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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...

326,169 Aufrufe • vor 1 Monat •via X (Twitter)

33 Kommentare

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Y Combinatorvor 1 Monat

A Cloud for Small Software @koomen Agents make it easy to build personal tools for yourself or your team. But deploying, securing, and sharing that software is still far more complicated than creating it. A cloud built for small software could remove that complexity and make bespoke tools as easy to share with a colleague as a Google Doc.

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Y Combinatorvor 1 Monat

The Future of American Defense @SecArmy Warfare is at an inflection point, and the Army is replacing the old playbook with commercially developed, modular technology that can be deployed and improved quickly. We're looking for founders building low-cost interceptors, next-generation sensors, drones, resilient logistics, advanced manufacturing, and hardware that can survive the world’s harshest environments.

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The Primer @amiklas The best education has always come from one-on-one tutoring, but that privilege has historically been reserved for very few people. AI could give every child a patient, adaptive tutor that grows with them over the years, beginning with reading, writing, and arithmetic, and eventually helping them learn to think and reason. For the first time, Neal Stephenson’s Primer is starting to feel possible.

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Y Combinatorvor 1 Monat

AI is moving into the physical world. We're excited about a new wave of startups rebuilding the systems that power the real world, from education and healthcare to defense, finance, infrastructure, and work itself.

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Compute at Sea @FrancoisChauba1 AI is running out of compute, and data centers are running out of electricity and land. One possible solution is to move compute offshore. The ocean offers abundant space, sunlight, and natural cooling, opening the door to fleets of modular data centers operating together as a global cloud.

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AI-Powered Consumer Products for a Billion People @raphaelschaad Every major platform shift creates new consumer giants. But three years into the AI era, ChatGPT is still the only new icon on most people’s home screens. As intelligence gets better and dramatically cheaper, nearly every consumer category opens up again: education, health, finance, entertainment, transportation, and how we connect with each other. Consumer is going to be so back.

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AI for the Aging Population @maxkolysh By 2030, one in five Americans will be over 65, and there are nowhere near enough caregivers to support them. AI could help older adults live safely and independently through better voice interfaces, monitoring, robotics, and tools for family caregivers. It is one of the world’s largest and most underserved markets, and it is growing every day.

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New Operating Systems for the Physical World @charliewarren Most of the global workforce does not sit at a desk, but the software used to manage physical work has barely changed in decades. The next operating systems will coordinate humans, robots, and AI agents together. The companies that build them could manage far more than software workflows. They could manage the labor itself.

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The Best Time to Build in Crypto @nemild Crypto is in a bear market, but the underlying technology is becoming more useful than ever. Stablecoins are spreading across financial institutions, tokenized assets are reshaping trading, fintech companies are quietly building on crypto rails, and AI agents may rely on them to transact. The hype may be down, but the opportunity to build is not.

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Data for the Real World @sdianahu & @_austintindle AI has become superhuman at code, language, and images because it has enormous amounts of data to learn from. But our understanding of the physical world is still limited by sparse sensors and models built largely on intuition. Cheaper sensors and better foundation models could unlock entirely new datasets for energy, agriculture, logistics, construction, and the climate. Once you can accurately model the physical world, you can begin to control it.

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Proving You’re Human @maxkolysh A finance worker recently wired $25 million after joining a video call with his CFO and colleagues. Every other person on the call was a deepfake. As voice and video become easier to fake, the internet needs a new trust layer: a private, reliable way to verify that there is a real human behind a call, message, review, or transaction.

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AI-Native Compliance Infrastructure @DaivikGoel Financial compliance still runs on spreadsheets, disconnected software, and growing teams of specialists. As companies expand into new markets, the cost and complexity of staying compliant can grow faster than the business itself. AI could monitor regulatory changes, flag anomalies, generate reports, and maintain audit trails in real time. The opportunity is not just to automate compliance work, but to rebuild the entire compliance stack around AI.

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Self-Maintaining APIs @GaddipatiHarsha APIs change constantly, but the way providers communicate those changes is still broken. Breaking updates go unnoticed, new features get buried in changelogs, and customers often find out only after something stops working. Coding agents make a better model possible. Instead of announcing a change, an API provider could find every affected use in a customer’s codebase and open the pull request itself.

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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:

Profilbild von Katja Danilina
Katja Danilinavor 1 Monat

@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!

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Sanjoy Dattavor 1 Monat

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:

Profilbild von Kiran Das
Kiran Dasvor 1 Monat

@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.

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Pablo Llanosvor 1 Monat

@aaron_epstein I am building @YappJam for this exact shift. We’re in public beta, testing how AI powered live collaboration achieves true velocity.

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Alex Bouazizvor 1 Monat

@aaron_epstein @aaron_epstein check out @get_akai you’ll love it! + we are pushing multiplayer to it’s extreme

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Harjiv Singhvor 1 Monat

@aaron_epstein We already have this deployed & working across 100+ orgs in 25 + countries.

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Victor Gardriniervor 1 Monat

@aaron_epstein @arthaud_

Profilbild von Peter D'Ambrosio
Peter D'Ambrosiovor 1 Monat

@aaron_epstein @GilboaAmitay is steps ahead

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CodeManivor 1 Monat

@aaron_epstein do you mean something like this?

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Pattern AI Labsvor 1 Monat

@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.

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Hila Shmuelvor 1 Monat

@aaron_epstein Cabinet is the AI workspace for teams of agents and human. Team collaboration and your own machine in the cloud is coming

Profilbild von Safi Qadir
Safi Qadirvor 1 Monat

@aaron_epstein @FurqanR saw this coming @NebulaAI

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Kenrickvor 1 Monat

@aaron_epstein Yep we are building this at the workspaces is shared by humans and agents alike

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James Lanevor 1 Monat

@aaron_epstein

Profilbild von Pres Mihaylov
Pres Mihaylovvor 1 Monat

@aaron_epstein hey this is exactly what ive built with

Profilbild von George Koshy
George Koshyvor 1 Monat

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.

Profilbild von Mark
Markvor 1 Monat

@aaron_epstein Oh. We’re doing this 👀

Profilbild von Lukas Andersson
Lukas Anderssonvor 1 Monat

@aaron_epstein @aaron_epstein I think you are on to something

Profilbild von Cristian Castillo
Cristian Castillovor 1 Monat

@aaron_epstein @alejandrozepe AgentDM.

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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.

Stanislas Polu

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