Hacker News

This is a project that spun from my frustrations of using LocalSend and DashBeam to transfer stuff between devices, and with the extra goal of being fast, trying out the Slint framework and, most importantly, establishing a communication channel with trusted external people that can be left always on.

But how? How does it all work? I proposed we just do it the Ratatui way, but my friend was like, nah! We shall make it possible to build TUIs in Lua. (Weirdo!) But it paid off, and we got ourselves a shiny new Lua library, ito!!!

He didn't get the gravity of the situation. We had an awesome terminal UI library in Lua! I wanted everyone to know how cool that is, so I got cooking, wrote myself a custom canvas implementation of this library instead of the usual terminal adaptor, exported it as wasm, and made this super cool website where you can experiment building awesome UIs in Lua. For vibe-coders, we got an llms.txt too. Have at it, and see if you can build something really cool with it. The library's at github.com/uji-labs/ito, and the awesome sauce harness is at github.com/uji-labs/uji.

I hope you like it!

I’m Jason Thomas, one of the founders of CoScreen.

As some of you may know, Datadog sunset the CoScreen service on July 31st.

Four of us from the original CoScreen team have spent the last couple months building a free and open source pair programming tool inspired by those that came before us: It’s called Petal (https://github.com/kiruna-labs/petal)

Some history first, because when we started CoScreen we had hoped to break the sad and established pattern of this industry.

Screenhero was an exceptional tool that a lot of us loved for pairing. Multiple cursors, low latency, you could click your partner’s editor, and just start typing. It felt like magic while we had it. Then Slack bought it in 2015, and shut down the standalone app in December 2017.

When Till, Max, and I started CoScreen, we were aware of this history, and wanted to build an even more magical collaboration and screen sharing experience: the entire concept was “throw a window from your laptop up on someone else’s screen, and start collaborating with zero friction.”

Datadog acquired us in 2022, and thus began the great adventure of adapting our real-time technology into Datadog products, while also continue developing CoScreen as a standalone tool from the Datadog ecosystem. Datadog invested in the product for years and we’re thankful for that. But CoScreen itself proved, like so many other screen sharing tool acquisitions, to be too tangential from the customer base and core mission. We instead built other communication features in Datadog, the integrations with other video platforms, and also its wildly successful MCP server. We weren't the only ones. Around was bought by Miro and shut down in March 2025. Multi (formerly Remotion) was acqui-hired by OpenAI in 2024 and shut down about a month later. It's nearly always the same story: a small team builds something hard that people love, a platform buys it for the team or the feature, and the standalone product doesn't survive the integration. So we decided firmly to do things differently this time. Petal is completely free and open source and we aren't monetizing it. If we lose interest or get hit by a bus, you can self-host it or fork it, and nobody can sunset it on you. Honestly it's a love letter to everyone in this community that supported us, believed in us, and to liberate collaborative screen sharing from this vicious cycle.

We hope through this we can help foster a large and vibrant community around innovating in this product sector. What Petal does: shared windows show up as real windows on your desktop, movable and resizable, not tiles in a grid. Several people can share at once, everyone gets a labeled cursor, and you can click into any shared window to type and scroll. Rooms are persistent, so you click once to join "eng-sync" instead of passing links around. It runs on macOS and Windows (Linux is next, this time for real and you can help us!), plus a web app. Media goes over LiveKit. You can use our hosted instance with zero config, or point the app at your own LiveKit server with one docker-compose if you want the traffic to stay on your network or even use an entirely different video backend if you want to. The part that still feels strange to us: CoScreen took almost six years to build. The first version of Petal took under eight weeks, from scratch, with frontier models like Fable and Astra doing a lot of the work. Real-time video and window capture is some of the most unforgiving code we have ever written, so we didn't expect that. We will do a proper writeup on what worked and what didn't, and are happy to answer questions about it here. Till, Darren, Max and I will be in the thread.

I'd guess that's what the DMA API is for and drivers shouldn't be doing cache maintenance by hand, but I'm not a kernel dev, so maybe I'm missing something.

I’m a hobbyist woodworker. I manually design simple things in Shapr3d with a lot of patience when I build things. I wonder in the time of LLMs if there is an effective way to accelerate the 3D model design using AI.. Anybody tried using AI to model wood projects? Any tools to recommend?

A good friend was visiting from Orlando over the summer and told me she was struggling to decide what to plant in her own yard despite her landlord being ok with it. That was enough of an excuse for me to kick off work on Indigene, which is aimed at giving folks just-in-time knowledge about what to plant based on their locale, sun exposure, soil conditions, and their own ecosystem support goals.

Candidly, as many of us have, I've also leaned heavily on LLMs (mostly Claude here) to bring this to life. Largely to avoid saying demonstrably false things, which might be an absurd statement. You can find the GitHub repository[2] a wild array of open data sources I've dug out and cross-referenced to ensure mistakes and hallucinations are unlikely to survive for long. But given today's Indigenous Peoples Day I figured it was past time I shared the projects and invited more scrutiny.

Being the Keep a Changelog guy, you can bet it has extensive release notes[3] generated from the project changelog. Those are also parsed into feature-specific guides so each also lists relevant recent updates.

Lastly, I put together a post[5] that goes into a bit more detail on the story of the project and what I've learned along the way.

I really, really hope people here (and beyond) find it as useful and enlightening as I do.

PS: before it comes up, all the LLM usage for the project is documented[6] and used as warning system in every PR but I think there's a lot more I can do to further reduce it

[1]: https://news.ycombinator.com/item?id=49192566

[2]: https://github.com/olivierlacan/indigene

[3]: https://indigene.app/release-notes/

[4]: https://indigene.app/guide/

[5]: https://constantvariable.net/blog/2026/indigene-native-plant...

[6]: https://indigene.app/llm/