://docs.zocomputer.com/agents^1
Step 2: Write an instruction that’s “schedulable”
A schedulable instruction has four parts:
Inputs (what data to read)
Transformation (what to do with it)
Output format (how to structure the result)
Failure behaviour (what to do if something is missing)
Good instruction template
Every weekday at 8:00am:
Read today’s events from my primary calendar.
Summarise them in 6 bullet points max.
Identify anything that needs prep (slides, docs, agenda).
If the calendar is empty, say “No meetings today”. Deliver via email.
Bad instruction template
“Keep me organised.”
Vagueness is fine in chat. It’s a failure mode in automation.
Step 3: Pick delivery that matches the job
A simple heuristic:
If you’ll want to search it later → Email
If you need to react now → SMS
If another process should consume it → Write a file
Zo tutorial (broader): https://www.zo.computer/tutorials/how-to-automate-tasks-with-ai^2
Step 4: Start with one of these “ChatGPT Tasks” equivalents
Below are instructions you can copy into an agent (adjust times, filenames, and tone).
A) Daily calendar briefing
Every day at 7:30am:
Pull today’s meetings.
For each meeting: title, time, attendees.
Add one line of suggested prep.
End with a single “today’s focus” sentence. Deliver via email.
B) Website change monitor (with a clear threshold)
Every 6 hours:
Check the webpage: https://example.com/pricing
If the page content changed meaningfully (not just timestamps), summarise what changed.
If no meaningful change, output exactly: “No meaningful change.” Deliver via SMS.
If you need authenticated pages, Zo can use a logged-in browser session.
Tools overview: https://docs.zocomputer.com/tools-overview^3 Read a webpage (fast): https://docs.zocomputer.com/tools/read-webpage^4 View a webpage (browser mode): https://docs.zocomputer.com/tools/view-webpage^5
C) Weekly “folder digest” from your own files
Every Monday at 9:00am:
Read all markdown files in file 'Notes/Weekly' edited in the last 7 days.
Produce:
A 10-bullet summary
A “follow-ups” checklist
A list of unanswered questions
Save the output to file 'Reports/weekly-digest-YYYY-MM-DD.md'. Deliver via email.
This pattern is powerful because it forces the agent to ground itself in your own writing, not vibes.
Step 5: Make it resilient (so it keeps working next month)
Add one or two lines to handle common failure cases:
“If a linked page fails to load, retry once. If it still fails, report the error in one sentence and stop.”
“If a folder doesn’t exist, create it.”
“Never modify files outside file 'Reports'.”
Step 6: Iterate like an engineer
After the first run, treat the output like a test result:
Too long → impose explicit limits (“max 6 bullets”, “max 120 words”)
Too fluffy → require citations to the specific input used (“quote the calendar event title”, “name the file you read”)
Too slow → reduce scope (one inbox label, one folder, one page)
If you want a deeper pattern for designing agentic systems (beyond simple schedules), see: https://www.zo.computer/tutorials/how-to-build-ai-agents-without-coding^6