Letta Code

Letta Code is a memory-first coding harness, designed for long-lived agents that can learn from experience.

Instead of working in independent sessions, you work with a persisted agent whose memory is portable across models (Claude, GPT, Gemini, GLM, Kimi, and more).

Run Letta Code in the CLI, or download the desktop app for MacOS, Windows, and Linux.
You can also access Letta Code via your phone and Slack/Telegram/Discord.

Get started

Install the package via npm:

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

Navigate to your project directory and run letta (see various command-line options on the docs).

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

You can also download the desktop app for MacOS, Windows, and Linux. Agents created in the CLI are available via the desktop app, and vice versa.

Philosophy

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

Agent Memory & Learning

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:

> /init

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

> /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. You can ask your agent to learn a skill from its current trajectory with the command:

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

Read the docs to learn more about skills and skill learning.

Community maintained packages are available for Arch Linux users on the AUR:

yay -S letta-code # release
yay -S letta-code-git # nightly

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