New Letta Office Hours is up.
This week: @just_cameron is back, Letta Code harness mods, Windows fixes, Slack channel controls, Signal progress, local mode, and schedules improvements.
This clip covers the update segment before our colleague Caren joins for the mods demo + the
Come join our Office Hours livestream at 11:30am Pacific!
@just_cameron is back and ready to show off some of the amazing work the Letta team has done over the past few weeks.
Join us on Discord, link below 👇
I used the tutor and now all I do is ask Letta to do stuff all day. Night and day difference from codex because Letta *understands my culture by having not only long term memory, but an excellent way to update it*.
It's like having continual learning - check it out:
You can now create a "Tutor" agent in Letta.
Tutor walks you through how Letta works while learning your needs and tracking your progress. It proactively demos features - and explains how they work as it goes.
You can also ask Tutor to configure channels, schedules, skills, and
You can now create a "Tutor" agent in Letta.
Tutor walks you through how Letta works while learning your needs and tracking your progress. It proactively demos features - and explains how they work as it goes.
You can also ask Tutor to configure channels, schedules, skills, and
amazing onboarding! i'm SO excited for this. model agnostic, local-first but mobile friendly, and memory capable sounds like the ideal agent harness. thanks!
Letta Code now supports Opus 4.8!
We find that Opus 4.8 has comparable context management capabilities to Opus 4.7 (e.g. skill use and filesystem use), but with better token efficiency.
Opus 4.8 achieves the lowest violation rate across any model for adherence to the Context Constitution, suggesting better alignment and improved ability to drive long-lived agents that curate and value memory.
Letta Code can now run **fully locally** with an embedded server - no login or Docker required
Memory is stored locally, but can be synced to GitHub with `/memory-repository`
Now includes builtin support for local LLMs (@ollama@lmstudio) through pi-ai from @badlogicgames