Загрузка видео...

Не удалось загрузить видео

Возникла проблема при загрузке этого видео. Это может быть связано с временными проблемами сети или видео может быть недоступно.

На главную

A prototype from a BloomTech AI student: This multi-agentic system writes React components in their entirety (within the context of the company code base.) Generates fully-formed React/JavaScript + CSS + unit tests + Documentation, completely automatically.

Austen Allred

474,138 subscribers

36,185 просмотров • 2 лет назад •via X (Twitter)

Наука и технологии

Anya Rossi• Live Now

Private livecam show

Комментарии: 8

Фото профиля Austen Allred

Austen Allred2 лет назад

In the past few weeks the company used it to generate 290 unique React components. 22 of the 290 (7.6%) were rejected (or recreated) for bad structure, bad prompt, or overly complicated code. After including time for touch-up, the company estimates it saved 205 hours of developer time so far. At a mean cost of $.57/component.

Фото профиля Austen Allred

Austen Allred2 лет назад

By the way, this methodology works on all aspects of a code base, as well as on aspects of products that aren’t code at all. To learn how:

Фото профиля FBIVANWIFI

FBIVANWIFI2 лет назад

Brilliant to use a vector to store acceptable models to feed the prompt pre-execution. Never would have thought to use that!

Фото профиля Amir Bagheri

Amir Bagheri2 лет назад

All these models will disappear and eaten up alive by big-techs. Look what happened to all these AI startups.

Фото профиля Austen Allred

Austen Allred2 лет назад

These are big tech models…

Фото профиля shree

shree2 лет назад

why is this called multi agentic? is the bar for an agent, a python script which calls openai apis?

Фото профиля Austen Allred

Austen Allred2 лет назад

Huh? He used RAG to build a vector data store of various aspects of the code base and docs, and the data is passing between multiple fine-tuned agents.

Фото профиля Julian Schoen

Julian Schoen2 лет назад

very cool!

Похожие видео

Cool student project from this: An AI agent that looks at code, commit messages, and context from the project management system. Then automatically writes out a detailed, human-friendly description of everything that changed and what that means for customers.

Cool student project from this: An AI agent that looks at code, commit messages, and context from the project management system. Then automatically writes out a detailed, human-friendly description of everything that changed and what that means for customers.

Austen Allred

22,526 просмотров • 2 лет назад

Introducing Bifrost, a tool that uses AI to turn anything from Figma into clean React code automatically. How it works: - Generates usable code for anything in Figma - Drops the code directly into your code editor - Learns how to structure code just like yours 1/4

Introducing Bifrost, a tool that uses AI to turn anything from Figma into clean React code automatically. How it works: - Generates usable code for anything in Figma - Drops the code directly into your code editor - Learns how to structure code just like yours 1/4

kartik

756,127 просмотров • 3 лет назад

we released our react package build an ai chat w/ interactive components in a few lines of code. add it to your app with: npx tambo full-send we support: - streaming for both messages and components - message history and message threads - state manage for generated components - suggested actions based on available components - component library that uses the react package the react package is open-source. server package will be open-sourced later this year.

we released our react package build an ai chat w/ interactive components in a few lines of code. add it to your app with: npx tambo full-send we support: - streaming for both messages and components - message history and message threads - state manage for generated components - suggested actions based on available components - component library that uses the react package the react package is open-source. server package will be open-sourced later this year.

Michael Magán

65,473 просмотров • 1 год назад

Meet Boxy, your new AI coding assistant 🤖 🧠 Has the full context of your project 🌱 Generates code in seconds 🔥 Refactors code from the UI 💬 Writes meaningful commit messages Read the full post or see the highlights below 👇

Meet Boxy, your new AI coding assistant 🤖 🧠 Has the full context of your project 🌱 Generates code in seconds 🔥 Refactors code from the UI 💬 Writes meaningful commit messages Read the full post or see the highlights below 👇

CodeSandbox

103,493 просмотров • 3 лет назад

Introducing proof of concept React Imgui! The name is a joke, but it is accurate enough. In the last few days I have been working on a prototype of React driving Dear ImGui using Static Hermes. The result is a fully native app written almost entirely in JavaScript, using unmodified React, typed JS, plus a very small amount of glue C++ code and unmodified Dear ImGui and Sokol. The actual renderer translating React into Dear ImGui is written entirely in typed JS using zero-cost FFI. Of course this wouldn't be possible without React's great design and flexibility. I find it really fascinating that I was able to take literally unmodified React, write a little extra JS, and get a functional fully native app so quickly. Of course everything is unoptimized, and prototype code quality, and who knows how buggy, but it seems to work well enough. Please, watch the video to see it in action. If there is interest, I will write a more detailed article.

Introducing proof of concept React Imgui! The name is a joke, but it is accurate enough. In the last few days I have been working on a prototype of React driving Dear ImGui using Static Hermes. The result is a fully native app written almost entirely in JavaScript, using unmodified React, typed JS, plus a very small amount of glue C++ code and unmodified Dear ImGui and Sokol. The actual renderer translating React into Dear ImGui is written entirely in typed JS using zero-cost FFI. Of course this wouldn't be possible without React's great design and flexibility. I find it really fascinating that I was able to take literally unmodified React, write a little extra JS, and get a functional fully native app so quickly. Of course everything is unoptimized, and prototype code quality, and who knows how buggy, but it seems to work well enough. Please, watch the video to see it in action. If there is interest, I will write a more detailed article.

Tzvetan Mikov

211,113 просмотров • 9 месяцев назад

React Server Components allow you to call your database directly from a component. And that's great... but how do we make sure this code never ever runs on the client?

React Server Components allow you to call your database directly from a component. And that's great... but how do we make sure this code never ever runs on the client?

Lee Robinson

177,038 просмотров • 2 лет назад

A record from one of the calendars under React Native Components built with Expo 🧙 I plan to build at least 10 apps this year, starting with @niceprompt v2 + the mobile app. The React Native Components UI library and templates will make this process much smoother (highly recommended). This year will be exciting! 🥳

A record from one of the calendars under React Native Components built with Expo 🧙 I plan to build at least 10 apps this year, starting with @niceprompt v2 + the mobile app. The React Native Components UI library and templates will make this process much smoother (highly recommended). This year will be exciting! 🥳

Erencan Arica

43,741 просмотров • 6 месяцев назад

The first open-source implementation of the paper that will change automatic test generation is now available! In February, Meta published a paper introducing a tool to automatically increase test coverage, guaranteeing improvements over an existing code base. This is a big deal, but Meta didn't release the code. Fortunately, we now have Cover-Agent, an open-source tool you can install that implements Meta's paper to generate unit tests automatically: I recorded a quick video showing Cover-Agent in action. There are two things I want to mention: 1. Automatically generating unit tests is not new, but doing it right is difficult. If you ask ChatGPT to do it, you'll get duplicate, non-working, and meaningless tests that don't improve your code. Meta's solution only generates unique tests that run and increase code coverage. 2. People who write tests before writing the code (TDD) will find this less helpful. That's okay. Not everyone does TDD, but we all need to improve test coverage. There are many good and bad applications of AI, but this is one I'm looking forward to make part of my life.

The first open-source implementation of the paper that will change automatic test generation is now available! In February, Meta published a paper introducing a tool to automatically increase test coverage, guaranteeing improvements over an existing code base. This is a big deal, but Meta didn't release the code. Fortunately, we now have Cover-Agent, an open-source tool you can install that implements Meta's paper to generate unit tests automatically: I recorded a quick video showing Cover-Agent in action. There are two things I want to mention: 1. Automatically generating unit tests is not new, but doing it right is difficult. If you ask ChatGPT to do it, you'll get duplicate, non-working, and meaningless tests that don't improve your code. Meta's solution only generates unique tests that run and increase code coverage. 2. People who write tests before writing the code (TDD) will find this less helpful. That's okay. Not everyone does TDD, but we all need to improve test coverage. There are many good and bad applications of AI, but this is one I'm looking forward to make part of my life.

Santiago

774,488 просмотров • 2 лет назад

over the weekend i built and shipped Sentra for our docs. we use Mintlify for documentation. the built-in assistant kept running into context issues. wrong answers, missing context, no citations. so we extended Sentra's capability to the docs site directly. now when you're reading Dodo Payments docs, you can ask Sentra questions right there. it pulls context from our entire documentation via RAG (the same contextmcp (completely opensource) + Pinecone vector search with reranking), generates grounded answers, and cites the exact doc pages. built as a single Cloudflare Worker serving both the widget and the chat endpoint. React widget bundled into one self-contained IIFE, mounted in Shadow DOM so it doesn't conflict with Mintlify's styles. OpenAI models routed through Cloudflare AI Gateway. Vercel's AI SDK for streaming and shadcn for beautiful chat components. live now at

over the weekend i built and shipped Sentra for our docs. we use Mintlify for documentation. the built-in assistant kept running into context issues. wrong answers, missing context, no citations. so we extended Sentra's capability to the docs site directly. now when you're reading Dodo Payments docs, you can ask Sentra questions right there. it pulls context from our entire documentation via RAG (the same contextmcp (completely opensource) + Pinecone vector search with reranking), generates grounded answers, and cites the exact doc pages. built as a single Cloudflare Worker serving both the widget and the chat endpoint. React widget bundled into one self-contained IIFE, mounted in Shadow DOM so it doesn't conflict with Mintlify's styles. OpenAI models routed through Cloudflare AI Gateway. Vercel's AI SDK for streaming and shadcn for beautiful chat components. live now at

Ayush Agarwal

18,001 просмотров • 20 дней назад

Alibaba just dropped an AI that doesn’t just write code. It runs it. Tests it. Fixes it. Until it actually works. Here’s what makes Qwen 3 Coder Next different: → Executes code, not just autocomplete → Runs tests automatically → Iterates until all tests pass → Handles multi-file repositories → Works fully offline This is a real coding agent, not a text generator. Save this video, you’ll rethink how coding gets done. Want the SOP? DM me. 💬

Alibaba just dropped an AI that doesn’t just write code. It runs it. Tests it. Fixes it. Until it actually works. Here’s what makes Qwen 3 Coder Next different: → Executes code, not just autocomplete → Runs tests automatically → Iterates until all tests pass → Handles multi-file repositories → Works fully offline This is a real coding agent, not a text generator. Save this video, you’ll rethink how coding gets done. Want the SOP? DM me. 💬

Julian Goldie SEO

20,956 просмотров • 5 месяцев назад

Something cool - had Devin build a React Native app with Expo and test it on my phone in real time AI writes code in the cloud, I scan a QR code, app shows up on my device with hot reload. No local dev environment needed! I can run parallel sessions from anywhere.

Something cool - had Devin build a React Native app with Expo and test it on my phone in real time AI writes code in the cloud, I scan a QR code, app shows up on my device with hot reload. No local dev environment needed! I can run parallel sessions from anywhere.

nader dabit

32,113 просмотров • 3 месяцев назад

had a lot of fun creating this social media web app. it taught me a lot: - many principles & best practices in react - how to manage complex code - the importance of components - an in-depth view on useState, useEffect, useContext & many other hooks

had a lot of fun creating this social media web app. it taught me a lot: - many principles & best practices in react - how to manage complex code - the importance of components - an in-depth view on useState, useEffect, useContext & many other hooks

Chisom Ozor

14,702 просмотров • 1 год назад

The best way to understand Agentic AI isn’t by reading about it -> it’s by using it. Meet OptimAI Persona Agentic System - where your AI becomes you: it writes how you speak, thinks how you think, and acts with context, memory, and awareness. 👉 Not a chatbot. A digital extension of yourself. The world will soon run on Agentic AI. Early users won’t just use it, they’ll shape it.

The best way to understand Agentic AI isn’t by reading about it -> it’s by using it. Meet OptimAI Persona Agentic System - where your AI becomes you: it writes how you speak, thinks how you think, and acts with context, memory, and awareness. 👉 Not a chatbot. A digital extension of yourself. The world will soon run on Agentic AI. Early users won’t just use it, they’ll shape it.

OptimAI Network

20,547 просмотров • 7 месяцев назад

CHINA JUST DROPPED AN AI CODING MODEL WITH A 1M CONTEXT WINDOW. And I connected it to Claude Code to see what it could actually do. Meet GLM-X Preview On paper, a few things immediately stood out: → 1M context window → Agentic coding capabilities → Works inside Claude Code → Designed for large-scale coding and reasoning workflows But specs don't matter much if the model can't deliver in practice. So I gave it a real-world task. THE TEST One prompt: > Build a modern AI lead generation dashboard using React and Tailwind CSS. Requirements: → Dark mode → Analytics dashboard → Lead table → Email outreach section → Responsive design → Production-ready component structure Instead of generating a few snippets, it planned the architecture, generated the dashboard components, created the Tailwind configuration, and walked through the implementation requirements. What impressed me most wasn't the code itself. It was how well it maintained context throughout the workflow. That's where a 1M context window starts becoming useful. Less time re-explaining requirements. Less context loss. More room for complex projects. The AI coding race is getting very interesting. And it's no longer just GPT, Claude, and Gemini competing for attention. Results from my test below 👇

CHINA JUST DROPPED AN AI CODING MODEL WITH A 1M CONTEXT WINDOW. And I connected it to Claude Code to see what it could actually do. Meet GLM-X Preview On paper, a few things immediately stood out: → 1M context window → Agentic coding capabilities → Works inside Claude Code → Designed for large-scale coding and reasoning workflows But specs don't matter much if the model can't deliver in practice. So I gave it a real-world task. THE TEST One prompt: > Build a modern AI lead generation dashboard using React and Tailwind CSS. Requirements: → Dark mode → Analytics dashboard → Lead table → Email outreach section → Responsive design → Production-ready component structure Instead of generating a few snippets, it planned the architecture, generated the dashboard components, created the Tailwind configuration, and walked through the implementation requirements. What impressed me most wasn't the code itself. It was how well it maintained context throughout the workflow. That's where a 1M context window starts becoming useful. Less time re-explaining requirements. Less context loss. More room for complex projects. The AI coding race is getting very interesting. And it's no longer just GPT, Claude, and Gemini competing for attention. Results from my test below 👇

Md Riyazuddin

31,199 просмотров • 1 месяц назад

Unit tests are essential, but it takes time to write them. Speed up your coding and boost productivity by letting AI Assistant write unit tests for you in #IntelliJIDEA! 🖱️ Right-click a method and choose “AI Actions | Generate Unit Tests” from the context menu. Select “Accept All” if you’re happy with the generated tests, “Specify” to add an additional prompt, or “Regenerate” to try again. #IntelliJIDEATips

Unit tests are essential, but it takes time to write them. Speed up your coding and boost productivity by letting AI Assistant write unit tests for you in #IntelliJIDEA! 🖱️ Right-click a method and choose “AI Actions | Generate Unit Tests” from the context menu. Select “Accept All” if you’re happy with the generated tests, “Specify” to add an additional prompt, or “Regenerate” to try again. #IntelliJIDEATips

IntelliJ IDEA, a JetBrains IDE

14,994 просмотров • 1 год назад

Google just killed every paid coding tool. Their new AI Studio destroys Cursor completely. Here's how to build React apps instantly: → Open Google AI Studio Build Mode → Type what you want to build → Watch it code everything automatically → Deploy to GitHub with one click → Share working apps instantly Features that crush the competition: • Angular + React support ✔ • GitHub integration ✔ • Real-time code preview ✔ • Gemini API built-in ✔ • Enterprise AI for $0 ✔ Save this thread, you'll build faster apps. Want the SOP? DM me. 💬

Google just killed every paid coding tool. Their new AI Studio destroys Cursor completely. Here's how to build React apps instantly: → Open Google AI Studio Build Mode → Type what you want to build → Watch it code everything automatically → Deploy to GitHub with one click → Share working apps instantly Features that crush the competition: • Angular + React support ✔ • GitHub integration ✔ • Real-time code preview ✔ • Gemini API built-in ✔ • Enterprise AI for $0 ✔ Save this thread, you'll build faster apps. Want the SOP? DM me. 💬

Julian Goldie SEO

188,249 просмотров • 9 месяцев назад

Building an Agentic Search System Building an agentic system is not too hard. Loops, function calling, tool execution, and the model. That's it! I show in this video how to build a search agent from scratch. ~350 lines of code!

Building an Agentic Search System Building an agentic system is not too hard. Loops, function calling, tool execution, and the model. That's it! I show in this video how to build a search agent from scratch. ~350 lines of code!

elvis

57,290 просмотров • 1 год назад

🚨 Electrical engineers are going to hate this. Someone just turned React into a circuit board factory. Write code. Get a real PCB manufactured and delivered to your door. It's called tscircuit. React for Electronics. No Altium. No $10,000/year licenses. No 6-month learning curve. You write React components. But instead of and , you write , , and . The same way you build a website. That's how you build a circuit board now. Here's what this thing actually does: → Design real circuit boards using TypeScript and React → Edit code in your IDE, watch the circuit update in real time → Auto-generates schematics, PCB layouts, and 3D previews from your code → Automatic part selection and bill of materials generation → Built-in autorouting algorithm for PCB traces → Export to Gerber files and send directly to a manufacturer → Online playground. Design circuits in your browser right now. Here's the wildest part: The creator wrote 40 lines of TypeScript. From that he got a full PCB, a schematic, and a 3D preview. Then he exported it, sent it to a manufacturer, and got a real working circuit board delivered. 40 lines of code. A real physical product. This is free. Write React. Get hardware. $20K+ in bounties already paid to contributors. 8 years in the making. 100% Open Source. MIT License.

🚨 Electrical engineers are going to hate this. Someone just turned React into a circuit board factory. Write code. Get a real PCB manufactured and delivered to your door. It's called tscircuit. React for Electronics. No Altium. No $10,000/year licenses. No 6-month learning curve. You write React components. But instead of and , you write , , and . The same way you build a website. That's how you build a circuit board now. Here's what this thing actually does: → Design real circuit boards using TypeScript and React → Edit code in your IDE, watch the circuit update in real time → Auto-generates schematics, PCB layouts, and 3D previews from your code → Automatic part selection and bill of materials generation → Built-in autorouting algorithm for PCB traces → Export to Gerber files and send directly to a manufacturer → Online playground. Design circuits in your browser right now. Here's the wildest part: The creator wrote 40 lines of TypeScript. From that he got a full PCB, a schematic, and a 3D preview. Then he exported it, sent it to a manufacturer, and got a real working circuit board delivered. 40 lines of code. A real physical product. This is free. Write React. Get hardware. $20K+ in bounties already paid to contributors. 8 years in the making. 100% Open Source. MIT License.

Nav Toor

380,460 просмотров • 3 месяцев назад