Office Hours are today! Come join the livestream at 11:30am Pacific.
New stuff:
- Cloud sandboxes are now persistent -- one per agent
- GitHub integration -- clone repositories into an agent's cloud sandbox
- Schedule management on Letta Chat
- GPT 5.6/Grok 4.5 support
Link
Our already very smart support agent just got smarter (running on GPT 5.6 sol)
I also love how you can ask @Letta_AI agents to reconfigure themselves - like reducing the max context size.
The distributed agent era is here.
Run agents programmatically on cloud sandboxes or any registered remote (running `letta server`).
Memory & context moves with agents across machines.
Letta Agent is the easiest way to add persistent, digital coworkers to your team. Each agent:
- is teachable and customizable
- never forgets
- works with your whole team (not just you)
- runs locally & on remote machines
Available on MacOS/Linux/Windows
2/ Works where you work
Bring your agent to where your team works.
Chat with the same agent on Discord, Slack, Telegram, or through custom channels - just like you would a human coworker.
3/ Model Agnostic + BYOK
Connect your existing ChatGPT subscription or LLM API keys. Port your agent (including all its configuration and state) to the latest model release.
Letta Agent is the easiest way to add persistent, digital coworkers to your team. Each agent:
- is teachable and customizable
- never forgets
- works with your whole team (not just you)
- runs locally & on remote machines
Available on MacOS/Linux/Windows
1/ Learning & memory
Each agent becomes unique through its own experience, and what you & your team teach it.
As you work with your Letta Agent, it will rewrite its skills, prompts, and other reference files (e.g. a wiki) over time.
Mods in Letta are pretty cool - agents can self-expand their capabilities.
Today, I had our fully local finance agent (running on @Railway) install a mod to support web search with @ExaAILabs -- all via slack
Agents are now very good at writing code. Agents are also composed of code (the harness). This means that agents can self-adapt through rewriting their harness - now supported in Letta Code through *mods*.
Mods are very similar to extensions in @badlogicgames's Pi harness. You
Agents can now not only rewrite their memory, but also rewrite the execution code they run in (the harness) through Mods.
Mods (inspired by Pi's extension system) allow for harness-level changes like:
- modifying context
- injecting custom tools
- customizing the statusline
Harness is memory.
My current running example: "please use uv not pip".
This can get written into system-level memory (context-as-memory), or if the agent has access to mutate its own harness, it can be written into a pre-tool use hook (block commands w/ pip).
Agents can now not only rewrite their memory, but also rewrite the execution code they run in (the harness) through Mods.
Mods (inspired by Pi's extension system) allow for harness-level changes like:
- modifying context
- injecting custom tools
- customizing the statusline
Agents can now not only rewrite their memory, but also rewrite the execution code they run in (the harness) through Mods.
Mods (inspired by Pi's extension system) allow for harness-level changes like:
- modifying context
- injecting custom tools
- customizing the statusline
External mods can also be installed through npm or git with: `letta install <source>`
We're listing community and official mods at letta.com/agent/mods/
