10x-React-Engineer, Generate Entire React Codebases with Llama 2
Hi HN, Yesterday I live streamed myself for 6 hours building this from scratch. It’s an AI agent that uses Llama 2 (so far the 13b chat model) to generate a full react codebase from a single prompt. It had a “dev loop” that iterates on your feedback and resolves dependencies. In the end it kinda worked and I got excited so wanted to post here haha. Long story short a viewer on my discord suggested I build in of these and I just had to look into how these work (inspired by GPT Engineer and AutoGPT) I wanted to work on a more specific downstream task so I focused on web dev. Llama 2 isn’t the…
In plain words
10x-React-Engineer is an AI agent that generates complete React codebases from a single text prompt using Llama 2. It includes a development loop that iterates on user feedback and resolves dependencies automatically. Designed for web developers, the tool aims to streamline React project generation, though the creator plans to explore fine-tuned models for improved results.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hi HN, Yesterday I live streamed myself for 6 hours building this from scratch. It’s an AI agent that uses Llama 2 (so far the 13b chat model) to generate a full react codebase from a single prompt. It had a “dev loop” that iterates on your feedback and resolves dependencies. In the end it kinda worked and I got excited so wanted to post here haha. Long story short a viewer on my discord suggested I build in of these and I just had to look into how these work (inspired by GPT Engineer and AutoGPT) I wanted to work on a more specific downstream task so I focused on web dev. Llama 2 isn’t the best option for this so I will look into utilizing a chat fine tuned starcoder or fine tune llama 2 myself for better results. In the end I spend only some compute units testing this 1000 times on a single gpu I had in Colab and has some pretty solid results for iterating in a fairly short amount of time. Going to build upon this more in the coming weeks (clean the code…). Let me know what you think! Livestream: https://www.youtube.com/live/6_sdnYDmUmo?feature=share
More ai this month
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com


Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com


Launched alongside, August 2023
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Lottielab▲871Create and ship lottie animations to sites and apps faster
Dev tools · 2023 · lottielab.com
- LC
Outlines is a Python library that focuses on text generation with large language models. Brandon and I are not LLM experts and started the project a few months ago because we wanted to understand better how the generation process works. Our original background is probabilistic, relational and symbolic programming. Recently we came up with a fast way to generate text that matches a regex (https://blog.normalcomputing.ai/posts/2023-07-27-regex-guide...). The basic idea is simple: regular expressions have an equivalent Deterministic-Finite Automaton (DFA) representation. We…
AI · 2023 · github.com