Collection · 11 use cases
From OpenAI's own examples
The jobs OpenAI uses to explain dots, as paste-ready prompts. Official prompts are word for word; the rest are adapted and labeled.
OpenAI’s announcement and learn docs describe what dots are for through a handful of concrete jobs. We collected the ones that make a complete, repeatable job in one place. Where OpenAI published a full prompt, it’s here word for word. Where it described the job in a sentence, we wrote the prompt and marked it as adapted.
Why start here. These are the jobs OpenAI chose to show, so they line up with what dots are designed to do today: keep a responsibility current, follow a source, and bring decisions back to you. Every entry names the official page it came from, so you can read OpenAI’s own description before you paste.
Two official prompts first. The offsite prompt and the weekday check-in are copied exactly from OpenAI’s learn docs. Try those before the adapted ones: they show the pattern OpenAI recommends, with a clear scope, drafts before sends, and a request to confirm any schedule.
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Keep an offsite on track
Hand your dot the plan and venue emails; it tracks decisions, deadlines and open questions, and drafts replies for you to send.
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Weekday planning check-in
Each weekday morning your dot reads a planning channel, updates the list, and messages you only when a deadline or decision needs you.
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Compare venues on a budget
Your dot compares three venues on capacity, travel, dates and full price, keeps the total under your cap, and books nothing.
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Keep a sales proposal current
Your dot keeps a working copy of a proposal in step with the latest emails and call notes, and shows you every change and its source.
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Content kit from an interview
Share an interview and your dot returns a kit: exact quotes, a summary, post drafts, a newsletter blurb and claims to fact-check.
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Keep launch materials aligned
Your dot checks landing copy, FAQ and sales material against the product spec and lists every mismatch with a suggested fix.
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Update a study as results arrive
When new results land, your dot updates a copy of the study, reruns the summary numbers, and notes what changed for each finding.
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Fix reported bugs for review
Your dot works through bug reports, reproduces each one in Codex, and opens a draft pull request with the fix for you to review.
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Watch Slack for bug reports
When a new bug report lands in a Slack channel, your dot investigates it and prepares a fix for your review, without posting in the channel.
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Catch forgotten invoices
Your dot matches delivered work against invoices you've sent and drafts the missing ones. Nothing goes to a client until you approve it.
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Route updates by channel
Routine progress stays in ChatGPT; decisions, risks and approvals reach you in Slack with the options and a deadline.