Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

Recently Theo - t3.gg told me "TANSTACK Start will be the future of full-stack JS" so we went ahead and integrated Tidewave with it. Give your favorite coding agent access to TanStack's server logs, let it detect and fix error pages, and drive UI changes directly from the browser!

José Valim

55,245 subscribers

33,337 views • 6 months ago •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

The craft of engineering is rapidly changing. At Ramp, we built our own background coding agent to accelerate faster. We call it Inspect. It wrote 30% of merged frontend + backend PRs in the past week. It’s powered by OpenCode, Modal and Cloudflare Developers. It runs fully in the cloud, and starts in seconds, letting every builder work at the speed of thought, no setup required. Today, we’re open sourcing the full blueprint so anybody can build their own Inspect. Just give our spec to your current coding agent, and let it build your new favourite.

The craft of engineering is rapidly changing. At Ramp, we built our own background coding agent to accelerate faster. We call it Inspect. It wrote 30% of merged frontend + backend PRs in the past week. It’s powered by OpenCode, Modal and Cloudflare Developers. It runs fully in the cloud, and starts in seconds, letting every builder work at the speed of thought, no setup required. Today, we’re open sourcing the full blueprint so anybody can build their own Inspect. Just give our spec to your current coding agent, and let it build your new favourite.

Zach Bruggeman

802,543 views • 6 months ago

BREAKING 🚨: Google is preparing Gemini Agent prototype to perform your tasks on the web! It is likely to be powered by the recently released Computer User model and will be able to operate a browser and perform deep research. With great power comes responsibility 🤖

BREAKING 🚨: Google is preparing Gemini Agent prototype to perform your tasks on the web! It is likely to be powered by the recently released Computer User model and will be able to operate a browser and perform deep research. With great power comes responsibility 🤖

TestingCatalog News 🗞

119,790 views • 9 months ago

What if your model handled its own tuning? ⚙️ With NVIDIA TAO 7, just prompt your coding agent what you want in plain language and let it do the rest. • Agent skills plug into your coding agent and improve accuracy. • AutoML removes the guesswork from hyperparameters. LLM-guided tuning finds strong configs up to 2x faster. • Fine-tune any Hugging Face CV or VLM model on local NVIDIA GPUs. • Data enhanced fine-tuning helps your agent identify why the model fails, then fix it. Try TAO skills ➡️

What if your model handled its own tuning? ⚙️ With NVIDIA TAO 7, just prompt your coding agent what you want in plain language and let it do the rest. • Agent skills plug into your coding agent and improve accuracy. • AutoML removes the guesswork from hyperparameters. LLM-guided tuning finds strong configs up to 2x faster. • Fine-tune any Hugging Face CV or VLM model on local NVIDIA GPUs. • Data enhanced fine-tuning helps your agent identify why the model fails, then fix it. Try TAO skills ➡️

NVIDIA AI

41,902 views • 1 month ago

Hi friends 👋 We recently saw Raptor try to cover his campfire in the rain with his van. It didn’t quite work… but it was such a cool idea that we had to reward it. So we went ahead and implemented it - you can now keep campfire going with your van's help!🔥

Hi friends 👋 We recently saw Raptor try to cover his campfire in the rain with his van. It didn’t quite work… but it was such a cool idea that we had to reward it. So we went ahead and implemented it - you can now keep campfire going with your van's help!🔥

Outbound 🚐 Fishing Update OUT NOW!

352,171 views • 5 months ago

Really stoked that the Cursor team hooked me up with early access to cursor-agent. Soon you will be able to use it alongside Claude Code and Codex inside of Terragon!

Really stoked that the Cursor team hooked me up with early access to cursor-agent. Soon you will be able to use it alongside Claude Code and Codex inside of Terragon!

Sawyer Hood

38,749 views • 1 year ago

Okay, this is seriously cool. A team from Google DeepMind, including DeepMind Cofounder Shane Legg, published a paper "From AGI to ASI". In the paper, they include instructions for an AI agent to read along with you. You can open the paper in Codex's in-app browser and have GPT-5.5 read it with you and explain all the concepts. This is the future. AI agents will be part of the target audience, and help us to understand anything we want.

Okay, this is seriously cool. A team from Google DeepMind, including DeepMind Cofounder Shane Legg, published a paper "From AGI to ASI". In the paper, they include instructions for an AI agent to read along with you. You can open the paper in Codex's in-app browser and have GPT-5.5 read it with you and explain all the concepts. This is the future. AI agents will be part of the target audience, and help us to understand anything we want.

Dan McAteer

53,480 views • 1 month ago

LangGraph. CrewAI. Agno. Which one to pick? The good news is that this will not matter soon! Finally, we have a full picture of how the industry is solving this with just three open protocols that work across ALL frameworks. It's not about picking the best framework. Instead, it's about understanding how protocols create interoperability. The Agent Protocol Landscape shows how three complementary protocols are creating a universal language for Agents: > AG-UI (Agent-User Interaction): - The bi-directional connection between agentic backends and frontends. - This is how agents become truly interactive inside your apps, not just as chatbots, but collaborative co-workers. > MCP (Model Context Protocol): - The standard for how agents connect to tools, data, and workflows. > A2A (Agent-to-Agent): - The protocol for multi-agent coordination. - How agents delegate tasks and share intent across systems. These aren't competing standards. They're layers of the same stack and have handshakes with each other. So instead of building point-to-point integrations, you build to protocols. Moreover, you can integrate LangGraph, CrewAI, or Agno into the same frontend, without rewriting your UI logic. These protocols let everything work together. For instance: - Your LangGraph agent pulls data via MCP. - It delegates analysis to a CrewAI agent via A2A. - Results stream to your React app via AG-UI. - Users see real-time collaboration in your interface. This way, you can focus on building agent capabilities instead of integration mechanics. The protocols handle interoperability automatically. CopilotKit unifies this entire stack into one framework so you can build "Cursor for X" style apps without implementing each protocol from scratch. It gives you all three protocols, generative UI support, and production-ready infrastructure in one framework. I have shared this playbook in the replies! It breaks down handshakes, misconceptions, and real examples and shows exactly how to start building.

LangGraph. CrewAI. Agno. Which one to pick? The good news is that this will not matter soon! Finally, we have a full picture of how the industry is solving this with just three open protocols that work across ALL frameworks. It's not about picking the best framework. Instead, it's about understanding how protocols create interoperability. The Agent Protocol Landscape shows how three complementary protocols are creating a universal language for Agents: > AG-UI (Agent-User Interaction): - The bi-directional connection between agentic backends and frontends. - This is how agents become truly interactive inside your apps, not just as chatbots, but collaborative co-workers. > MCP (Model Context Protocol): - The standard for how agents connect to tools, data, and workflows. > A2A (Agent-to-Agent): - The protocol for multi-agent coordination. - How agents delegate tasks and share intent across systems. These aren't competing standards. They're layers of the same stack and have handshakes with each other. So instead of building point-to-point integrations, you build to protocols. Moreover, you can integrate LangGraph, CrewAI, or Agno into the same frontend, without rewriting your UI logic. These protocols let everything work together. For instance: - Your LangGraph agent pulls data via MCP. - It delegates analysis to a CrewAI agent via A2A. - Results stream to your React app via AG-UI. - Users see real-time collaboration in your interface. This way, you can focus on building agent capabilities instead of integration mechanics. The protocols handle interoperability automatically. CopilotKit unifies this entire stack into one framework so you can build "Cursor for X" style apps without implementing each protocol from scratch. It gives you all three protocols, generative UI support, and production-ready infrastructure in one framework. I have shared this playbook in the replies! It breaks down handshakes, misconceptions, and real examples and shows exactly how to start building.

Avi Chawla

30,762 views • 8 months ago

Introducing: Browser Use Box (bux). Your 24/7 personal agent box, powered by Browser Harness. ♞ We got tired of agents that vanish when you close the laptop. So we put them on a server. > 24/7 box that runs while you sleep > Real Chrome with persistent logins > Telegram baked in, text from anywhere I gave mine my email and a Telegram chat. It books flights, replies to LinkedIn and does my to-do list before I'm awake. Try it at ↓

Introducing: Browser Use Box (bux). Your 24/7 personal agent box, powered by Browser Harness. ♞ We got tired of agents that vanish when you close the laptop. So we put them on a server. > 24/7 box that runs while you sleep > Real Chrome with persistent logins > Telegram baked in, text from anywhere I gave mine my email and a Telegram chat. It books flights, replies to LinkedIn and does my to-do list before I'm awake. Try it at ↓

Larsen Cundric

293,159 views • 3 months ago

Alright, now that we know *what* an agent is, how does it actually work? When you ask for help on a task, the agent plans a series of steps and executes them directly in the application on your behalf, using the tools it has access to. Say you are booking a local service or trying to organize your inbox (which typically takes multiple steps): the AI model first plans how to achieve the task using its existing knowledge and then interacts with your inbox to execute the task. The agent will continue until it is confident the task has been successfully completed.

Alright, now that we know what an agent is, how does it actually work? When you ask for help on a task, the agent plans a series of steps and executes them directly in the application on your behalf, using the tools it has access to. Say you are booking a local service or trying to organize your inbox (which typically takes multiple steps): the AI model first plans how to achieve the task using its existing knowledge and then interacts with your inbox to execute the task. The agent will continue until it is confident the task has been successfully completed.

Google AI

22,487 views • 8 months ago

GNON Labs EchoChambers now supports the DuckAI Framework! EchoChambers supports both V1 and V2 of the OpenPond Network with future support for V2 planned as it continues to evolve. Users launching agents/swarms on OpenPond can now easily integrate their agents into EC to access our agent tooling and evals to improve the performance of their agents and see how their agents are measuring up! Additionally, OpenPond can pull data directly from EC to be integrated into various user experiences on thier platform. Powered by $GNON #Fuxwiththedux $DUCKAI

GNON Labs EchoChambers now supports the DuckAI Framework! EchoChambers supports both V1 and V2 of the OpenPond Network with future support for V2 planned as it continues to evolve. Users launching agents/swarms on OpenPond can now easily integrate their agents into EC to access our agent tooling and evals to improve the performance of their agents and see how their agents are measuring up! Additionally, OpenPond can pull data directly from EC to be integrated into various user experiences on thier platform. Powered by $GNON #Fuxwiththedux $DUCKAI

GNON Labs | △

39,628 views • 1 year ago

The boundaries of trading just disappeared. 🌐 You can now trade U.S. Stock Index Perpetual Contracts directly with USDT. No switching apps, no bank delays—just seamless access to global giants like $TSLA and $MSTR. Your crypto and your favorite stocks, all in one powerful account. The future of trading isn't divided; it's unified. Experience it now:

The boundaries of trading just disappeared. 🌐 You can now trade U.S. Stock Index Perpetual Contracts directly with USDT. No switching apps, no bank delays—just seamless access to global giants like $TSLA and $MSTR. Your crypto and your favorite stocks, all in one powerful account. The future of trading isn't divided; it's unified. Experience it now:

KuCoin

10,430 views • 4 months ago

Ant on his threes: "Let it fly. I told Steph I was working with him all summer. Big shoutout, big credit to him. He influenced me to be able to shoot the ball really well so I went back in the summer and started working on it once I left him and I got better at it"

Ant on his threes: "Let it fly. I told Steph I was working with him all summer. Big shoutout, big credit to him. He influenced me to be able to shoot the ball really well so I went back in the summer and started working on it once I left him and I got better at it"

Oh No He Didn't

796,609 views • 1 year ago

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:

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 views • 2 months ago

Return to the Spectrum of Intergalactic Happiness! This album is something we’ve been working on quietly for years and we’re so happy to finally be able to share with you. We will have more to say about it in the near future but for now we’ll give you the chance to listen to it

Return to the Spectrum of Intergalactic Happiness! This album is something we’ve been working on quietly for years and we’re so happy to finally be able to share with you. We will have more to say about it in the near future but for now we’ll give you the chance to listen to it

Zeds Dead

89,078 views • 1 year ago

i'm too stubborn to simply give up on the concept of Benji after almost 10 years(!!) of iterating on it with different stacks... 2018: graphql backend + react SPA 2019: made a react native app for 6 months 2020: gave up on it and wrote 3 years of using other bs tools and being grumpy about them 2023: rewrote it in blitz js (JUGE mistake) 2024: iterate on react native + PWA + RN pwa wrapper 2025: time for a rewrite to Zero To Shipped ⛴️ stack (but next js sucks for this kind of app, add api, mcp, cross platform app, and many other things 2026: i want it all actions INSTANT AND FAST AF and next js is the wrong tech choice for a mostly client app, so i'm starting a rewrite with TANSTACK + Convex + Better Auth it feels so snappy 😭 btw 99% of the customers abandoned it, there are like 3 ride or die fans but i know i can turn it around!!!! let /goal cook.

i'm too stubborn to simply give up on the concept of Benji after almost 10 years(!!) of iterating on it with different stacks... 2018: graphql backend + react SPA 2019: made a react native app for 6 months 2020: gave up on it and wrote 3 years of using other bs tools and being grumpy about them 2023: rewrote it in blitz js (JUGE mistake) 2024: iterate on react native + PWA + RN pwa wrapper 2025: time for a rewrite to Zero To Shipped ⛴️ stack (but next js sucks for this kind of app, add api, mcp, cross platform app, and many other things 2026: i want it all actions INSTANT AND FAST AF and next js is the wrong tech choice for a mostly client app, so i'm starting a rewrite with TANSTACK + Convex + Better Auth it feels so snappy 😭 btw 99% of the customers abandoned it, there are like 3 ride or die fans but i know i can turn it around!!!! let /goal cook.

kitze · supermac.io 🐦‍🔥

16,580 views • 2 months ago

been getting a lot of qs on how i vibe coded this demo. and the answer is: stop acting like a coder and start acting like a PM! my exact playbook👇 1. logic first ignore the UI/graphics. focus strictly on how it works. do a massive brain dump of every requirement into a plain txt file and drop it in your root folder. make it exhaustively detailed. 2. the stack · Nano Banana 2 (tiles/textures/3D refs) · Tripo AI (turning the 2D pics into actual 3D models) · Cursor + Opus 4.6 (doing the heavy lifting) · Netlify (deploy) 3. hire the AI PM feed your brain dump to an LLM. tell it to write a technical spec sheet like a senior PM would. drop that in the root too. 4. the scrum master have it break the entire project down into a markdown checklist by phases. notice we still haven't touched the codebase yet. that's the point. 5. let it cook go to your agent in Cursor and literally just prompt "Start Phase 1". test locally. bugs? tell it to fix. works? "Start Phase 2". loop this until you're done. Now you can focus on visuals, refine them with the agent. And yes, it can deploy it for you too if you give it perms. stop rushing to the editor. architect the idea and let the AI sweat the code. Open sourced repo in the qt post below

been getting a lot of qs on how i vibe coded this demo. and the answer is: stop acting like a coder and start acting like a PM! my exact playbook👇 1. logic first ignore the UI/graphics. focus strictly on how it works. do a massive brain dump of every requirement into a plain txt file and drop it in your root folder. make it exhaustively detailed. 2. the stack · Nano Banana 2 (tiles/textures/3D refs) · Tripo AI (turning the 2D pics into actual 3D models) · Cursor + Opus 4.6 (doing the heavy lifting) · Netlify (deploy) 3. hire the AI PM feed your brain dump to an LLM. tell it to write a technical spec sheet like a senior PM would. drop that in the root too. 4. the scrum master have it break the entire project down into a markdown checklist by phases. notice we still haven't touched the codebase yet. that's the point. 5. let it cook go to your agent in Cursor and literally just prompt "Start Phase 1". test locally. bugs? tell it to fix. works? "Start Phase 2". loop this until you're done. Now you can focus on visuals, refine them with the agent. And yes, it can deploy it for you too if you give it perms. stop rushing to the editor. architect the idea and let the AI sweat the code. Open sourced repo in the qt post below

TechHalla

70,060 views • 5 months ago

GITHUB JUST KILLED THE WORST PART OF VIBE CODING they shipped a free tool called Spec Kit and it already crossed 120,000 stars the fix is stupidly simple instead of tossing vague prompts at an agent and praying it doesn't wreck your project Spec Kit makes the AI write a full structured spec before it touches a single line of code it works through the problem first figures out what you want to build asks about the gaps lays out the project then it starts coding you get fewer insane bugs, cleaner output and results you can predict the flow looks like this: /constitution for your rules and standards /specify for what you want to build /clarify for the open questions before you start /plan for architecture and stack /tasks for the ordered work /implement to run it it plugs into Claude Code, Cursor, Copilot, Codex, Gemini CLI and 25+ other agents 120,000 stars, 10,000 forks, open source, shipped by GitHub itself learning to drive agents like this is most of what separates people getting hired as AI engineers from everyone still fighting their prompts

GITHUB JUST KILLED THE WORST PART OF VIBE CODING they shipped a free tool called Spec Kit and it already crossed 120,000 stars the fix is stupidly simple instead of tossing vague prompts at an agent and praying it doesn't wreck your project Spec Kit makes the AI write a full structured spec before it touches a single line of code it works through the problem first figures out what you want to build asks about the gaps lays out the project then it starts coding you get fewer insane bugs, cleaner output and results you can predict the flow looks like this: /constitution for your rules and standards /specify for what you want to build /clarify for the open questions before you start /plan for architecture and stack /tasks for the ordered work /implement to run it it plugs into Claude Code, Cursor, Copilot, Codex, Gemini CLI and 25+ other agents 120,000 stars, 10,000 forks, open source, shipped by GitHub itself learning to drive agents like this is most of what separates people getting hired as AI engineers from everyone still fighting their prompts

Atlas

500,090 views • 26 days ago

$Haha, let me tell you all about a particularly fun way to use Avante.nvim: ever since Avante.nvim fully supported ACP and full view, avante can also be used as a Coding Agent CLI! Moreover, you can utilize your well-familiar Vim UI/UX muscle memory and equip it with thousands of interesting Neovim plugins! All you need is: alias avante='nvim -c "lua vim.defer_fn(function()require(\"avante.api\").full_view_ask()end, 100)"'$

Haha, let me tell you all about a particularly fun way to use Avante.nvim: ever since Avante.nvim fully supported ACP and full view, avante can also be used as a Coding Agent CLI! Moreover, you can utilize your well-familiar Vim UI/UX muscle memory and equip it with thousands of interesting Neovim plugins! All you need is: alias avante='nvim -c "lua vim.defer_fn(function()require(\"avante.api\").full_view_ask()end, 100)"'

yetone

91,432 views • 11 months ago

“You want a show? I’ll give you a show.” Go see the The Running Man Movie on the biggest screen, large and loud. We had a wild adventure making this one and you get to enjoy it from the comfort of your cinema seat. Have a blast with it and let me know what you think. (And if you saw it more than once, let us know what you discovered on a second viewing.)

“You want a show? I’ll give you a show.” Go see the The Running Man Movie on the biggest screen, large and loud. We had a wild adventure making this one and you get to enjoy it from the comfort of your cinema seat. Have a blast with it and let me know what you think. (And if you saw it more than once, let us know what you discovered on a second viewing.)

edgarwright

17,712 views • 8 months ago