Switch brings AI agents into the collaboration tools your team already uses. Agents join as named participants in your Slack, Teams, Discord, or Telegram channels, sharing the same context and history as your team. Connect an agent once and use it across projects. Each room carries its own context, participants, and rules. Works with Claude Code, OpenAI, Google ADK, LangChain, and more. Open source, self-hostable, running in minutes.
What's great
Really smart approach to a problem I keep running into. When you're building AI products you end up with agents scattered across different tools and nobody on the team can actually interact with them naturally. Switch puts the agent right in Slack where everyone already works. It feels like adding a new team member, not installing another tool. Setup was straightforward and I like that it's fully open source.
vs Alternatives
Honestly just building a custom bot, but that's a rabbit hole I didn't want to go down when I should be focused on my actual product. Switch saved me a lot of time there.
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Thanks @anas_chhilif! That "adding a team member, not installing another tool" framing is exactly the what we have been going for
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Really like the idea of agents becoming part of the team’s existing conversations instead of another tool people have to switch to. Congrats on the launch, Safi and team!
When an agent connector drops mid-thread, does Switch retry delivery or hand the room back to a human? Congrats on the launch btw!
@colegawin Hi there! Switch does not need retry the delivery. Upon reconnecting, the client on the agent side will tell the switch server what is the last message he has seen, and then switch will make sure to send everything that was missed to the client and agent
@lamaudruz Got it, makes a lot of sense :)
@colegawin The nice part is this happens invisibly! From the team's perspective in Slack or Discord, the agent just picks back up where it left off. Everything stays in sync automatically and the team doesn't have to do anything.
Congrats on #1 today. The "named participant with shared context" framing is what stands out - most Slack bots reset context every message so the agent never actually feels like it's in the room. Curious how conflicting instructions get resolved if two humans in the same channel give the agent contradictory asks in the same thread.
@galdayan thank you! the persistent context definitely opens things up. When it comes to conflicting instructions, the agent just has a single context window so it will see both instructions and the LLM "brain" will reason through what to do. Switch itself doesn't arbitrate. Of course, it may be that only one of these humans is allowed to instruct the agent, in which case the other human's message doesn't reach the agent as an instruction at all.
@galdayan Thanks Gal! Appreciate you checking out Switch and leaving a review. The feedback on the docs is super helpful.
Really cool product - I like it
The idea that you can bring any AI agent into the tools your team already uses without rebuilding anything is so practical.
@maria_anosova Awesome to hear that Maria! Yes, we really wanted to keep this low friction for users
Love the approach of treating agents as real channel participants. The open protocol is the right call here, really smart way to solve the last mile problem for AI agents. Congrats on the launch!
@ana_robakidze Thank you! Last mile is a good way to put it. The agents were already capable, the gap was getting them to where the work happens with the rest of the team.
@lamaudruz wrote a great blog post outlining how we got here! https://www.flintai.dev/blog-posts/our-team-is-now-composed-of-5-devs-and-45-agents-all-in-slack