Founders and executives
Turn decisions, research and recurring reviews into consistent deliverables without losing judgment or source traceability.
Turn one recurring knowledge-work task into a reviewed work product. Define the decision, approved sources, action boundary, verifier and handoff before you start.
This ChatGPT Work tutorial is for a reviewed business deliverable, not a generic chat. Start with one outcome, approved sources, an action boundary and a named verifier. Workspace plans, apps and permissions vary, so confirm the available controls in your account before relying on them.
A detailed guide for turning ChatGPT Work into a dependable operating system for knowledge work.
No spam. Just the tutorial and useful follow-ups.
Who this is for
Turn decisions, research and recurring reviews into consistent deliverables without losing judgment or source traceability.
Build projects, briefs, research loops, documents and spreadsheets around the actual work you repeat every week.
Plan a governed rollout across workspaces, roles, groups, apps, connectors, agents and data boundaries.
Inside the tutorial
Capture the raw request, then state the audience, decision, sources, format and review owner.
Separate durable project instructions, source files, working chats and final outputs so context stays useful.
Use apps and connectors with an explicit permission model, source list and fallback when a connection is unavailable.
Combine prompts, files, documents, spreadsheets, slides, browser work and long-running tasks into an observable loop.
For recurring work, define material updates, cadence, source boundary, owner and a stop condition before scheduling it.
Keep citations, assumptions, change logs, owners and approval steps visible in the final deliverable.
The operating loop
Turn the raw request into a decision, audience, inputs, output format and risk level.
Put the right sources and instructions in the right project or app boundary.
Let ChatGPT Work draft, analyze or structure the work while you control external actions and material updates.
Review the sources, factual claims, format and stop condition before sharing or automating the output.
Teams and enterprise
This is not a solo productivity checklist. The guide includes the operating decisions an admin and a team lead need before company data, apps or shared agents enter the workflow.
Map workspace owners, admins, members, analytics viewers, groups and role-based access to the work people actually need to do.
Review which apps are enabled, how connectors and custom MCP apps are governed, and where read/write actions require explicit approval.
Start with one repeatable workflow, define quality and privacy checks, train reviewers, then expand only when the evidence supports it.
It is the work-oriented set of ChatGPT surfaces and workflows: Projects, files, apps, browser/cloud work and repeatable task patterns. Check current availability in your workspace.
Yes. The tutorial treats permissions, app allowlists, read/write boundaries and human approval as design inputs.
Yes. It includes workspace governance, roles, groups, apps, custom MCP and rollout questions, with links to OpenAI’s current admin documentation.
No. Prompts are included, but the main asset is the source, permission and review architecture around them.
Choose one recurring decision, define the finished artifact, list the approved sources, state the action boundary and name the person who will accept the result.

Created by Iwo Szapar
Iwo builds AI operating systems for founders, operators and teams. The emphasis is on useful context, careful permissions and outputs people can act on.
Get the tutorial, pick one recurring workflow and turn it into a reviewable system your team can improve.
Open the full tutorial