They spent months building what's now fully open-source.
Anthropic recently put Claude inside Slack, where you can tag it in a channel. It reads the thread, breaks the task into steps, and posts the result back.
The problem is that it only runs Claude and only in the channels Anthropic supports.
Running your own agent there is harder.
The reasoning, tool calls, and state management are mostly handled by the framework. Connecting that agent to a messaging platform is not.
Moreover, each platform has a different integration:
- Slack renders messages with Block Kit - Teams uses Adaptive Cards - and each has its own SDK, auth flow, and delivery model.
If an agent needs to run on three platforms, one must write three separate integrations against the same agent logic.
That overhead explains why most custom agents never get deployed to Slack, and why the ones that do are usually a single vendor's hosted assistant.
The alternative is to keep the agent in one place and add a per-platform adapter that translates its output into each platform's native format.
The agent is written once, and each channel requires just another output target instead of a separate build.
CopilotKit open-sourced this full implementation in the Channels SDK.
Essentially, any agent that implements AG-UI can run in a messaging platform in a few lines of code, like Slack, Teams, Discord, WhatsApp, and many more.
Because the agent runs inside the thread, it has that conversation's context, so it can summarize the discussion, open a ticket, or route to the right person.
It works with any backend, so LangGraph, CrewAI, Mastra, Google ADK, or a plain HTTP agent can connect through an existing endpoint.
The same message can render as a Block Kit in Slack and as Adaptive Cards in Teams.
In practice, the model and orchestration stay the same; it requires no migration or rewrite.
It also handles human-in-the-loop approvals, persistence, and transcripts that carry state across platforms, so a thread started in Teams can continue in Slack.
CopilotKit is open-source, and AG-UI is supported across every major agent framework, including LangGraph, CrewAI, Mastra, and Google ADK.
Pretty-ts-errors is a VSCode extension that reformats TypeScript's nested type errors into readable, human-friendly messages.
- Syntax highlighting that matches your theme, for both light and dark modes - Buttons to jump to the relevant type declaration or get a plain-English explanation - Supports React, Solid, Qwik, Astro, Svelte, Vue, and JSDoc type errors - Works with Node and Deno TypeScript error reporters
Runs hundreds of large models on a single GPU by loading them from SSD to VRAM up to 10x faster than alternative loaders, achieving coldstarts under 2 seconds.