Dust

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.

Most AI at work is still single-player. The gains stay trapped with each individual. Nothing compounds across the team. Today, we're announcing @DustHQ $40M Series B to scale multiplayer AI: humans and agents working in parallel, with shared context, shared tools, and shared goals. 🧵

What should designers produce to help teams decide faster? We've been running an experiment at Dust. Field report by our very own @duncid: dust.tt/blog/field-stu…

Engineering Night: London Edition 🇬🇧 Mondays just got better. We're bringing Engineering Night to the UK on Feb 23, and yes, it's on a Monday. 👀 We may be biased, but spending your Monday night with cool people, learning how to ship better agents, and eating pizza sounds like a pretty great way to start the week. Victoria Klein from Agentica and our very own Jules Belveze are sharing the real, technical details of shipping AI agents. Not what might work someday. What's working now. Then the important stuff: Q&A, pizza, drinks, talking shop with people who actually build this stuff. PSA: Our events fill up fast, so if you're interested, register now! 📍 London 📅 Monday, Feb 23 | 6pm GMT Link 👉 luma.com/w5keu427

@guillaumesimon pretty excited too (reading this) -- wanna come on our newsletter (dusthq.substack.com) to share more details? are you in our Slack Community btw?

This is how PM work evolves: extract signals from noise faster, focus on what actually matters, spend time where humans add real value. What would you automate first? 👇

I recently started running 8 AI agents continuously for my squad at @photoroom_app . They analyze, compile, and structure information while I focus on decisions and execution. Built with @DustHQ . Here’s how it works 🧵

read the full issue here 👉 open.substack.com/pub/dusthq/p/h…

latest newsletter issue "ANOTHER ONE BITES" has been published -- incl. - more info on our upcoming ambassador program - events to come this week (anyone in SF on thursday evening for a meetup with Anthropic on 'Skills' for instance -- or for the Claude Code meetup in Paris...) - our engineers turned writers lately - many use cases for AEs and SDRs - some new job opportunities

🔧 Your agent fleet just got an upgrade. Today we’re launching Skills. Picture this: 1. Your sales ops specialist builds the perfect HubSpot workflow 2. Three agents use it 3. Twenty-seven agents don't even know it exists 4. Expertise doesn't spread, agents stay siloed Skills fixes this: - Package instructions, knowledge, and tools once - Deploy across every agent that needs it - Update once, improve everywhere Your sales workflow becomes a skill. Your data query patterns become a skill. Your compliance rules become a skill. One sales ops expert just became a force multiplier for 50 agents. Available now to workspace admins and builders 👷

@regulatorynerd @ashleevance @gabhubert let's help with the handles here: @spolu it is :v:

@ashleevance Gotta be @gabhubert and @DustHQ (and Stan, too, but I don’t remember his twitter handle).

Most interesting tech people/companies/things in France?

@instadeepai @OwkinScience link to register 👉 luma.com/azypc8p5

WE ARE BACK. our Eng. Night series is coming back to Paris next week with the first theme of 2026 -and the first ever- Biology. featuring Marie Lopez from @instadeepai - Maxime Mistretta from Spore.bio - Khalil Ouardini from @OwkinScience link to register 👇

At the end of last year, like many other teams, we felt a significant phase transition in models coding capabilities. Agents shifting from sycophancy vibes to constructive push back. Across the team, engineers progressively bumped their grid-size (number of independent checkouts one has on their machine to parallelise agent work), but we started experiencing friction due to pre-agent baked assumptions in our dev-setup (port conflicts preventing having multiple dev instances running on the same machine and slow warm-up times form fresh checkouts). It was clear to us that we had to prioritise engineering work in 2026 to upgrade our dev setup to the user of larger grid-sizes. @henryfontanier came back from holidays with a present for us and casually dropped on the team `dust-hive` a full repackaging of our dev-env for agentic coding with batteries included: github.com/dust-tt/dust/t… Henry wrote a full blog post presenting the technical details behind dust-hive + some thoughts on impac of agents on software engineering at large: dust.tt/blog/engineeri… Each dev env is a bit specific and it's likely that every team will have to build a bit of specific software to adapt their environment to large grid-size with proper containment and rapid branching. Henry's work can serve as a solid starting point to do so in days not weeks. The interesting questions to me are (most covered in the article): (i) can this be standardized? the answer seems to be yes but would require a very rich configuration layer that goes beyond a Dockerfile. (ii) What does it mean for software engineering? We strongly believe at Dust that it means more taste and more technical competency are needed from software engineers not less. Almost like an inverted Jevons paradox. The world we live in.

Join us here ➡️ watch.getcontrast.io/register/dust-…

Your agents aren't just answering questions anymore. 👀 They're booking meetings, updating CRMs, calling APIs - acting like privileged employees at machine speed. Traditional security controls weren't built for this. Join Dust's security team for a 30-minute deep dive on what changes when AI moves from passive chatbots to autonomous action. Built for CISOs, Security Directors, IT Leaders and anyone responsible for securing AI in their organization.

@MaxenceCornet @AnthropicAI poetry to my ears Maxence :v:

In past months, I went from using OpenAI for everything to cancelling my OpenAI subs and using specialized AI model / tool per task @AnthropicAI 's Claude for anything programming & tech @DustHQ for workflows, dashboards, general multi-model questions (Dust Frame is incredible) @perplexity_ai to replace Google Search Google Gemini for image gen and some niche stuff

Build vs Run and zero-sumness: a simple framework to reason about how to scale teams post artificial intelligence abundance. Will AI annihilate all head-counts? I posit it's not quite the case especially for run functions that are inherently a zero-sum game in the market. dust.tt/blog/build-vs-…

@Fin_ai @linear @OpenAI @tines_hq @Lovable @synthesiaIO and on to the next 🥂

And a special thank you to all the leaders who joined us this year: Tom Moor, Head of Engineering, @linear Alistair Gillespie, @OpenAI Eoin Hinchy, CEO, @tines_hq Anton Osika, Co-Founder and CEO, @Lovable Victor Riparbelli, Co-Founder and CEO, @synthesiaIO Gabriel Hubert, CEO & Co-Founder, @DustHQ Andrey Khusid, CEO, @MiroHQ Marcel Weekes, VP of Engineering, @figma Marco Perini, Deployed Engineer, @langchain Deeni Fatiha, Head of AI Product, @GammaApp Todd Royal, Head of Engineering, EMEA, @TrustVanta Anna Marie Clifton, Director of Product, AI & Agents, @zapier Brendan Irvine-Broque, Senior Director of Product, @Cloudflare Matt Rubright, CCO, @jamdotdev Lindsey Simon, VP, Engineering, @vercel Arvind Jain, Founder and CEO, @glean Timothy Young, CEO, @heyjasperai Max Junestrand, CEO & Co-founder, @WeAreLegora Hanno Renner, CEO & Co-founder, @InsidePersonio Nicolas Sharp, CEO & Co-founder, @attio Vas Zhovner, CTO, @meetgranola Varun Anand, Co-founder & COO, @clay

16 meetups. 10 cities. 35 AI leaders and innovators. 1600+ attendees. The goal across our Fin meetups this year was simple: help people understand how AI is transforming the way we work, reshaping organizations and team structures, and redefining how products are built, sold, and priced. Leaders from companies like @linear, @Lovable, @attio, @clay, and more shared valuable insights into how they’re navigating this shift, what’s working and what isn’t. A few big themes kept coming up across these conversations: 𝗣𝗮𝗰𝗲 𝗮𝗻𝗱 𝗽𝗿𝗼𝗴𝗿𝗲𝘀𝘀 𝗺𝗮𝘁𝘁𝗲𝗿 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝗽𝗲𝗿𝗳𝗲𝗰𝘁𝗶𝗼𝗻: In a world where surface features can be copied quickly, speed, persistence, and product momentum are what separate long-term winners from short-lived copycats. 𝗙𝗮𝗹𝗹 𝗶𝗻 𝗹𝗼𝘃𝗲 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 (𝗻𝗼𝘁 𝘁𝗵𝗲 𝘁𝗲𝗰𝗵): The best teams are obsessing over building trustworthy, reliable AI that solves real problems and delivers outcomes. 𝗥𝗼𝗹𝗲𝘀 𝗮𝗿𝗲 𝗰𝗼𝗻𝘃𝗲𝗿𝗴𝗶𝗻𝗴: The shape of teams is shifting toward more hybrid profiles, people who care about the full experience and are happy to do what it takes, instead of staying strictly in their lane. Watch the video below to catch some memorable moments and standout ideas from our speakers to spark your own for next year. How has AI changed the way you work this year? What will you carry into next year?  Let us know in the comments below. Thank you to everyone who joined us in person (or caught the recaps and replays)! Your curiosity, energy, and participation helped enrich the conversations we're having on AI. We can't wait to bring you an exciting schedule of new meetups with forward-thinking leaders in 2026. Stay tuned.

@TrustVanta Vanta 🤝 Dust

The @DustHQ team moves fast—and takes trust just as seriously. Vanta partnered with them to get them to audit-ready confidence in just 3 weeks, all while maintaining enterprise momentum. 👏

read more here 👉 dust.tt/customers/how-…

we're helping @TrustVanta reclaim 400+hours/week across their GTM organization through a connected network of Dust agents! when Daniel and @shashankbuilds came to us, their biggest blocker was that company expertise lived in silos.