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In Antigravity, we’ve reimagined how you collaborate with Agents using Artifacts. Artifacts go beyond text. They are dynamic intermediates to communicate agentic progress like screen recordings, diagrams, or markdown. And you can leave feedback right on the artifact itself.

Google Antigravity

172,893 subscribers

66,757 次观看 • 7 个月前 •via X (Twitter)

Anya Rossi• Live Now

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Better feedback = Better code. Artifacts are the agent’s proof of work. Review plans, screen recordings, and code changes. Then, leave feedback to keep the agent on track. Try it today:

Better feedback = Better code. Artifacts are the agent’s proof of work. Review plans, screen recordings, and code changes. Then, leave feedback to keep the agent on track. Try it today:

Google Antigravity

82,520 次观看 • 8 个月前

We built Artifacts so you don’t have to guess what the agent is doing. They are dynamic intermediates, the shared source of truth between you and the agent.

We built Artifacts so you don’t have to guess what the agent is doing. They are dynamic intermediates, the shared source of truth between you and the agent.

Google Antigravity

138,919 次观看 • 6 个月前

With Antigravity, you collaborate with your agent using Google Docs-style commenting. Highlight specific sections of your app or data tables to provide contextual feedback and refine features in real time. Learn how to collaborate with Artifacts, here →

With Antigravity, you collaborate with your agent using Google Docs-style commenting. Highlight specific sections of your app or data tables to provide contextual feedback and refine features in real time. Learn how to collaborate with Artifacts, here →

Google Cloud Tech

52,167 次观看 • 5 个月前

You can decide how much autonomy you give to the agent in Google Antigravity Drop asynchronous feedback within artifacts and the agent folds it in when the time is right.

You can decide how much autonomy you give to the agent in Google Antigravity Drop asynchronous feedback within artifacts and the agent folds it in when the time is right.

Google Antigravity

81,962 次观看 • 8 个月前

LLM Wikis + HTML Artifacts are insanely powerful. You should seriously consider this in your workflows. LLM Wikis captures all the important information that lets you and your agents do meaningful work. HTML artifacts present that information in interesting ways that allow you to take important actions along with your agents. My HTML artifacts sit on top of my LLM wikis. They are dynamic and are easily extended as needs arise. I have hooked my Artifacts to talk to my agents, and similarly, the agents can talk to artifacts. This has allowed me to build powerful artifacts that reduce my inbox to zero, keep me updated on any topic of interest, fast prototyping, do deep research, design/trigger new experiments, generate figures to improve understanding, schedule research, search relevant information, discover topics, and so much more. What you see in the clip is not a website. It's a simple interactive HTML artifact. HTML artifacts are useful for designers, engineers, researchers, students, and anyone working with agents. Lastly, HTML doesn't replace Markdown. They are a much better combination working together.

LLM Wikis + HTML Artifacts are insanely powerful. You should seriously consider this in your workflows. LLM Wikis captures all the important information that lets you and your agents do meaningful work. HTML artifacts present that information in interesting ways that allow you to take important actions along with your agents. My HTML artifacts sit on top of my LLM wikis. They are dynamic and are easily extended as needs arise. I have hooked my Artifacts to talk to my agents, and similarly, the agents can talk to artifacts. This has allowed me to build powerful artifacts that reduce my inbox to zero, keep me updated on any topic of interest, fast prototyping, do deep research, design/trigger new experiments, generate figures to improve understanding, schedule research, search relevant information, discover topics, and so much more. What you see in the clip is not a website. It's a simple interactive HTML artifact. HTML artifacts are useful for designers, engineers, researchers, students, and anyone working with agents. Lastly, HTML doesn't replace Markdown. They are a much better combination working together.

elvis

248,444 次观看 • 2 个月前

arXiv Papers → LLM Artifacts This is how I keep up with AI research now. It's like having access to the most personalized arXiv feed. Automations run everyday to curate papers based a set of rules and insights. Curated papers are indexed and power the artifacts. Agent convert papers to LLM wikis (based on Andrej Karpathy idea), which means insights are indexed and easily searchable and reusable. I feel like LLM Artifacts is the natural evolution to LLM Wikis. It's about making that knowledge actionable. Artifacts are customizable via agents. Artifacts can interact with agents and are dynamic in nature. Anything can be injected into the artifact as needed (insights, components, suggested experiments, action items, etc). I can take action on Artifact items with my agent orchestrator (Electron app). So I can ask questions about any paper and automate experiments in the background right from within the artifact. This is more than a visual. It's not a single prompt. It's several proactive agents coordinating to surface interesting facts, knowledge, and insights that I can act on a researcher. Agents are not just for generating useful artifacts, they are useful to keep learning and staying on the cutting edge of knowledge. Stay tuned for more.

arXiv Papers → LLM Artifacts This is how I keep up with AI research now. It's like having access to the most personalized arXiv feed. Automations run everyday to curate papers based a set of rules and insights. Curated papers are indexed and power the artifacts. Agent convert papers to LLM wikis (based on Andrej Karpathy idea), which means insights are indexed and easily searchable and reusable. I feel like LLM Artifacts is the natural evolution to LLM Wikis. It's about making that knowledge actionable. Artifacts are customizable via agents. Artifacts can interact with agents and are dynamic in nature. Anything can be injected into the artifact as needed (insights, components, suggested experiments, action items, etc). I can take action on Artifact items with my agent orchestrator (Electron app). So I can ask questions about any paper and automate experiments in the background right from within the artifact. This is more than a visual. It's not a single prompt. It's several proactive agents coordinating to surface interesting facts, knowledge, and insights that I can act on a researcher. Agents are not just for generating useful artifacts, they are useful to keep learning and staying on the cutting edge of knowledge. Stay tuned for more.

elvis

59,160 次观看 • 2 个月前

We're also launching a preview of Artifacts on You can ask Claude to generate docs, code, mermaid diagrams, vector graphics, or even simple games. Artifacts appear next to your chat, letting you see, iterate, and build on your creations in real-time.

We're also launching a preview of Artifacts on You can ask Claude to generate docs, code, mermaid diagrams, vector graphics, or even simple games. Artifacts appear next to your chat, letting you see, iterate, and build on your creations in real-time.

Anthropic

588,734 次观看 • 2 年前

YT Podcast → LLM Artifact This is now my favorite way to consume podcasts. Knowledge artifacts generated by agents. The agent (Opus 4.7) spots important insights, does deep analysis, and generates thought-provoking observations that really get me curious to research further. All the research goes into a self-improving wiki for later use by any of my agents. I am using Elevenlabs Scribe for diarization. Skills and scripts to guide the artifact generation. Artifacts are just plain HTML + JS (e.g., chart.js). You can go further on anything by selecting text and components (charts) and doing deeper research, as I show in the clip. I expect more people to use agents in this way.

YT Podcast → LLM Artifact This is now my favorite way to consume podcasts. Knowledge artifacts generated by agents. The agent (Opus 4.7) spots important insights, does deep analysis, and generates thought-provoking observations that really get me curious to research further. All the research goes into a self-improving wiki for later use by any of my agents. I am using Elevenlabs Scribe for diarization. Skills and scripts to guide the artifact generation. Artifacts are just plain HTML + JS (e.g., chart.js). You can go further on anything by selecting text and components (charts) and doing deeper research, as I show in the clip. I expect more people to use agents in this way.

elvis

31,855 次观看 • 3 个月前

i think coding agents need an overhaul... long horizon tasks are the norm now, but agents only show you what they are doing ~right now~ i built a "mission control" concept with: - progress log - human-friendly artifacts - roadmap - eta please steal this idea, i'm begging ya

i think coding agents need an overhaul... long horizon tasks are the norm now, but agents only show you what they are doing ~right now~ i built a "mission control" concept with: - progress log - human-friendly artifacts - roadmap - eta please steal this idea, i'm begging ya

Nathan Flurry 🔩

13,488 次观看 • 16 天前

Antigravity has been getting some upgrades 🧑‍🚀 You can now define custom agents (and subagents) as markdown files with YAML frontmatter. I've been waiting for this! In Antigravity CLI you can use the --agent flag to launch with a custom agent instead of the default.

Antigravity has been getting some upgrades 🧑‍🚀 You can now define custom agents (and subagents) as markdown files with YAML frontmatter. I've been waiting for this! In Antigravity CLI you can use the --agent flag to launch with a custom agent instead of the default.

Jack Wotherspoon

31,842 次观看 • 16 天前

Introducing Hubble: the best notepad for you and your agents. - Feels like Notion or Apples Notes, but for Markdown - Live-reloading editor to collaborate with agents - Supports HTML-based apps to build interactive visualizations Free and open-source 👉

Introducing Hubble: the best notepad for you and your agents. - Feels like Notion or Apples Notes, but for Markdown - Live-reloading editor to collaborate with agents - Supports HTML-based apps to build interactive visualizations Free and open-source 👉

Ben Holmes

163,558 次观看 • 1 个月前

I'm excited to share my talk on building Agentic RAG systems at last week's event with Arize AI and Google! 🥳 My talk covered: 1. The differences between Vanilla RAG and Agentic RAG 2. The agent ecosystem and how you can build agents today 3. How Weaviate AI Database is building agents with Generative Feedback Loops (GFLs) This snippet presents the multi-agent paradigm for Agentic RAG. I hope you find this talk interesting and would love to know what you think! The slide deck and full video links are below.

I'm excited to share my talk on building Agentic RAG systems at last week's event with Arize AI and Google! 🥳 My talk covered: 1. The differences between Vanilla RAG and Agentic RAG 2. The agent ecosystem and how you can build agents today 3. How Weaviate AI Database is building agents with Generative Feedback Loops (GFLs) This snippet presents the multi-agent paradigm for Agentic RAG. I hope you find this talk interesting and would love to know what you think! The slide deck and full video links are below.

Erika Shorten

61,317 次观看 • 1 年前

Introducing autoresearch for GitHub repos Change 'Github' to 'ARGithub' in any repo URL Research artifacts extend beyond papers. Autoresearch is especially useful for experimenting on existing codebases that move fast and outpace their own publications. With one URL change you can now deploy an agent to orient itself on the codebase, resolve setup issues, and iterate on experiments.

Introducing autoresearch for GitHub repos Change 'Github' to 'ARGithub' in any repo URL Research artifacts extend beyond papers. Autoresearch is especially useful for experimenting on existing codebases that move fast and outpace their own publications. With one URL change you can now deploy an agent to orient itself on the codebase, resolve setup issues, and iterate on experiments.

alphaXiv

72,227 次观看 • 1 个月前

The State of Claude Artifacts - August 2024 With Artifacts generally available across Claude dot ai and our mobile apps, I figured now is a good time to record a walkthrough of everything that you can do with Artifacts today. Artifacts has so much potential as a new UX paradigm - we're just scratching the surface of what it will eventually become. I have a feeling that when we look back at this video in the not-too-distant future, we'll be amazed at how quickly Artifacts evolved.

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Alex Albert

83,686 次观看 • 1 年前

New course: Build agents that respond to users with not only plaintext, but custom UIs like charts, forms, and whiteboards, generated on demand and displayed right in the chat. This short course is built in partnership with CopilotKit🪁 and taught by Atai Barkai, co-founder of CopilotKit. You'll learn three approaches: Your agent can pick from custom components you build, like charts and forms. It can compose new layouts from a set of building blocks you provide, like rows, cards, and text. Or it can incorporate existing third-party apps, like a whiteboard or a calendar, right inside the conversation. Skills you’ll gain: - Build agents that render custom components like charts and forms on demand - Build an app where the agent and user collaborate on shared data, beyond just the chat window - Place third-party apps like maps, calendars, and whiteboards right in your interface Join and build agents that give users something to see and act on!

New course: Build agents that respond to users with not only plaintext, but custom UIs like charts, forms, and whiteboards, generated on demand and displayed right in the chat. This short course is built in partnership with CopilotKit🪁 and taught by Atai Barkai, co-founder of CopilotKit. You'll learn three approaches: Your agent can pick from custom components you build, like charts and forms. It can compose new layouts from a set of building blocks you provide, like rows, cards, and text. Or it can incorporate existing third-party apps, like a whiteboard or a calendar, right inside the conversation. Skills you’ll gain: - Build agents that render custom components like charts and forms on demand - Build an app where the agent and user collaborate on shared data, beyond just the chat window - Place third-party apps like maps, calendars, and whiteboards right in your interface Join and build agents that give users something to see and act on!

Andrew Ng

211,218 次观看 • 2 个月前

you can make videos like this using AI. all you need are the right tools and prompts, and I’ll show you how to get them on freepik using Seedream 4 on this thread 🧵👇

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TechHalla

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Fab

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TechHalla

48,256 次观看 • 7 个月前

Screen X seems like a neat idear but the movies shown aren’t made for it and you see a lot of weird CG artifacts that are meant to be off camera. But tbh those are cool in their own way.

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CamTheCan

295,022 次观看 • 3 个月前

For the first time we are fundamentally changing how humans can collaborate with ChatGPT since it launched two years ago. We’re introducing canvas, a new interface for working with ChatGPT on writing and coding projects that go beyond simple chat. Product and model features: 1/ Ask for in-line feedback. With canvas, ChatGPT can better understand the context of what you’re trying to accomplish. You can highlight specific sections to indicate exactly what you want ChatGPT to focus on. Like a copy editor or code reviewer, it can give in-line feedback and suggestions with the entire project in mind. 2/ Directly edit the model's output and select a specific area for targeted editing. You control your creative work on canvas. You can directly edit text or code. 3/ Menu of shortcuts. There’s a menu of shortcuts for you to ask ChatGPT to adjust writing length, debug your code, and quickly perform other useful actions. You can also restore previous versions of your work by using the back button in canvas. 4/ Use search with canvas for research writing! As we are moving towards the new paradigm of reasoning we are fundamentally evolving the chat interface into a more collaborative human-AI interaction. Today you can say “browse / use browsing to find XYZ on the internet and write a report in canvas”

For the first time we are fundamentally changing how humans can collaborate with ChatGPT since it launched two years ago. We’re introducing canvas, a new interface for working with ChatGPT on writing and coding projects that go beyond simple chat. Product and model features: 1/ Ask for in-line feedback. With canvas, ChatGPT can better understand the context of what you’re trying to accomplish. You can highlight specific sections to indicate exactly what you want ChatGPT to focus on. Like a copy editor or code reviewer, it can give in-line feedback and suggestions with the entire project in mind. 2/ Directly edit the model's output and select a specific area for targeted editing. You control your creative work on canvas. You can directly edit text or code. 3/ Menu of shortcuts. There’s a menu of shortcuts for you to ask ChatGPT to adjust writing length, debug your code, and quickly perform other useful actions. You can also restore previous versions of your work by using the back button in canvas. 4/ Use search with canvas for research writing! As we are moving towards the new paradigm of reasoning we are fundamentally evolving the chat interface into a more collaborative human-AI interaction. Today you can say “browse / use browsing to find XYZ on the internet and write a report in canvas”

Karina

845,627 次观看 • 1 年前