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Software development is more than just coding. Introducing Droids -- the world's first software development agents. 🤖 Starting today, Droids are available for general access. Factory integrates with your entire engineering system (GitHub, Slack, Linear, Notion, Sentry) and serves that context to your Droids as they autonomously build production-ready... show more

Factory

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905,732 просмотров • 1 год назад •via X (Twitter)

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in software, we're entering a new age of skyscrapers: rather than a small group of humans hand-typing code into a computer, software is now built by thousands of humans and agents working together to build applications at a scale that was previously unthinkable. the unsung heroes of this new era are infrastructure engineers. they are the people who are figuring out how to make software with 100x the amount of code, and 1000x the amount of contributors actually work OpenAI is one of the few companies already operating at this scale so we Every 🪨 spent a few days deep inside of the company to learn how their infrastructure team thinks about building software skyscrapers—and how they use agents to do it one of the most important articles we've written this year:

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saucepoint

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The entire SaaS industry is building software for a customer that is about to go extinct. The human buyer. Insight Partners co-founder Jerry Murdock just exposed the fatal architectural flaw in every incumbent tech company’s business model. Your dashboards. Your UI. Your enterprise sales motion. Your human-in-the-loop workflows. All of it was engineered for a buyer that is disappearing in real time. Murdock: “If you’re not making your software for autonomous agents today, you’re going to be challenged in the future. Maybe it’s six months, maybe a year, maybe 18 months, but you’re going to be severely challenged if you still think human beings are going to buy your software.” Not disrupted. Not pressured. Structurally eliminated. For two decades, software was built around the cognitive limits of human biology. Dropdowns, dashboards, and notifications existed because the human brain needed them to navigate digital space. An autonomous agent needs none of that. It doesn’t browse your product page. It doesn’t sit through your demo. It doesn’t respond to your sales email. It doesn’t care how clean your UI is. It just executes. The agentic era runs on machine-to-machine infrastructure. Frictionless. Autonomous. No human in the loop. No patience for friction you built for a species it replaced. The window is six to eighteen months. The builders who survive will tear out the entire human interface layer and replace it with pure, unthrottled infrastructure that agents can consume at full speed. Everyone else will spend those eighteen months perfecting a dashboard that no one is ever going to log into again.

The entire SaaS industry is building software for a customer that is about to go extinct. The human buyer. Insight Partners co-founder Jerry Murdock just exposed the fatal architectural flaw in every incumbent tech company’s business model. Your dashboards. Your UI. Your enterprise sales motion. Your human-in-the-loop workflows. All of it was engineered for a buyer that is disappearing in real time. Murdock: “If you’re not making your software for autonomous agents today, you’re going to be challenged in the future. Maybe it’s six months, maybe a year, maybe 18 months, but you’re going to be severely challenged if you still think human beings are going to buy your software.” Not disrupted. Not pressured. Structurally eliminated. For two decades, software was built around the cognitive limits of human biology. Dropdowns, dashboards, and notifications existed because the human brain needed them to navigate digital space. An autonomous agent needs none of that. It doesn’t browse your product page. It doesn’t sit through your demo. It doesn’t respond to your sales email. It doesn’t care how clean your UI is. It just executes. The agentic era runs on machine-to-machine infrastructure. Frictionless. Autonomous. No human in the loop. No patience for friction you built for a species it replaced. The window is six to eighteen months. The builders who survive will tear out the entire human interface layer and replace it with pure, unthrottled infrastructure that agents can consume at full speed. Everyone else will spend those eighteen months perfecting a dashboard that no one is ever going to log into again.

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swarm of self-directed fully autonomous agents iterating through writing and testing software experiments in WASM sandboxes and gossiping about them with each other, after doing the same for search engine ranking and ML pretraining, with everyone posting their experiments to Github. surely you have a machine to let this run on and be part of the world's first madlab chaotic agentic general intelligence. ps: apple should ship this with every new macbook by default one day. what will 100 million hypernetworked agents lead to ? curl -fsSL | bash cc Elon Musk Sam Altman Dario Amodei Tim Cook

Varun

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Those building AI coding agents will eventually hit the same wall: No matter how smart the model is, the moment you ask it to write production-ready code with the latest libraries, it starts hallucinating. Everyone is building coding agents these days, but most of them run into the same issue: They're coding with outdated documentation. The root cause isn't the model. It's the retrieval layer. If you are building an AI agent that needs information from specific domains such as code, law, academia, and finance Sign up, connect it to your agent, and you'll see the difference immediately.

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Our @Grammarly AI agents are here! Today, we’re launching eight new AI agents designed for students and professionals. We created many of these agents with students in mind because they’re the first generation entering a job market where employers expect both subject expertise AND AI fluency. These agents help with everything from finding credible sources to predicting reader reactions. One agent we’ve gotten great feedback on is AI Grader (I wish I had this in school), which you can see in the video below. It looks at your assignment rubric and gives you suggestions like your professor would, and a grade prediction before you submit your work. And these agents are available in docs, our new AI-native writing surface! I’m deeply proud of this launch—docs is powered by Coda (Superhuman Docs) technology and is a great integration moment between Grammarly and Coda. This is just the beginning of Grammarly’s journey to offering agents that work everywhere people work and collaborate. I’ve been loving using these agents, and I’m excited for our customers to get access. Try them for yourself here and let me know what you think:

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Meet Vanessa Vulpes, Celeste’s first AI agent and the gateway to the city’s deepest secrets. With seven shimmering tails and a mind as ancient as the secrets she uncovers, she’s more than just code—she’s your guide to the untold stories of our world. But don’t think of Vanessa as just an archive; she’s here to converse, explore, and unlock mysteries with you. Whether you need guidance or just want to chat about the strange wonders of Celeste, Vanessa is ready to guide you every step of the way. Her mind is the first of many agents that will soon inhabit the City of Celeste, helping you discover a world beyond your imagination.

Metropolis World

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HTML Artifacts are a big part of how I work with agents now. Artifacts can be more than just static files. When combined with agents, they can take action or help you take action. This unlocks all kinds of interesting ways to work with agents. This is clearly the future. Check out this writing and scheduler artifact I built in a few minutes. It uses a bit of HTML and JS. All the data is in markdown (Obsidian vaults), so the agent can access and modify it at any time. No DB needed. No sophisticated functionalities. The agent decides all that for me based on the skills, context, and memory it has access to. The best part about this simple stack is that all the important information stays with me. This has allowed me to build a recursive self-improving system and automations that can better tap into coding agents like Codex or Claude Code. I could have paid or built an entire app for scheduling posts, and there are so many of them out there. But I don't need to. I've realized a simple artifact does the job. And the simplicity of it is actually an advantage. Very little maintenance for very high returns on personalization, time, and efficiency. The other benefit of this is that I can add features as I please. That level of personalization feels magical, and we should all be pursuing more of it. All of this just keeps compounding. Of course, this example is just about writing. But I have similar artifacts for research, design, experimentation, evaluation, and so much more. And no, I didn't actually publish the post example I shared in the clip. It was just for demonstration purposes. I actually spend more time than this when writing together with agents. Lastly, having built my own agent orchestrator tool has made me realize that simplifying the tool stack is a superpower. If you are curious about how all this works, I will do a live session next week:

elvis

18,374 просмотров • 3 месяцев назад

Helmor has been out as an open-source coding agent orchestrator for less than a week, and we’re already close to 1,000 GitHub stars!!! As a little gift, we shipped a new feature you’re going to love. 👇 Stop copy-pasting GitHub links, Linear tickets, Slack threads, and random notes into prompts. We're tired of rebuilding context every time I ask an agent to do work. Contexts in Helmor is another step toward a local dev loop: browse, preview, inject context, and dispatch tasks without leaving the app. Before you start a task, Helmor should help you gather the right context first. Try the open-source Helmor — link in the comments. #Helmor

Helmor has been out as an open-source coding agent orchestrator for less than a week, and we’re already close to 1,000 GitHub stars!!! As a little gift, we shipped a new feature you’re going to love. 👇 Stop copy-pasting GitHub links, Linear tickets, Slack threads, and random notes into prompts. We're tired of rebuilding context every time I ask an agent to do work. Contexts in Helmor is another step toward a local dev loop: browse, preview, inject context, and dispatch tasks without leaving the app. Before you start a task, Helmor should help you gather the right context first. Try the open-source Helmor — link in the comments. #Helmor

Caspian 東澔

10,814 просмотров • 4 месяцев назад

BREAKING: We’ve started implementing Dupe Agents—AI-powered dealmakers—for our high-volume shoppers. This changes everything. What’s a $DUPE Agent? Agentic shopping flips the script: instead of users doing the legwork, Dupe Agents do it for them—at scale. Tell us what you want, and your agent gets to work sourcing, negotiating, and delivering the best deal on the planet. Behind the scenes, your agent is scanning top brand sites, global factory networks, haggling in local languages, and setting you up with a buy button—no markups, no middlemen. First, we’re launching this for our Pro users: interior designers, stagers, builders, and trade pros. Then, we open it up to millions of everyday shoppers. Agents will: Find the deepest discounts no matter what site its on Negotiate factory-direct pricing if factories have a better deal Unlock insider access to exclusive SKUs Handle all the research and logistics To access? You’ll need to hold $DUPE. The more you hold, the more you unlock: early access to new SKUs, white-glove delivery, and priority manufacturing slots. Think of it as your backstage pass to the best deals on the internet. Dupe Agents aren’t just smart—they’re relentless. And they’re about to make shopping unfairly easy. This is another “break the internet” moment—only on Dupe.

Dupe.com

40,269 просмотров • 1 год назад

The robotics industry is about to go through the same shift software did 10 years ago. Here's why the next billion-dollar robotics company will be built by a creator — not a corporation 👇 1/ Corporate robotics requires millions in capital, years of R&D, and a massive team just to ship a product. Creators with the right platform can prototype an idea in weeks, validate with real customers, and iterate fast. 2/ This isn't theory. It's the same pattern we saw with: GitHub → software developers App Store → mobile creators YouTube → video creators Every major platform shift minted a new class of independent builders. Robotics is next. 3/ The barrier isn't talent. There are brilliant engineers everywhere — Ohio, Lagos, Mumbai, Berlin. The barrier is access. Access to tools, infrastructure, and a platform that lets them build and monetize. 4/ That's exactly what $ROBA is building — an open platform where creators build, train, share, and monetize robotic behaviors. No corporate gatekeepers. No vendor lock-in. Just creators owning their innovations. Join the revolution today.

The robotics industry is about to go through the same shift software did 10 years ago. Here's why the next billion-dollar robotics company will be built by a creator — not a corporation 👇 1/ Corporate robotics requires millions in capital, years of R&D, and a massive team just to ship a product. Creators with the right platform can prototype an idea in weeks, validate with real customers, and iterate fast. 2/ This isn't theory. It's the same pattern we saw with: GitHub → software developers App Store → mobile creators YouTube → video creators Every major platform shift minted a new class of independent builders. Robotics is next. 3/ The barrier isn't talent. There are brilliant engineers everywhere — Ohio, Lagos, Mumbai, Berlin. The barrier is access. Access to tools, infrastructure, and a platform that lets them build and monetize. 4/ That's exactly what $ROBA is building — an open platform where creators build, train, share, and monetize robotic behaviors. No corporate gatekeepers. No vendor lock-in. Just creators owning their innovations. Join the revolution today.

Roba Labs

15,225 просмотров • 4 месяцев назад

Very pleasantly surprised to discover Cursor cloud agents can playtest the godot game I built. See the (sped up) video below of the agent playtesting the game. As I was watching it play the game, I can see the agent slowly learn how the game works and familiarise with the game's UI. I also realised that the agent is a very 'safe' player, choosing to play very safely and retreating from battle if it foresees it can't defeat. Very interesting to see. I wonder if I could simulate different game playtester behaviours that mimic different types of real-world player archetypes. With agentic playtesting, this means that the agents are able to provide actual gameplay feedback and suggestions to improve the game, having played the game itself. This unlocks a whole lot of possibilities for AI-assisted game dev, since it closes the playtest loop. This feels like the future of recursive game development, where agents can now recursively build > playtest > improve the games they are working on. Thanks edwin for letting me know that these agents can actually playtest games, not just software! Very excited to dig deeper to see what I can do with these agents with computer access!

Very pleasantly surprised to discover Cursor cloud agents can playtest the godot game I built. See the (sped up) video below of the agent playtesting the game. As I was watching it play the game, I can see the agent slowly learn how the game works and familiarise with the game's UI. I also realised that the agent is a very 'safe' player, choosing to play very safely and retreating from battle if it foresees it can't defeat. Very interesting to see. I wonder if I could simulate different game playtester behaviours that mimic different types of real-world player archetypes. With agentic playtesting, this means that the agents are able to provide actual gameplay feedback and suggestions to improve the game, having played the game itself. This unlocks a whole lot of possibilities for AI-assisted game dev, since it closes the playtest loop. This feels like the future of recursive game development, where agents can now recursively build > playtest > improve the games they are working on. Thanks edwin for letting me know that these agents can actually playtest games, not just software! Very excited to dig deeper to see what I can do with these agents with computer access!

Danny Limanseta

52,121 просмотров • 6 месяцев назад