How I Manage Global Context Across Claude, Codex, and Other AI Tools

If you use multiple AI tools like Claude, Codex, Cursor, and others, one problem shows up very quickly.

None of them naturally share the same context.

Each system can be useful on its own, but your actual context ends up scattered across chats, random project files, temporary notes, and half-written documents. One tool knows one part, another tool knows something else, and after some time you start repeating the same background again and again.

I wanted to fix that.

So this is the simple workflow I use to manage context across my AI tools:

The core idea is simple.

Instead of treating every AI system as a separate brain, I make them all work around the same knowledge base.

For me, Obsidian was the right choice because it stays very close to plain files. The notes are just .md files, which means they are easy to search, easy to edit, easy to version, and easy to move. On top of that, Obsidian gives a very good graph view, which makes it easier to understand how ideas, projects, and notes are connected.

Obsidian has its own paid sync, but I did not need that. I used GitHub for syncing instead. That gave me version control, backup, and a simple way to keep everything in one place without locking myself into a separate sync product.

The note app is only one part of the workflow though.

The more important part is the shared rule layer.

For Claude, I keep instructions in CLAUDE.md. For Codex, I keep them in config.toml under developer instructions. The idea is the same in both places:

That one decision changed the workflow a lot.

Now if I am working on a codebase, learning a new concept, debugging something painful, or refining an idea, I can save the useful part into the same place. It can be:

This matters because the main benefit is not note-taking.

The main benefit is persistent context.

Once the useful information is stored in one place, every AI tool can work with much better context about what I care about, how I work, and what I have already learned. Instead of starting from scratch every time, the tools can build on top of the same growing context.

Earlier, my notes were scattered across random repositories, local files, chats, and unfinished documents. Now I have one place for project context, technical notes, ideas, workflows, and personal learnings.

That also makes the whole workflow portable. The notes are still just Markdown. I can read them without Obsidian, sync them with GitHub, search them easily, and keep full ownership of the data.

So the workflow is simple, but the effect is big:

For me, this has been one of the simplest and most effective ways to manage shared context across AI systems without making the workflow complicated.

If you use multiple AI tools, I think maintaining one common context layer is much better than letting each tool live in its own isolated context.