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Workshop: Build a self-hosted cloud agent.

Ishaan Jaffer
Ishaan Jaffer
CTO, LiteLLM
LiteLLMLiteLLM← Blog

Workshop: Build a
self-hosted cloud agent.

Build and deploy with the LiteLLM team, on infrastructure your team controls.

LITELLM WORKSHOP · OCTOBER 19–30

Build a self-hosted cloud agent.

Tell us about your team and what you want to achieve. We’ll follow up to arrange a 30-minute intake. Remote, over two weeks.

Workshop signup details

* Required. We’ll use your details to arrange your workshop intake. Submitting this form does not reserve a time slot.

Remote 2 weeks October 19–30, 2026

Work with your preferred agent

Claude Code
Codex
Hermes
OpenClaw
A Slack request reaches an agent harness and sandbox in your cloud, then produces a pull request.

Introducing Microsoft 365 Copilot in LiteLLM

Yassin Kortam
Yassin Kortam
Senior SWE @ LiteLLM

LiteLLM × Microsoft 365 Copilot

Microsoft 365 Copilot is now a provider in LiteLLM. Use it from your applications to ask questions about your Microsoft 365 work data.

Users sign in with their Microsoft work account and ask questions like “Summarize my latest meeting.” Copilot answers using the data they already have permission to access.

Introducing the LiteLLM ROI Calculator

Moe Khalil
Moe Khalil
AI Product Engineer, LiteLLM

LiteLLM ROI Calculator overview: $258 of matched gateway spend compared with 78 estimated engineering hours, or $3.31 per estimated hour, above a list of merged pull requests.

Your gateway tells you what your team spends on AI. It doesn't tell you what that spend produced.

The LiteLLM ROI Calculator compares gateway spend with the engineering work your team ships. It reads spend per user from LiteLLM, estimates the effort in each merged pull request with a model you choose, and matches people by email. The result is one number: spend per estimated engineering hour.

Claude Code server-side auto mode through LiteLLM

LiteLLM Team
LiteLLM Team
LiteLLM Core Team

Last Updated: October 9, 2026

Anthropic is moving Claude Code auto mode's safety classifier from the client to the Claude API. Starting with Claude Code v2.1.278, released September 19, sessions on Enterprise plans and Claude API accounts ask the server to run those checks as part of their own model requests, and Anthropic does not charge for the checks when the server performs them. Anthropic told us the rollout started on September 18 and is gradual, beginning with the Claude Code CLI and VS Code extension and followed by the desktop app and Claude Code on the web over the following week, and that on September 25 auto mode becomes the default permission mode in Claude Code. Today the built-in default is auto on Pro, Max and Team plans and Manual on Enterprise plans and Claude API keys, the accounts that typically sit behind a gateway, per Anthropic's permission modes reference.

Server-side auto mode depends on a contract between Claude Code and the API that some gateways did not preserve, LiteLLM included. The fix first shipped in the dev release cut on Tuesday, September 22, and is now in the v1.104.0 stable release and in patch releases of earlier lines. This post explains what Claude Code needs from an AI Gateway, what LiteLLM was doing wrong, what changed, which release carries it, and how to confirm your deployment is ready.