DEDUPED Hot AI repos, turned into use cases Get 5 a day

How to resume a project on another machine with the same memory with AI Memory

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

Credentials. Setup creates a bearer token for the server, so keep that token file owner-only and do not share it between people.

Who it is forA developer who works on the same repository from a desktop, a laptop, and a homelab box and loses context when switching.

The problemAgent notes stay on one machine, so the open questions from the desktop session are missing on the laptop.

The outcomeThe laptop agent retrieves the same project knowledge and open questions recorded on the desktop.

What you need first

  • 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

Steps

  1. Run curl -fsSL https://github.com/akitaonrails/ai-memory/releases/latest/download/install.sh | sh on the server and on each machine
  2. Run ai-memory setup on each machine and point it at your server
  3. Work on the project on the first machine until a session ends
  4. On the second machine, start the agent in the same project and check that the brief lists the earlier open questions

Prompt for your agent

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.

Caveat. The README describes the server setup in general terms only, so the exact configuration for a remote server is not covered in the README excerpt and needs the docs.

Share: X LinkedIn Hacker News Email Copy link

Disclaimer

Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked "Seen in the wild", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email [email protected] and we will look at it promptly. Full disclaimer page