How to Share Context Between ChatGPT and Claude

Separate stable context from current context

Stable context changes slowly: your role, audience, preferred answer style, technology choices and recurring constraints. Current context expires quickly: today's task, yesterday's rejected option and this morning's feedback.

Keep them separate instead of building one enormous prompt.

Stable profile

• Role and responsibilities.
• Preferred answer style.
• Usual audience.
• Constraints that apply broadly.

Project brief

• What you are making and who it serves.
• The current goal.
• Important constraints.
• Decisions already made.
• Open questions.

This makes context easier to update and safer to reuse.

Use ChatGPT memory for small, stable preferences

ChatGPT memory can carry details such as your occupation, preferred response style or a recurring constraint into later conversations. It is not a complete project archive.

Knowing that you use React is different from knowing why you rejected another approach last week. Review what you expect ChatGPT to remember, remove stale facts and keep detailed project history outside the memory feature. See the guide to reducing repeated setup in ChatGPT.

Give Claude the same brief

When moving to Claude, paste the current project brief instead of recreating it from memory. A useful opening contains:

1. The project brief.
2. Relevant decision history.
3. The request for this conversation.

For a pricing-page review, that could mean the audience, product position and agreed pricing model; rejected alternatives and their reasons; then the specific review request. This keeps the conversation from returning to already-considered ideas while leaving room for a reasoned challenge.

Keep sources beside decisions

A decision log without evidence becomes difficult to trust. Keep the article, competitor page, customer message or document that informed each important choice.

You do not need every source in every conversation. If Claude is reviewing onboarding, include the onboarding brief and relevant feedback, not unrelated pricing research.

A notes app, document folder or dEssence can keep material outside one AI platform. dEssence lets you save references and ask for them later. Whichever system you choose, the important point is that the record is not trapped in one chat.

Build the smallest useful context packet

Use this structure:

Project: One paragraph describing the work.

Current goal: The outcome required from this conversation.

Constraints: Requirements the answer must respect.

Decisions: Accepted choices with short reasons.

References: Relevant notes, links or excerpts.

Request: One clear action.

Update the packet after meaningful work. If ChatGPT helps choose an onboarding sequence, add the decision before moving to Claude. If Claude identifies a risk, record it before returning to ChatGPT.

Understand the platform boundaries

A new chat can begin cold. ChatGPT memory is better suited to sticky-note facts than multi-conversation reasoning. Claude Projects can use pinned project documents, but conclusions still need to be added to those documents. Gemini can draw on connected Google material, but a decision made elsewhere—such as Slack or an external article—may remain outside that view.

A useful shared record therefore includes your stack, constraints, accepted and rejected decisions, preferences and active projects, regardless of which model you open next.

The goal is control, not perfect memory

Do not ask ChatGPT or Claude to remember your whole history. Give each tool the right context for the current task while you maintain the record that connects them.

This also prevents repetitive founder-style introductions such as the same market, stack, constraints and rejected vendors at the start of every chat. The durable fix is a maintained layer for those facts and decisions, not a longer improvised introduction.