How to Make ChatGPT and Claude Work Together on One Task

Make ChatGPT and Claude work together by assigning one a draft and the other a specific review, then passing a checked handoff between them. Give both the same current instructions and sources; two open chat windows do not by themselves create a shared work record.

You can copy the relevant material manually or use an outside record such as fenbs that supported AI apps can read and update. The essential part is agreeing what is current, who acts next, and which choices still need a person.

What is the simplest useful two-assistant workflow?

1. Write one task description: desired result, audience, source material, constraints, and what counts as finished.
2. Ask the first assistant for a draft against those requirements. Tell it to identify assumptions and unfinished checks.
3. Give the second assistant the same task description, the draft, and a focused review request. Ask for evidence and specific corrections rather than a general rating.
4. Review the disagreements yourself. Approve the direction or ask for more evidence, then give one assistant responsibility for the revision.
5. Check the revised result against the original requirements and save the outcome, verification, and next step.

Say you are preparing a customer onboarding guide. One assistant drafts the instructions from your product notes. The other checks whether a new user can follow the sequence, whether each promise is supported, and where the wording contradicts those notes. You decide which changes to accept.

The value comes from a different job description, not from an assumption that one brand always writes better or reasons better. Try the assignment in either direction. If the second pass adds little, use one assistant and spend the saved effort on checking the source material.

How should you divide the jobs?

Name one active owner of the next output. “Both improve the guide” invites competing versions. “ChatGPT drafts the steps; Claude lists unsupported claims; I approve changes; ChatGPT revises the master draft” establishes an order that you can follow and audit.

Give the reviewer limits too. It can flag a possible policy conflict without rewriting the policy, and identify an unverified claim without declaring it false. Those distinctions prevent a review from quietly taking over decisions that belong to the person responsible for the work.

For choosing between the apps, read Claude versus ChatGPT; for improving the assignment itself, see ChatGPT prompts for work. This workflow starts after you have chosen to use both.

What context must travel with every pass?

Pass the task, the current output, and the reason for the next pass. Include the approved constraints and the sources that establish them. A reviewer who receives only the draft may criticize a deliberate choice because it never saw the client’s requirement.

• Goal: what the result must help the reader or user do.
• Current version: the named draft or file that should receive revisions.
• Decisions: what a person approved, with the reason when it affects review.
• Evidence: approved source documents and the limits of what was checked.
• Next action: one request, with clear boundaries and any waiting approval.

Do not carry every exchange forward by default. A rejected title from the first chat may be irrelevant; the rule that the guide cannot promise same-day setup is essential. Keep the handoff short enough to review, while retaining references to the longer material when the reviewer needs it.

fenbs keeps these current facts with the project, so the next assistant can read the same project context before working. It does not make ChatGPT and Claude share their private chats or personal memories.

Can both apps use the same outside tools?

They can when each app supports the connection and you authorize it separately. MCP, a standard way for an AI app to use an outside tool, is one route. Anthropic documents remote custom connectors↗ (opens in a new tab), and OpenAI documents connecting a custom MCP server↗ (opens in a new tab).

Follow the current setup for your account and organization. Connecting a tool in Claude does not connect it in ChatGPT, and permission to read a record is different from permission to change it. Start with a small read request and confirm that each assistant reaches the intended project before asking either to write.

You can still use the draft-and-review routine if you cannot connect either app. Copy a reviewed handoff yourself and maintain one master result. For the differences between the apps’ project containers, see Claude projects versus ChatGPT projects, rather than assuming those containers synchronize.

How do you handle disagreements without creating a loop?

Ask each assistant to name the claim, its evidence, and the consequence of being wrong. A disagreement about a documented product behavior can be checked against the product source. A disagreement about tone needs a person’s choice or an agreed style example.

Do not bounce the whole answer back and forth until the wording converges. The second assistant may repeat an error from the first, and agreement is not independent verification. Give the revision one owner and a finite list of accepted changes, then test against the requirements again.

For example, if both assistants say an onboarding step is automatic, check the product’s actual behavior. If it requires approval, change the guide and record that fact. An apparently polished consensus is less useful than one checked correction with a clear source.

How to do this with fenbs

1. Create a free account and add a project for one real deliverable, such as the onboarding guide.
2. Add a task with the draft, review, and revision steps in its plan. Record the person-approved requirements in Decisions and rules.
3. Connect both apps using the guides on Integrations, signing in through the browser and approving the access you intend to give.
4. Ask the drafting assistant to read the project context first. After drafting, save progress with the version, sources, and questions for the reviewer.
5. Ask the reviewing assistant to read that checkpoint and the task. Decide which changes to accept, then save the revised state and the next action in Where we left off.

fenbs does not run a hidden conversation between the two models or automatically import their histories. For an occasional second opinion, manual copying can be enough. Use the shared record when you repeatedly hand active work between sessions, assistants, or teammates.

Start with one draft and one review, then check whether the second pass caught something useful. The AI handoffs topic offers more ways to make that transition repeatable. A successful first setup ends with an improved deliverable and an accurate next step.