syncing-memory-filesystem

Install the package via [npm](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm):

```bash

npm install -g @letta-ai/letta-code

```

Navigate to your project directory and run letta (see various command-line options [on the docs](https://docs.letta.com/letta-code/commands)).

Run /connect to configure your own LLM API keys (OpenAI, Anthropic, etc.), and use /model to swap models.

> [!NOTE]

> By default, Letta Code will to connect to the [Letta API](https://app.letta.com/). Use /connect to use your own LLM API keys and coding plans (Codex, zAI, Minimax) for free. Set LETTA_BASE_URL to connect to an external [Docker server](https://docs.letta.com/letta-code/docker).

Letta Code is built around long-lived agents that persist across sessions and improve with use. Rather than working in independent sessions, each session is tied to a persisted agent that learns.

Claude Code / Codex / Gemini CLI (Session-Based)

• Sessions are independent
• No learning between sessions
• Context = messages in the current session + AGENTS.md
• Relationship: Every conversation is like meeting a new contractor

Letta Code (Agent-Based)

• Same agent across sessions
• Persistent memory and learning over time
• /clear starts a new conversation (aka "thread" or "session"), but memory persists
• Relationship: Like having a coworker or mentee that learns and remembers

If you’re using Letta Code for the first time, you will likely want to run the /init command to initialize the agent’s memory system:

```bash

> /init

```

Over time, the agent will update its memory as it learns. To actively guide your agents memory, you can use the /remember command:

```bash

> /remember [optional instructions on what to remember]

```

Letta Code works with skills (reusable modules that teach your agent new capabilities in a .skills directory), but additionally supports [skill learning](https://www.letta.com/blog/skill-learning). You can ask your agent to learn a skill from it's current trajectory with the command:

```bash

> /skill [optional instructions on what skill to learn]

```

Read the docs to learn more about [skills and skill learning](https://docs.letta.com/letta-code/skills).

Community maintained packages are available for Arch Linux users on the [AUR](https://aur.archlinux.org/packages/letta-code):

```bash

yay -S letta-code # release

yay -S letta-code-git # nightly

```

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