Stagewise – frontend coding agent for real codebases
Hey HN, we're Glenn and Julian, and we're building stagewise (https://stagewise.io), a frontend coding agent that inside your app’s dev mode and that makes changes in your local codebase. We’re compatible with any framework and any component library. Think of it like a v0 of Lovable that works locally and with any existing codebase. You can spawn the agent into locally running web apps in dev mode with `npx stagewise` from the project root. The agent lets you then click on HTML Elements in your app, enter prompts like 'increase the height here' and will implement the changes in…
In plain words
Stagewise is a frontend coding agent that runs locally within a developer's app during development. Users can click on HTML elements in their running web app and enter text prompts describing changes they want made, and the agent implements those modifications directly in the source code. It works with any framework and component library, launched via `npx stagewise` from a project's root directory. Stagewise is designed for developers who want AI-assisted frontend development in their existing codebases rather than starting from scratch.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hey HN, we're Glenn and Julian, and we're building stagewise (https://stagewise.io), a frontend coding agent that inside your app’s dev mode and that makes changes in your local codebase. We’re compatible with any framework and any component library. Think of it like a v0 of Lovable that works locally and with any existing codebase. You can spawn the agent into locally running web apps in dev mode with `npx stagewise` from the project root. The agent lets you then click on HTML Elements in your app, enter prompts like 'increase the height here' and will implement the changes in your source code. Before stagewise, we were building a vertical SaaS for logistics from scratch and loved using prototyping tools like v0 or lovable to get to the first version. But when switching from v0/ lovable to Cursor for local development, we felt like the frontend magic was gone. So, we decided to build stagewise to bring that same magic to local development. The first version of stagewise just forwarded a prompt with browser context to existing IDEs and agents (Cursor, Cline, ..) and went viral on X after we open sourced it. However, the APIs of existing coding agents were very limiting, so we figured that building our own agent would unlock the full potential of stagewise. Since our last Show HN (https://news.ycombinator.com/item?id=44798553), we launched a few very important features and changes: You now have a proprietary chat history with the agent, an undo button to revert changes, and we increased the amount of free credits AND reduced the pricing by 50%. We made a video about all these changes, showing you how stagewise works: https://x.com/goetzejulian/status/1959835222712955140/video/.... So far, we've seen great adoption from non-technical users who wanted to continue building their lovable prototype locally. We personally use the agent almost daily to make changes to our landing page and to build the UI of new features on our console (https://console.stagewise.io). If you have an app running in dev mode, simply `cd` into the app directory and run `npx stagewise` - the agent should appear, ready to play with. We're very excited to hear your feedback!
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Launched alongside, August 2025
the whole month →
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I built the world's most impractical 1000-pixel display and anyone in the world can draw on it. It draws a single pixel at a time and takes 30-60 minutes to complete a single image. Anyone can participate in the project by voting for the next image to be drawn, and submitting images. https://kilopx.com/
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- KT
Kitten TTS is an open-source series of tiny and expressive text-to-speech models for on-device applications. We are excited to launch a preview of our smallest model, which is less than 25 MB. This model has 15M parameters. This release supports English text-to-speech applications in eight voices: four male and four female. The model is quantized to int8 + fp16, and it uses onnx for runtime. The model is designed to run literally anywhere eg. raspberry pi, low-end smartphones, wearables, browsers etc. No GPU required! We're releasing this to give early users a sense of the latency and voices…
Dev tools · 2025 · github.com
- IW
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