I vibecoded a 35k LoC recipe app
Over the last 2-3 weeks, I vibecoded the recipe app that I always wished existed - recipeninja.ai . It now includes a fully interactive voice assistant so you don't need to get your dirty hands over your new iPad when you're cooking. Background: I’m a startup founder turned investor. I taught myself (bad) PHP in 2000, and picked up Ruby on Rails in 2011. I’d guess 2015 was the last time I wrote a line of Ruby professionally. Last month, I decided to use Windsurf to build a Rails 8 API backend and React front-end app, using OpenAI's realtime API for voice-to-voice responses. Over the last few…
In plain words
RecipeNinja.ai is a recipe application built with a Rails 8 backend and React frontend that features a fully interactive voice assistant powered by OpenAI's realtime API. Users can interact with the app entirely through voice commands without needing to use their hands while cooking, making it suitable for kitchen use on tablets or other devices. The voice assistant uses function-calling to navigate the application in real-time as users chat, allowing hands-free browsing and recipe interaction.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Over the last 2-3 weeks, I vibecoded the recipe app that I always wished existed - recipeninja.ai . It now includes a fully interactive voice assistant so you don't need to get your dirty hands over your new iPad when you're cooking. Background: I’m a startup founder turned investor. I taught myself (bad) PHP in 2000, and picked up Ruby on Rails in 2011. I’d guess 2015 was the last time I wrote a line of Ruby professionally. Last month, I decided to use Windsurf to build a Rails 8 API backend and React front-end app, using OpenAI's realtime API for voice-to-voice responses. Over the last few days, I also used Claude Code and Gemini 2.5 Pro for some of the trickier features. 35,000 LoC later, this is what I built! The site uses function-calling to navigate the site in realtime as you chat with the voice assistant, which I think is pretty neat. For the long version, see https://tomblomfield.com/post/778601470234918912/vibecoding-... I'd love any feedback you have! Demo video of the voice assistant: https://www.youtube.com/watch?v=kRhVc9D5kcg Generate and edit new recipes: https://www.youtube.com/watch?v=VwwZF6dHcHg
More ai this month
the category →
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 · 26d ago · cactuscompute.com
Launched alongside, April 2025
the whole month →- IB
Hi everyone, I built PyXL — a hardware processor that executes a custom assembly generated from Python programs, without using a traditional interpreter or virtual machine. It compiles Python -> CPython Bytecode -> Instruction set designed for direct hardware execution. I’m sharing an early benchmark: a GPIO test where PyXL achieves a 480ns round-trip toggle — compared to 14-25 micro seconds on a MicroPython Pyboard - even though PyXL runs at a lower clock (100MHz vs. 168MHz). The design is stack-based, fully pipelined, and preserves Python's dynamic typing without static type restrictions.…
Dev tools · 2025 · runpyxl.com
- UC
Life & fun · 2025 · filiph.github.io
- IB
https://the-pocket.github.io/Tutorial-Codebase-Knowledge/
AI · 2025 · github.com
