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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...

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301,655 görüntüleme • 8 gün önce •via X (Twitter)

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we've been quietly building type. today we're sharing it with the world. type is the first multiplayer ai product for marketing, sales, support, coding, and much more. create ai teammates that work with all your tools and everyone at your company.
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we've been quietly building type. today we're sharing it with the world. type is the first multiplayer ai product for marketing, sales, support, coding, and much more. create ai teammates that work with all your tools and everyone at your company.

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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.
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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.

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Introducing Hamster 🐹 Multiplayer AI for product teams. Hunch in, PR out. Design, engineering, product, & business reason on the same work, and your agents deliver it. Your team makes a hundred decisions a week. Now your AI remembers all of them.

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Today we’re shipping new capabilities that make Resolve AI the platform where engineering teams run and fix production software with AI agents. New capabilities include background agents that run operational tasks, new agent architecture that delivers 2x investigation quality, new agent capabilities like governed actions, and new ways to work with agents in UI or terminal. With Resolve AI engineering teams can: - Delegate on-call to agents - Co-work with agents to resolve incidents - Run operational tasks with background agents.

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.Aaron Levie says AI agents may take years to diffuse from engineering into the rest of knowledge work. "The models are really good at code, and the work is verifiable." "You have 5 or 10 things that make agents work in an enterprise context for engineering." "The users are less technical, the data is much more fragmented, the systems are much more legacy." "That's why it's going to be a number of years for this diffusion to roll from what we're seeing in Silicon Valley, into the rest of knowledge work."
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.Aaron Levie says AI agents may take years to diffuse from engineering into the rest of knowledge work. "The models are really good at code, and the work is verifiable." "You have 5 or 10 things that make agents work in an enterprise context for engineering." "The users are less technical, the data is much more fragmented, the systems are much more legacy." "That's why it's going to be a number of years for this diffusion to roll from what we're seeing in Silicon Valley, into the rest of knowledge work."

MTS

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LAUNCH OF in 12 HOURS. Get excited!!! freemium of the most powerful AI agent is coming, for the first 2000 people we will keep giving you free daily credits until we spend $1mm. is a multiplayer AI brain — an AI workspace that finally knows you, does the proactive work you shouldn't have to do yourself, and leaves you with the parts that need a human: taste, review, and responsibility for what gets sent. For teams it becomes hive mind with permissioning and delegated access.
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LAUNCH OF in 12 HOURS. Get excited!!! freemium of the most powerful AI agent is coming, for the first 2000 people we will keep giving you free daily credits until we spend $1mm. is a multiplayer AI brain — an AI workspace that finally knows you, does the proactive work you shouldn't have to do yourself, and leaves you with the parts that need a human: taste, review, and responsibility for what gets sent. For teams it becomes hive mind with permissioning and delegated access.

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1:52

Here we go again 🚀! Excited to announce that we're building A1Zap (YC W25) with Pennie Li and that we're in the Y Combinator W25 batch in San Francisco! What is A1Base? A1Base gives AI Agents a real world identity for work. We do that by rebuilding Twilio and Okta from the ground up, putting AI Agents first. This means developers can make AI-first agentic applications 10x easier with our API's. ⁉️ Why are we doing this? Because there's a huge torrent of new valuable companies possible with AI agents, but to get their AI Agents to users, they have to chain custom apps, chat interfaces, awkward Slack integrations, browser bots, and wrestle with Twilio’s legacy API (which is built for marketing). We solve this by providing developers with an easy to use API to interface your AI agent with humans/coworkers/users where they are in this case in Whatsapp, Slack, Teams, SMS and more) - with AI Agent features built in. These digital workers are poised to transform how we work and we're the critical infrastructure to help them interact naturally in human workflows. We're not just building another AI tool. We're creating the infrastructure that will enable AI agents to become a natural part of the workforce - handling everything from customer support to sales development to creative work. We're backed by Y Combinator and working with founding teams who share our vision. We believe that in the near future, AI Agents with human coworkers will enable us to pursue more creative and impactful work. Our mission is to help developers build AI Agents that people can partner with and rely on as trusted allies—always with a human-first mindset. If you're thinking about the Agentic future of your company reach out! If you're looking to build your first AI Agentic company - reach out too - we have some amazing open source templates to get you started on the journey. Excited to share more of what we're up to soon 🔜.

Pasha Rayan

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We’re launching Judgment Labs today and announcing $32M in funding. As AI agents take on more of the work that creates economic value, they generate massive amounts of production data: the clearest record of how they behave with users, software, and the real world. Judgment builds infrastructure for improving AI agents from production data.
2:00

We’re launching Judgment Labs today and announcing $32M in funding. As AI agents take on more of the work that creates economic value, they generate massive amounts of production data: the clearest record of how they behave with users, software, and the real world. Judgment builds infrastructure for improving AI agents from production data.

Alex Shan

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At Notion, we believe every business deserves powerful & beautiful tools. AI is the most important technology of this era. It shouldn't only belong to companies that have AI teams or can afford forward deployed engineers. Today we're launching Custom Agents: — The first multiplayer agents built for business. — No coding. Minutes to set up. Hosted in the cloud. — Run autonomously 24/7 with all your business apps. — Switch between the best LLMs (usually the same day they're released). — One person builds it, the whole company benefits. Rolling out for Business and Enterprise customers today. The AI era should leave no one behind 👌
1:54

At Notion, we believe every business deserves powerful & beautiful tools. AI is the most important technology of this era. It shouldn't only belong to companies that have AI teams or can afford forward deployed engineers. Today we're launching Custom Agents: — The first multiplayer agents built for business. — No coding. Minutes to set up. Hosted in the cloud. — Run autonomously 24/7 with all your business apps. — Switch between the best LLMs (usually the same day they're released). — One person builds it, the whole company benefits. Rolling out for Business and Enterprise customers today. The AI era should leave no one behind 👌

Ivan Zhao

148,245 görüntüleme • 5 ay önce

Can AI agents automate all work? What happens to white collar jobs? I sat down with Aaron Levie (Aaron Levie), Founder and CEO of to talk about agents, deploying AI, the future of white collar jobs, the future of SaaS, and so much more. 0:00 Intro 1:02 AI at Box 2:59 New tools 5:26 Embracing AI at Box 8:13 Using AI to do more 11:09 White collar collapse? 14:51 How does demand scale? 19:29 Managing AI 25:51 Companies with too much power 29:58 Personal vs Work agents 35:37 What if AI makes a big mistake? 41:23 Who will own the agents? 43:37 SaaS is dead 48:40 Future of the web 57:23 Using AI on socials
59:27

Can AI agents automate all work? What happens to white collar jobs? I sat down with Aaron Levie (Aaron Levie), Founder and CEO of to talk about agents, deploying AI, the future of white collar jobs, the future of SaaS, and so much more. 0:00 Intro 1:02 AI at Box 2:59 New tools 5:26 Embracing AI at Box 8:13 Using AI to do more 11:09 White collar collapse? 14:51 How does demand scale? 19:29 Managing AI 25:51 Companies with too much power 29:58 Personal vs Work agents 35:37 What if AI makes a big mistake? 41:23 Who will own the agents? 43:37 SaaS is dead 48:40 Future of the web 57:23 Using AI on socials

Matthew Berman

91,581 görüntüleme • 1 yıl önce