Can Codex Use What You Told ChatGPT?
Same vendor, separate memory - unless you own the layer
You've spent months in ChatGPT working out how you build — your stack, your conventions, the way you like code explained. Then you open Codex CLI in your terminal to actually ship something, and it knows none of it. Same account, same OpenAI, and you're still re-explaining yourself from scratch.
It feels like these two should already talk to each other. They don't.
Can Codex see what you told ChatGPT?
No — not natively, even though both are OpenAI products. ChatGPT's memory is scoped to ChatGPT. Codex CLI runs in your terminal as a separate tool with its own session, and nothing in OpenAI's stack pipes your ChatGPT memory across to it. Being on the same account doesn't change that.
The reason is structural, not a missing feature. Platform memory is built to deepen a single product, not to travel between them — the memory a tool accumulates about you is part of what keeps you in that tool. memory built in one never transfers to another. That holds even inside one company's product line: ChatGPT and Codex are different surfaces, and the memory doesn't follow you from one to the other.
So the picture that should be seamless isn't. Large language models have no built-in memory — they process what's in the conversation and forget it when the session ends. Platforms have bolted on memory features, which help, but they're reactive, start empty, and stay locked to one platform. Codex opens cold every time, and the context you built up in ChatGPT stays where you left it.
What actually works — one shared layer both connect to
The fix is to stop relying on either tool to remember you and give both the same source to read from. A shared context layer sits outside ChatGPT and Codex, holds your context once, and connects to each over MCP — the open standard both tools speak.
This is a real shift for developers. The cold-start problem is having to re-establish your context every time you open an AI tool, because the model starts each session knowing nothing about you. It happens because LLMs are stateless and platform memory is shallow and siloed. A shared layer starts every session warm instead — the tool changes, the context behind it doesn't.
And because Codex CLI and ChatGPT both connect over MCP, the layer works in both directions. You're not exporting a snapshot from one and pasting it into the other. Both tools read your context at session start, and both can save context back into the vault. Work out an approach in ChatGPT, save it, and Codex has it in the terminal. Solve something in Codex, save it back, and ChatGPT reflects it next time. One vault, two tools, no clipboard.
That two-way loop is what separates a shared layer from a one-time migration. Importing ChatGPT memory into another tool is a snapshot taken once — accurate the day you do it, stale the day after. A shared layer both tools connect to stays current because both are reading from and writing to the same place.
How to set it up
The practical setup uses Unabyss as the shared layer both tools connect to. It's an MCP-native context vault: connect your sources once, and any MCP-compatible tool — ChatGPT and Codex CLI included — reads your context automatically and can save new context back.
- Build your vault once. Connect your real sources — GitHub, Notion, email — and Unabyss extracts a structured profile in under 90 seconds. This is your context, owned by you, not locked in either OpenAI product.
- Connect ChatGPT over MCP. ChatGPT reads your context at the start of a conversation and, with a custom instruction to save what matters, writes new context back to the vault.
- Connect Codex CLI over MCP. Point Codex at the same vault. It loads your stack, conventions, and current work before you type — and saves back what you work out in the terminal.
- Automate save-back (optional). Add a standing instruction in each tool to store notable decisions in Unabyss, so the loop closes without you thinking about it.
For the full cross-tool walkthrough, see How to Share Memory Across All Your AI Tools.
Once both are connected, the wall between the chat and the terminal is gone. What you told ChatGPT, Codex can use — and what you work out in Codex, ChatGPT inherits.
Set up your shared context layer with Unabyss →
