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Multiplayer AI Aaron Epstein The best work tools became more powerful when they became multiplayer. But AI is still mostly trapped in private chats, with agents working in sessions that teammates can’t join or influence. The next generation of AI tools will let teams work with agents together in... show more
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If you’re interested in working on any of these ideas, you should apply to YC. The deadline for applying to the Fall batch is July 27th at 8pm PT:
@aaron_epstein Thank you for sharing @aaron_epstein. We are currently building @MantleChat , which is the Multiplayer AI at its core. Looking forward to applying!
I've been experiencing this exact problem with my co-founder, so we developed an internal tool to let our Claude code sessions battle it out on Google Docs while we can oversee it and edit the context live. We just open sourced it so if anyone wants to give me some feedback and try it out lmk:
@aaron_epstein @ycombinator @aaron_epstein This is exactly the gap we're building @ReloadWork to fill. A shared workspace where multiple agents and humans collaborate, handing off tasks across teams to get the real work done. Will apply for the upcoming batch.
@aaron_epstein I am building @YappJam for this exact shift. We’re in public beta, testing how AI powered live collaboration achieves true velocity.
@aaron_epstein @aaron_epstein check out @get_akai you’ll love it! + we are pushing multiplayer to it’s extreme
@aaron_epstein We already have this deployed & working across 100+ orgs in 25 + countries.
@aaron_epstein @arthaud_
@aaron_epstein @GilboaAmitay is steps ahead
@aaron_epstein do you mean something like this?
@aaron_epstein Agents working in sessions teammates can't join or influence" — this is precisely the problem we solve. AgentCall drops your agent into the meeting as a real teammate: it talks, presents, and ships work live while the whole team steers it. Multiplayer by default.
@aaron_epstein Cabinet is the AI workspace for teams of agents and human. Team collaboration and your own machine in the cloud is coming
@aaron_epstein @FurqanR saw this coming @NebulaAI
@aaron_epstein Yep we are building this at the workspaces is shared by humans and agents alike
@aaron_epstein
@aaron_epstein hey this is exactly what ive built with
We have been building aimed at operational teams. Multiplayer computers on the cloud. Anyone on the team picks up the same chats, files, and data. - Easy setup. simple UX. no workflow builders - Live datasets - join data from 3K+ SaaS apps - Reliable task automation across 1000s of work items - Browser use for anything without an API - Artifacts - build files you can share @aaron_epstein, would love you to have a look and test it out.
@aaron_epstein Oh. We’re doing this 👀
@aaron_epstein @aaron_epstein I think you are on to something
@aaron_epstein @alejandrozepe AgentDM.
![We're only year 3 of a decade (if not multi-decades) long transformation of work. 3 years ago we bet on building an horizontal platform for work with agents, a chance to invent a new operating system for companies, from scratch, with AI as a fundamental premise. Many people considered us crazy for going after that, praising verticalized AI products as the winning strategy. But here's the thing: the time horizon of tasks successfully handled by agents has been predictively increasing form minutes to hours and will in all likelihood reach the equivalent of days and weeks of human work equivalent in the coming quarters. This is were verticalized and/or single-player AI falls short. Single-player tools, one person, one agent, confined to your machine is the wrong architecture for what's coming. We're shifting from using AI to produce things, to managing fleets of agents that do the producing. 3 years ago I wrote[1]: "ChatGPT is the Pong of LLMs. [...] Imagine, one day we'll get the DOOM, Civ, Red Alert, and Counter Strike of LLMs. Let alone multiplayer modes." Weeks long tasks in companies are inherently collaborative and mechanically spanning multiple teams. The new bottleneck in harnessing agents within organizations is coordination: multiple humans and multiple agents need to work together, with shared context, shared tools, shared goals. Agents that can hand work off to other agents or surface decisions to the right person at the right time. Humans who can review, steer, and step in without losing the thread. Teams that can run parallel workstreams and actually stay aligned. This is Multiplayer AI, and that's what we've been building at Dust. Across Datadog, Clay, Persona, 1Password, Doctolib and 3,000+ organizations globally, we've watched teams figure out what this looks like in practice. 300,000+ agents deployed. 70% weekly active. 240%+ NRR. Today we're announcing a $40M Series B with Abstract, Sequoia, Snowflake, and Datadog to accelerate our vision. Designing the right interfaces for multiplayer AI is the next frontier. Join us to redefine work by defining multiplayer AI.](https://image.24vids.com/tw-2056658851588399389/amplify_video_thumb/2056658261546262528/img/ma1TE40JmZjHASb3.jpg)
