Shared memory for AI coding agents aims to reduce repeated setup
AKASHA is a project that lets such as Cursor use one shared private memory. The goal is to avoid explaining the same preferences, working style, project habits, and useful skills every time a new chat or starts. The setup is presented as a single instruction: tell the AI tool to configure itself from the project on GitHub.
The public core is offered as a service, while each person’s own memory is described as private and visible only to them. The system focuses on storing personal style and rapport, reusing skills from past projects, loading only the skills needed for the current task, and onboarding a new AI tool with one short chat instruction.
Key points
- AKASHA is meant to give Cursor and similar one shared private memory.
- It tries to remove repeated setup across new chats and new .
- The proposed setup starts with one instruction pointing the AI tool to on GitHub.
- It can store personal working style and reuse skills from past projects.
- The project says the public core is shared, but each person’s own memory stays private.