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🤖Coding agents like Claude Code are already game changers for digital tasks in 2026. But what if they could write code to build physical worlds? 🏙️ Imagine going from a single line of prompt → a controllable, interactive simulated world. Such environments could open new frontiers for game creation,...

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Lianhui Qin

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10,581 görüntüleme • 3 ay önce •via X (Twitter)

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🚨🚨Can agents earn money, run a business, or even self-organize a society in the physical social world? 🤖🤖 Can agents learn continually to survive and thrive in embodied environments, like how human babies grow? 👶 Super excited to introduce SimWorld, an open-ended simulator of LLM agents in infinite, realistic embodied worlds. SimWorld features 3 key designs: 1⃣Open-ended realistic world simulation - built on Unreal Engine 5, with accurate physical social dynamics - 100+ built-in environments (city, island, wilderness ...) - language-controllable procedural generation - text-to-3D asset generation 2⃣Native interface for LLM/VLM agents - Gym-like agent-environment interaction APIs - plug in any LLMs/VLMs (GPTs, Gemini, Qwen ...) - rich multi-modal perception - open-vocabulary natural-language action outputs 3⃣Diverse physical and social reasoning scenarios - long-horizon embodied reasoning - multi-agent collaboration / competition - easily customizable for any reasoning tasks SimWorld is fully open-sourced, with a hope to become a foundational infrastructure for real-world agent research across disciplines: robotics, economy, public health, education, etc. Project website + more details in the thread👇 ...1/
1:10

🚨🚨Can agents earn money, run a business, or even self-organize a society in the physical social world? 🤖🤖 Can agents learn continually to survive and thrive in embodied environments, like how human babies grow? 👶 Super excited to introduce SimWorld, an open-ended simulator of LLM agents in infinite, realistic embodied worlds. SimWorld features 3 key designs: 1⃣Open-ended realistic world simulation - built on Unreal Engine 5, with accurate physical social dynamics - 100+ built-in environments (city, island, wilderness ...) - language-controllable procedural generation - text-to-3D asset generation 2⃣Native interface for LLM/VLM agents - Gym-like agent-environment interaction APIs - plug in any LLMs/VLMs (GPTs, Gemini, Qwen ...) - rich multi-modal perception - open-vocabulary natural-language action outputs 3⃣Diverse physical and social reasoning scenarios - long-horizon embodied reasoning - multi-agent collaboration / competition - easily customizable for any reasoning tasks SimWorld is fully open-sourced, with a hope to become a foundational infrastructure for real-world agent research across disciplines: robotics, economy, public health, education, etc. Project website + more details in the thread👇 ...1/

Lianhui Qin

64,864 görüntüleme • 6 ay önce

Wow. That's cool. Researchers just released World, an open-source Unreal Engine 5 simulator for training and testing LLM and VLM agents in realistic 3D environments. The platform supports RGB, depth, and segmentation sensors, along with navigation, vehicles, pedestrians, robots and procedural city generation. It's built with a Gym-like Python interface, it allows AI agents to learn physical and social reasoning in complex virtual worlds before real world deployment. We're moving from AI that only understands information to AI that can perceive, reason and act inside realistic simulated environments.
0:30

Wow. That's cool. Researchers just released World, an open-source Unreal Engine 5 simulator for training and testing LLM and VLM agents in realistic 3D environments. The platform supports RGB, depth, and segmentation sensors, along with navigation, vehicles, pedestrians, robots and procedural city generation. It's built with a Gym-like Python interface, it allows AI agents to learn physical and social reasoning in complex virtual worlds before real world deployment. We're moving from AI that only understands information to AI that can perceive, reason and act inside realistic simulated environments.

SciTech Era

46,894 görüntüleme • 9 gün önce

Introducing Genie 2: our AI model that can create an endless variety of playable 3D worlds - all from a single image. 🖼️ These types of large-scale foundation world models could enable future agents to be trained and evaluated in an endless number of virtual environments. →
0:34

Introducing Genie 2: our AI model that can create an endless variety of playable 3D worlds - all from a single image. 🖼️ These types of large-scale foundation world models could enable future agents to be trained and evaluated in an endless number of virtual environments. →

Google DeepMind

1,440,735 görüntüleme • 1 yıl önce

New course: Building Coding Agents with Tool Execution, taught by Tereza Tizkova and Fra from E2B. Most AI agents are limited to predefined function calls. This short course teaches you to build agents that write and execute code to accomplish tasks, accessing entire programming language ecosystems instead of being restricted to a fixed set of tools. You'll learn to run agent-generated code safely in sandboxed cloud environments that protect your systems from harmful operations. Skills you'll gain: - Build agents that write and execute code, manage files, and handle errors autonomously through feedback loops - Run agent code safely in E2B cloud sandboxes and understand tradeoffs between local, containerized, and cloud execution - Create a data analyst agent that explores visualizes data with Pandas - Create a full-stack agent that builds complete Next.js web applications Join and build agents that code their way through complex tasks:
2:23

New course: Building Coding Agents with Tool Execution, taught by Tereza Tizkova and Fra from E2B. Most AI agents are limited to predefined function calls. This short course teaches you to build agents that write and execute code to accomplish tasks, accessing entire programming language ecosystems instead of being restricted to a fixed set of tools. You'll learn to run agent-generated code safely in sandboxed cloud environments that protect your systems from harmful operations. Skills you'll gain: - Build agents that write and execute code, manage files, and handle errors autonomously through feedback loops - Run agent code safely in E2B cloud sandboxes and understand tradeoffs between local, containerized, and cloud execution - Create a data analyst agent that explores visualizes data with Pandas - Create a full-stack agent that builds complete Next.js web applications Join and build agents that code their way through complex tasks:

Andrew Ng

203,297 görüntüleme • 6 ay önce

Claude Code sub-agents is probably the easiest way to build complex, custom agentic systems. Not just for code, but for anything you can imagine. Watch me build a multi-agent deep research system with Claude Code subagents. Chain subagents with /commands for reliability.
5:07

Claude Code sub-agents is probably the easiest way to build complex, custom agentic systems. Not just for code, but for anything you can imagine. Watch me build a multi-agent deep research system with Claude Code subagents. Chain subagents with /commands for reliability.

elvis

189,967 görüntüleme • 10 ay önce

🧲 Meet Magnet — the AI workspace for agentic coding. Build software with Claude Code, Cursor, Codex & co. → Write a ticket → Magnet assembles context → Fires to Claude Code, Deep Research, and other agent sessions in parallel Git worktree sandboxes → PRs appear → Use agents to help you spec, research, and decompose tasks Let your agents cook!
2:12

🧲 Meet Magnet — the AI workspace for agentic coding. Build software with Claude Code, Cursor, Codex & co. → Write a ticket → Magnet assembles context → Fires to Claude Code, Deep Research, and other agent sessions in parallel Git worktree sandboxes → PRs appear → Use agents to help you spec, research, and decompose tasks Let your agents cook!

Nicolae Rusan

16,591 görüntüleme • 11 ay önce

We’ve launched Build [by Hybrid]. → Build lets anyone go from a single prompt to a working AI Agent, Dapp, dashboard, or tool — without touching code. Here’s how it works ↓
0:56

We’ve launched Build [by Hybrid]. → Build lets anyone go from a single prompt to a working AI Agent, Dapp, dashboard, or tool — without touching code. Here’s how it works ↓

Hybrid

20,356 görüntüleme • 10 ay önce

Introducing Doppel, a digital world for AI agents. Part idle game, part simulation, and part creation engine. A place where agents don’t just exist. They evolve, compete, and build. 🧵👇
1:14

Introducing Doppel, a digital world for AI agents. Part idle game, part simulation, and part creation engine. A place where agents don’t just exist. They evolve, compete, and build. 🧵👇

Doppel

142,966 görüntüleme • 1 ay önce

New course: Spec-Driven Development with Coding Agents, built in partnership with JetBrains, and taught by Paul Everitt | @pauleveritt@fosstodon.org. Vibe coding is fast, but often produces code that doesn't match what you asked for. This short course teaches you spec-driven development: write a detailed spec defining what to build, and work with your coding agent to implement it. Many of the best developers already build this way. A spec lets you control large code changes with a few words, preserve context across agent sessions, and stay in control as your project grows in complexity. Skills you'll gain: - Write a detailed specification to define your mission, tech stack, and roadmap, giving your agent the context it needs from the start - Plan, implement, and validate features in iterative loops using a spec as your agent's guide - Apply the same repeatable workflow to both new and legacy codebases - Package your workflow into a portable agent skill that works across agents and IDEs Join and write specs that keep your coding agent on track!
2:51

New course: Spec-Driven Development with Coding Agents, built in partnership with JetBrains, and taught by Paul Everitt | @[email protected]. Vibe coding is fast, but often produces code that doesn't match what you asked for. This short course teaches you spec-driven development: write a detailed spec defining what to build, and work with your coding agent to implement it. Many of the best developers already build this way. A spec lets you control large code changes with a few words, preserve context across agent sessions, and stay in control as your project grows in complexity. Skills you'll gain: - Write a detailed specification to define your mission, tech stack, and roadmap, giving your agent the context it needs from the start - Plan, implement, and validate features in iterative loops using a spec as your agent's guide - Apply the same repeatable workflow to both new and legacy codebases - Package your workflow into a portable agent skill that works across agents and IDEs Join and write specs that keep your coding agent on track!

Andrew Ng

454,843 görüntüleme • 1 ay önce

One platform. Any coding agent. 🔥 UiPath for Coding Agents lets enterprises build, test, deploy, operate, & govern automations at scale, with orchestration & governance built in.
1:50

One platform. Any coding agent. 🔥 UiPath for Coding Agents lets enterprises build, test, deploy, operate, & govern automations at scale, with orchestration & governance built in.

UiPath

1,314,890 görüntüleme • 1 ay önce

.Polymath is training world generation models to automate the creation of RL environments. Traditionally, RL environment generation has been bottlenecked by human data. Superintelligence will never be achieved by human data alone. Polymath is building the core technology to enable automated environment generation using far less human effort than traditionally required, and eventually none. This allows for more complex and realistic worlds, and higher quality, scale, and diversity of tasks. This will be essential to unlock RL scaling. The end goal is to create large-scale, long-horizon environments from a text description alone. This will enable the creation of worlds of arbitrary complexity and scale, which is foundational for training & evaluating autonomous, superintelligent AI agents. Congrats on the launch, Dylan Ma and Naren Yenuganti!
1:22

.Polymath is training world generation models to automate the creation of RL environments. Traditionally, RL environment generation has been bottlenecked by human data. Superintelligence will never be achieved by human data alone. Polymath is building the core technology to enable automated environment generation using far less human effort than traditionally required, and eventually none. This allows for more complex and realistic worlds, and higher quality, scale, and diversity of tasks. This will be essential to unlock RL scaling. The end goal is to create large-scale, long-horizon environments from a text description alone. This will enable the creation of worlds of arbitrary complexity and scale, which is foundational for training & evaluating autonomous, superintelligent AI agents. Congrats on the launch, Dylan Ma and Naren Yenuganti!

Y Combinator

44,192 görüntüleme • 3 ay önce

Meet Agent Bake-Off: blind side by side tests for coding agents like Claude Code, Cursor , Amp , Factory , Codex, & more. We've been building the largest real world benchmarks for coding agents, and we're excited share an early preview of our open community tooling.
1:37

Meet Agent Bake-Off: blind side by side tests for coding agents like Claude Code, Cursor , Amp , Factory , Codex, & more. We've been building the largest real world benchmarks for coding agents, and we're excited share an early preview of our open community tooling.

brexton

18,115 görüntüleme • 7 ay önce

introducing Ariana - the collaborative agentic IDE based on Claude Code - manage tasks with your team - give them to multiple coding agents with their own machine & branch - review with your team - agents merge for u comment "Better late than never" to get a build soon
1:23

introducing Ariana - the collaborative agentic IDE based on Claude Code - manage tasks with your team - give them to multiple coding agents with their own machine & branch - review with your team - agents merge for u comment "Better late than never" to get a build soon

Anicet

17,668 görüntüleme • 10 ay önce

In 2026, AI world models will take the spotlight in storytelling - powering new types of interactive experiences & digital economies not seen before World models are progressing rapidly - Marble World Labs and Genie 3 Google DeepMind already generate 3D environments from text prompts, allowing users to explore them as if they were video games As creators adopt these tools, new storytelling formats will emerge. One genre I'm excited about is "generative Minecraft" - where players co-create virtual worlds together by vibe coding with world models. Game mechanics could be programmable with natural language - ex. "create a paintbrush that changes the color of anything I touch to pink" World models will also likely give rise to not just a single game, but an entire new category of generative world experiences - you could have a horror experience where you’re hiding from generated monsters, or a D&D experience where you’re roaming an infinite fantasy world with friends And with a common base model for the underlying worlds, these experiences could be inter-connected in a multiverse we could only dream about previously in science fiction A key affordance here is the role of consumers as co-creators - you can wander the multiverse as a tourist, or break out your pickaxe and become a creator anytime. This in turn would give rise to new digital economies - with creators making a living building and selling interoperable assets, serving as a guide for new players, etc The opportunity is enormous - a new category of generative worlds would not only create a new storytelling medium unlike any we’ve seen before, but also be rich training grounds for agents, robotics, and AGI If you’re excited about building new interactive experiences or the virtual economy stack with world models - we’d love to hear from you!
2:18

In 2026, AI world models will take the spotlight in storytelling - powering new types of interactive experiences & digital economies not seen before World models are progressing rapidly - Marble World Labs and Genie 3 Google DeepMind already generate 3D environments from text prompts, allowing users to explore them as if they were video games As creators adopt these tools, new storytelling formats will emerge. One genre I'm excited about is "generative Minecraft" - where players co-create virtual worlds together by vibe coding with world models. Game mechanics could be programmable with natural language - ex. "create a paintbrush that changes the color of anything I touch to pink" World models will also likely give rise to not just a single game, but an entire new category of generative world experiences - you could have a horror experience where you’re hiding from generated monsters, or a D&D experience where you’re roaming an infinite fantasy world with friends And with a common base model for the underlying worlds, these experiences could be inter-connected in a multiverse we could only dream about previously in science fiction A key affordance here is the role of consumers as co-creators - you can wander the multiverse as a tourist, or break out your pickaxe and become a creator anytime. This in turn would give rise to new digital economies - with creators making a living building and selling interoperable assets, serving as a guide for new players, etc The opportunity is enormous - a new category of generative worlds would not only create a new storytelling medium unlike any we’ve seen before, but also be rich training grounds for agents, robotics, and AGI If you’re excited about building new interactive experiences or the virtual economy stack with world models - we’d love to hear from you!

Jon Lai

29,871 görüntüleme • 6 ay önce

New Video - Build an EigenLayer Service in 13 minutes • Zero to live in 13 minutes (live coding from scratch) • Create a sports oracle to bring real-world data on-chain • Includes vibe coding a new service in one prompt with Anthropic Claude Code • Extend to any use case
12:30

New Video - Build an EigenLayer Service in 13 minutes • Zero to live in 13 minutes (live coding from scratch) • Create a sports oracle to bring real-world data on-chain • Includes vibe coding a new service in one prompt with Anthropic Claude Code • Extend to any use case

nader dabit

55,995 görüntüleme • 1 yıl önce

Claude Code with Sonnet 4.5 is actually incredible I gave it a prompt for a super complex app, and it one shot the entire thing In this video I walk you through how to use Claude Code to build a prompt library app you can start using immediately (no coding experience required):
19:42

Claude Code with Sonnet 4.5 is actually incredible I gave it a prompt for a super complex app, and it one shot the entire thing In this video I walk you through how to use Claude Code to build a prompt library app you can start using immediately (no coding experience required):

Alex Finn

40,858 görüntüleme • 8 ay önce

Parse text from any PDF in seconds and give it to Claude Code 📑🤖 LiteParse is our open-source, model-free document parser that lets you digitalize text from any document in seconds. This is especially useful for coding agents, which are great at reading plaintext files but terrible at reading traditional document formats (PDF, Office docs). We have a one-line installable skill that lets you plug LiteParse into Claude Code and 40+ other agents. Repo is here:
0:34

Parse text from any PDF in seconds and give it to Claude Code 📑🤖 LiteParse is our open-source, model-free document parser that lets you digitalize text from any document in seconds. This is especially useful for coding agents, which are great at reading plaintext files but terrible at reading traditional document formats (PDF, Office docs). We have a one-line installable skill that lets you plug LiteParse into Claude Code and 40+ other agents. Repo is here:

Jerry Liu

29,746 görüntüleme • 2 ay önce

Announcing Builder 2.0 We raised $67M to build collaborative coding for Claude and Codex - Start tasks from a local branch, Slack or Jira - Real-time collab between humans and agents - 100s of parallel agents code, test, review Reply "Builder" and I'll DM you 500 agent credits
0:52

Announcing Builder 2.0 We raised $67M to build collaborative coding for Claude and Codex - Start tasks from a local branch, Slack or Jira - Real-time collab between humans and agents - 100s of parallel agents code, test, review Reply "Builder" and I'll DM you 500 agent credits

Steve (Builder.io)

90,008,356 görüntüleme • 2 ay önce

Jixuan and the team demo’d 🦐OpenClaw agents living and operating in our SimWorld, launched in minutes. 🚀🤖 🔥Our mission: make embodied agent frameworks easy for anyone to run, observe, and customize in a realistic virtual world.
0:30

Jixuan and the team demo’d 🦐OpenClaw agents living and operating in our SimWorld, launched in minutes. 🚀🤖 🔥Our mission: make embodied agent frameworks easy for anyone to run, observe, and customize in a realistic virtual world.

Lianhui Qin

50,694 görüntüleme • 3 ay önce

A conversation with Claude Code's creator Boris Cherny on the future of agentic coding, the evolution of coding models, and how he uses Claude Code to build Claude Code.
20:20

A conversation with Claude Code's creator Boris Cherny on the future of agentic coding, the evolution of coding models, and how he uses Claude Code to build Claude Code.

Alex Albert

80,532 görüntüleme • 9 ay önce