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What you can do with AI Memory

ai-memory is a Rust tool that gives AI coding agents a shared long-term memory, stored as a git-backed markdown wiki, so work can be handed off between agent CLIs and machines.

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akitaonrails/ai-memory on GitHub

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What do you want to do?

4 use cases

  • Hand off a half-finished task from Claude Code to Codex

    Quit one coding agent mid-task and resume in another in the same directory with the open questions intact.

    View prompt
    Using the ai-memory repo (github.com/akitaonrails/ai-memory), set up the tool, then start <target-agent> in the project at <project-path> through `ai-memory run`. Expected output: the new agent begins with a brief that lists the last session's status, failed approaches, and open questions. Verify the brief mentions the open questions from the previous session before continuing.

  • Resume a project on another machine with the same memory

    Run memory on a server you control so a project started on a desktop continues on a laptop.

    View prompt
    Using the ai-memory repo (github.com/akitaonrails/ai-memory), configure a second machine to use the memory server at <server-address>. Expected output: the agent on the second machine shows knowledge from sessions recorded on the first machine. Verify by asking for the open questions of the project and confirming they match the first machine.

  • Share project knowledge across a team on one server

    Point the whole team at one AI Memory server so each person's agents can retrieve shared project notes.

    View prompt
    Using the ai-memory repo (github.com/akitaonrails/ai-memory), set up a shared memory server for <team-name> and create one personal key per member. Expected output: each member's agent can search the shared project pages. Verify by searching for a known project fact from a second member's account.

  • Read and edit agent memory as plain markdown files

    Open the project's memory wiki in any text editor or Obsidian and correct it by hand.

    View prompt
    Using the ai-memory repo (github.com/akitaonrails/ai-memory), locate the markdown wiki for the project at <project-path>. Expected output: a list of .md page files that hold the project memory. Verify by opening one page and confirming its content matches a recent session summary.

How to use AI Memory

  1. Check you have what it needs: A Linux or macOS machine (native Windows is experimental; WSL2 is supported); At least one supported coding agent CLI installed, such as Claude Code or Codex; A terminal with curl and sh available.
  2. Open akitaonrails/ai-memory on GitHub and read the README and license.
  3. Run curl -fsSL https://github.com/akitaonrails/ai-memory/releases/latest/download/install.sh | sh
  4. Run ai-memory setup
  5. Quit Claude Code in the project directory
  6. Run ai-memory run codex from the same directory

These steps come from our top use case, Hand off a half-finished task from Claude Code to Codex, which also has a copy-paste agent prompt.

AI Memory alternatives · Best AI repos for Software and DevOps

About this repo

Requirements

  • A Linux or macOS machine (native Windows is experimental; WSL2 is supported)
  • At least one supported coding agent CLI installed, such as Claude Code or Codex
  • A terminal with curl and sh available
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Questions about AI Memory

What is AI Memory?

ai-memory is a Rust tool that gives AI coding agents a shared long-term memory, stored as a git-backed markdown wiki, so work can be handed off between agent CLIs and machines. It is an open-source project on GitHub: https://github.com/akitaonrails/ai-memory.

Who is AI Memory for?

Developers who switch between AI coding agents or machines and want the next agent to resume without re-explaining the project.

What can I do with AI Memory?

4 use cases so far, for example: Hand off a half-finished task from Claude Code to Codex; Resume a project on another machine with the same memory; Share project knowledge across a team on one server. Each has steps and a copy-paste agent prompt.

What do I need to run AI Memory?

A Linux or macOS machine (native Windows is experimental; WSL2 is supported); At least one supported coding agent CLI installed, such as Claude Code or Codex; A terminal with curl and sh available.

What are alternatives to AI Memory?

Other hot AI repos in Software and DevOps: Harness2, iFixAi, Orca, Diagram Design, Graphify.

Is AI Memory safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.