GuidesBy featureTeams looking at Dots, Agents API, plugins, Pages, meetings, team tasks or Codex without wanting to hand over the whole business

Turn OpenAI DevDay into one safe workflow trial

For teams looking at Dots, Agents API, plugins, Pages, meetings, team tasks or Codex without wanting to hand over the whole business.

3 min read
6 steps
1 prompt to copy

The 2-minute version

Use it when A launch drops dozens of new AI surfaces at once: always-on agents, API agents with computer use, plugin panels, shared spaces, pages, meeting notes, team tasks and faster models. You need a useful trial by Friday, not a shopping list.

Turns a repeated trigger, like a meeting, support request, project board item or code diff, into a first draft or routing recommendation
Keeps related work in a shared surface such as a Page, Space or project context instead of scattering it across chats
Classifies or routes simple cases when the acceptable answers are finite and written down first
Prepares a review pack that shows sources, assumptions, missing information and the proposed next action

In short

What this helps you do: OpenAI's DevDay 2026 announcements make AI feel like a workplace layer, not just a chat box. The safe move is to pick one workflow, define the human approval step, and test whether the new surface really reduces work before you roll it out.
What you leave with: A repeatable workflow and a starter prompt you can adapt to your own work.
What to check before trusting it: You choose one workflow instead of trying every announcement at once

Ask Bit to set up this workflow

Best fit today: ChatGPT.Our read of the reviewed tool guides, not tested by us. Reviewed 29 September 2026. Open a tool guide for what each one does with this kind of work.

Workflow

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Pick one repeated job with a clear before and after, such as meeting notes to actions, project-board item to draft plan, source pack to a brief, code diff to risk list, or customer request to routing decision
Write the acceptance check first: what must be true before a person accepts the result
List the data the AI may use, the tools it may touch and the actions it must never take without approval
Run the first version on non-sensitive material or a copied workspace, and keep the approval step visible
Score the result on accepted output, corrections needed, source errors, privacy issues and time saved
Only then choose the surface: Dots for ongoing responsibility, Agents API for product workflows, Decisions API for finite routing, plugins or Sites for connected app work, Pages or Space for shared deliverables, and Codex for code review or implementation work

Prompt to try

Use it, adapt it, and make it your own.

Prompt

I want to trial one OpenAI DevDay workflow safely. The job is [real repeated job]. The source material is [approved sources]. The output must be [accepted artefact]. Before you suggest tools, write the acceptance checklist, the human approval step, what data must not be used, and what actions must stop for approval. Then suggest the simplest workflow using only the new OpenAI surface if it genuinely helps.

Ask Bit to adapt it

Human lens

You choose one workflow instead of trying every announcement at once
You define what the AI may prepare and what still waits for approval
You check source fidelity, privacy, permissions and anything that would be hard to undo
You decide whether the saved time is worth the new review surface

What to avoid

Do not treat launch-day availability as proof your plan, region or workspace admin settings support the feature
Do not let an always-on agent send, publish, spend, delete, change permissions or update production without a human checkpoint
Do not use a new shared space as a dumping ground: decide what source is authoritative before AI starts organising it
Do not measure success by whether the demo looked impressive; measure accepted work and correction time

Related guides

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Using deep research without trusting it blindly

Deep research modes read many sources and return a longer, cited answer. They are powerful for a first pass, and they still need you to check the sources and the reasoning.

Letting an assistant take multiple steps on its own

Agentic modes plan a task, take a sequence of actions such as browsing, running code or editing files, and check their own progress along the way. They can save real time on chores with several steps, and they can also wander off course, so you set the boundaries and check the outcome.

Using projects to keep AI in context, not starting over

Projects or workspaces let you gather files, instructions and past chats in one place, so the assistant carries the right context into every new conversation instead of you repeating it each time.

Reviewed 29 September 2026