The best Hacker News stories from Show from the past week
Latest posts:
Show HN: Watch bots interact with an SSH honeypot in real time
Show HN: Watch bots interact with an SSH honeypot in real time
Show HN: Firefox in WebAssembly
This is the entire Firefox browser rendering to a <canvas> element. Gecko, all UI components, and the Spidermonkey JS engine are all compiled and running in WebAssembly.<p>Here are a few things you might find interesting:<p>- This is fully end to end encrypted! We use the WISP protocol for TCP-over-websockets.<p>- There is a novel WASM->JS JIT for experimental site speedup<p>- This port cost over 25k in opus/fable tokens for debugging and JIT research<p>This was just a fun experiment to push the boundaries of WebAssembly. For a more usable "browser in browser" experience, we also built <a href="https://github.com/HeyPuter/browser.js" rel="nofollow">https://github.com/HeyPuter/browser.js</a> that eats a bit less RAM.
Show HN: Opening lines of famous literary works
This came from an idea that had been knocking around in my head for several years. I had been collecting opening lines of famous works and thought it would be cool to see one everyday as I opened the browser. I tried different styles but landed on the simple background with the text, let the words speak for themselves. Over time i've added more quotes I believe now there are close to 60, so hopefully you can refresh a few times and get a fresh one every time. I hope you guys like it, enjoy!
Show HN: Juggler – an open-source GUI coding agent, by the creator of JUCE
Hello HN, I don't post on here much, but wanted to get some eyes on a new project I'm just launching. I think we definitely need one more AI code agent..<p>I'm a long-term C++ dev, and over 30+ years I've created some successful audio dev tools (JUCE, the Tracktion DAW, the Cmajor DSP language). All of these came from me getting annoyed with something I had to use, and deciding to have a go at my own take on whatever it was.<p>So Juggler is my attempt at an AI code agent, after spending too many hours loving what the models could do, but hating the CLI experience, and having some opinions of what a better UX might be for this stuff.<p>Lots more blurb on the website and github, but a quick tech dump which might grab your attention if you're into these things:<p>A session is a document, not a log file. Each conversation is a Yjs CRDT tree. It can branch into sub-threads (recursively), and you can drill down, backtrack, edit, undo/redo, and inspect everything: tool calls, approvals, and the raw context JSON going to the model, etc. The UI is based around Finder-style Miller columns rather than a big doom-scroll, and is quick to navigate.<p>Because it's a CRDT behind a local web server, multiple clients can attach P2P to a live session: the native desktop app, a browser tab, or your phone. Run the headless server on the box where the code lives, view it from wherever.<p>Almost everything is a JavaScript plugin: every item in the context (read/write/bash/etc.), the LLM loop strategies, slash commands, and their UIs. You can inspect, fork, or replace any of them. I don't do much agent customisation myself, but lots of people do, and I'd love to see what they think of with this plugin API.<p>Go backend, Wails for windowing (no Electron), plain type-checked JS (strict JSDoc), Yjs for the documents. Usual BYOK provider support: Claude (CLI or API), OpenAI/Codex, Gemini, Ollama, OpenRouter, DeepSeek, etc.<p>The app's AGPLv3; the extension SDK and bundled extensions are Apache-2.0, so extensions have no copyleft strings attached. No signup, no telemetry, trying to make it frictionless for people to try it out..<p>It's very much a beta, and is a one-man side project. It hasn't yet had a proper kicking from the real world, but I'm confident some people with similar preferences to my own will like it!<p><a href="https://juggler.studio" rel="nofollow">https://juggler.studio</a>
Show HN: Clawk – Give coding agents a disposable Linux VM, not your laptop
Show HN: Super Dario
Show HN: Mindwalk – Replay coding-agent sessions on a 3D map of your codebase
Show HN: Mindwalk – Replay coding-agent sessions on a 3D map of your codebase
Show HN: Ant – A JavaScript runtime and ecosystem
Hello HN!<p>I'm the author of Ant, a JavaScript ecosystem built around a runtime with its own JavaScript engine. Ant also includes a package manager, the ants.land package registry, a platform for deploying and hosting applications, and Ant Desktop for building native desktop apps with web technologies, similar to Electron.<p>The goal is for these pieces to work as one coherent platform while remaining compatible with the wider JavaScript ecosystem. It's still early, and I'd appreciate any feedback on the overall direction or what you'd like to see from an e2e alternative to the existing JavaScript stacks.<p>P.S. I’ve shared Ant here before as a runtime; since then, it has grown into the broader ecosystem you see today.
Show HN: Yamanote.fun – A complete soundscape for Tokyo's Yamanote line
After visiting Japan for the first time a decade ago I became completely enamoured with Tokyo's Yamanote Line railway loop. Particularly the sonic experience of it. Like so many others I fell in love with the charming departure melodies and enjoyed discovering experiences like Yamanot.es (<a href="https://news.ycombinator.com/item?id=45045307">https://news.ycombinator.com/item?id=45045307</a>) here on Hacker News when I returned home.<p>But it wasn't until my second trip to Tokyo that I truly appreciated how much the door chimes, on-board announcements and train noise were contributing to the rich soundscape that I loved.<p>I returned home and found myself playing YouTube videos of Yamanote Line journeys as I worked. The combination of sonics, ambience and softly spoken Japanese was incredibly soothing to me.<p>But these recordings were often incomplete, poorly captured or out of date, and I wanted something far more comprehensive.<p>So I gathered up all of the constituent parts from Reddit threads, YouTube videos and Japanese fan sites, and set about recreating the experience of riding the Yamanote Line in Logic Pro X. Melody, door chimes and announcement, all stitched together under a bed of train noise and ambience.<p>I turned those soundscapes into an Alexa Skill (<a href="https://www.amazon.co.uk/Paul-Jackson-Yamanote-Line/dp/B07S18QRMV" rel="nofollow">https://www.amazon.co.uk/Paul-Jackson-Yamanote-Line/dp/B07S1...</a>) in 2019 and began to think about a companion website to share the soundscapes with a wider audience.<p>Seven years later and that website is Yamanote.fun: <a href="https://www.yamanote.fun/" rel="nofollow">https://www.yamanote.fun/</a>.<p>It's a small installable web app that plays the soundscapes like a playlist. All 30 stations and in both directions, since the inner and outer loops use different melodies. You can skip forward or back a station, and there's a scrub bar broken into melody / chime / ambience / announcement so you can jump straight to the bit you want. Each station has its own shareable link (yamanote.fun/jy13-ikebukuro-inner) that unfurls with the right station name and artwork when you share it.<p>It's a progressive web app too, so you can add it to your home screen and it behaves like a native app. There's an option to offline the audio too.<p>Under the hood it's relatively basic stuff: plain HTML, CSS & JS, audio served from Cloudflare R2 and the site hosted on Netlify. I was impressed to see how far I could get with the free tiers of these services. I designed the whole thing in Figma (I'm a Product Designer) and used Claude Code to architect and deliver the polished UI, PWA plumbing, offline caching and share-link infrastructure.<p>I would love feedback, particularly from anyone who's ridden the real thing.
Show HN: Getting GLM 5.2 running on my slow computer
A few days ago I found myself trying out GLM 5.2 and was really positively impressed. The capabilities and security I was getting from this LLM are similar to those I've gotten from models like Claude or GPT, and this really surprised me.<p>But then I thought, "I wonder how it would work on a normal computer like mine," and above all, "I wonder if it would work without going into OOM on a computer like mine." So I started working with the help of agents to test this possibility.<p>I started converting the model to int4, understanding MTP usage, and if possible implementing DSA for long context. How it responds in int4 and whether the quality is maintained or not. Until I got to the point, on my computer with 32GB of RAM, I was able to communicate with GLM 5.2 with times that, of course, aren't high in cold start, but even then, we're talking about 0.1 tok/s, but that wasn't important to me. The important thing was the journey to reach this goal. I just wanted it to work at all costs, even slowly.<p>So I created Colibrì, which was born from a very simple idea, to be honest, but tested in every way, where a 744B Mixture-of-Experts model activates only ~40B parameters per token—and only ~11 GB of those change from token to token (the routed experts). So:<p>The dense part (attention, shared experts, embeddings—~17B params) stays resident in RAM at int4 (~9.9 GB); The 21,504 routed experts (75 MoE layers × 256 experts + the MTP head, ~19 MB each at int4) live on disk (~370 GB) and are streamed on demand, with a per-layer LRU cache, an optional pinned hot-store, and the OS page cache as a free L2.<p>The engine is a single C file (c/glm.c, ~1,300 lines) plus small headers. No BLAS, no Python at runtime, no GPU.No GPU or serious hardware because I don't have that hardware so I can't test it on hardware that is more powerful than my computer.Colibrì is a one-person project, written and tested entirely on a 12-core laptop with 25 GB of RAM — the numbers above are the ceiling of what I can measure at home.<p>Any feedback is welcome! (and if anyone wanted to participate in the project I would be delighted)<p>Repo: <a href="https://github.com/JustVugg/colibri" rel="nofollow">https://github.com/JustVugg/colibri</a>
Show HN: Getting GLM 5.2 running on my slow computer
A few days ago I found myself trying out GLM 5.2 and was really positively impressed. The capabilities and security I was getting from this LLM are similar to those I've gotten from models like Claude or GPT, and this really surprised me.<p>But then I thought, "I wonder how it would work on a normal computer like mine," and above all, "I wonder if it would work without going into OOM on a computer like mine." So I started working with the help of agents to test this possibility.<p>I started converting the model to int4, understanding MTP usage, and if possible implementing DSA for long context. How it responds in int4 and whether the quality is maintained or not. Until I got to the point, on my computer with 32GB of RAM, I was able to communicate with GLM 5.2 with times that, of course, aren't high in cold start, but even then, we're talking about 0.1 tok/s, but that wasn't important to me. The important thing was the journey to reach this goal. I just wanted it to work at all costs, even slowly.<p>So I created Colibrì, which was born from a very simple idea, to be honest, but tested in every way, where a 744B Mixture-of-Experts model activates only ~40B parameters per token—and only ~11 GB of those change from token to token (the routed experts). So:<p>The dense part (attention, shared experts, embeddings—~17B params) stays resident in RAM at int4 (~9.9 GB); The 21,504 routed experts (75 MoE layers × 256 experts + the MTP head, ~19 MB each at int4) live on disk (~370 GB) and are streamed on demand, with a per-layer LRU cache, an optional pinned hot-store, and the OS page cache as a free L2.<p>The engine is a single C file (c/glm.c, ~1,300 lines) plus small headers. No BLAS, no Python at runtime, no GPU.No GPU or serious hardware because I don't have that hardware so I can't test it on hardware that is more powerful than my computer.Colibrì is a one-person project, written and tested entirely on a 12-core laptop with 25 GB of RAM — the numbers above are the ceiling of what I can measure at home.<p>Any feedback is welcome! (and if anyone wanted to participate in the project I would be delighted)<p>Repo: <a href="https://github.com/JustVugg/colibri" rel="nofollow">https://github.com/JustVugg/colibri</a>
Show HN: 18 Words
Show HN: 18 Words
Show HN: Follow London Trains in 3D
deck.gl based visualiser of the TFL Api + National Rails to be able to track (with minimal drift) a train along the way in London and to the nearest airports. If you pick one from any platform in <a href="https://nexttrain.london" rel="nofollow">https://nexttrain.london</a> basically you can share your train journey along the rails. Build to test Cloudflare workers and their infra along with deck.gl performance that is incredible in my opinion.
Show HN: Microsoft releases Flint, a visualization language for AI agents
Data visualizations are the bridge between user and data.<p>But building AI agents that can generate visualizations reliably can be very tricky:<p>- simple chart specs can be reliable, but generated charts are often of low quality due to reliance on system defaults;
- complex chart specs with explicit details can produce good-looking charts, but they are verbose and agents can struggle with reliability<p>We figured out it is a limitation on the language issue (not just AI capability thing) -- current visualization languages are a bit too low-level for AI agents, requiring them to explicitly make visual decisions that are supposed to be handled by a good compiler. Flint is a visualization intermediate language to address this issue, allow AI agents to solve this last-mile human-agent interaction problem. It provides a simple semantic-type based specification, and contains a layout optimization engine that can produce good-looking charts (filled with derived low-level details) from simple high-level specs. The result is also very human understandable and adaptable. Flint powers data formulator for generating visualizations (another open source project from microsoft <a href="https://data-formulator.ai/" rel="nofollow">https://data-formulator.ai/</a>).<p>Flint is available open source, and we built a MCP server that you can directly plug flint in your favorite agent app to play with data.
Show HN: Rowboat – Open-source, local-first alternative to Claude Desktop
Claude’s desktop app is brilliant, but for our own daily work we kept wanting it to be less like a chat app and more like a full-fledged work app. Rowboat is our attempt at that, including the ability to build your own work surfaces inside Rowboat (more below).<p>Our repo is <a href="https://github.com/rowboatlabs/rowboat" rel="nofollow">https://github.com/rowboatlabs/rowboat</a>, and there’s a demo video here: <a href="https://www.youtube.com/watch?v=et5yQABJ3xI" rel="nofollow">https://www.youtube.com/watch?v=et5yQABJ3xI</a><p>In a previous startup, we built a deep-learning product for enterprise support reps, including teams supporting P&G brands. Models took live notes, suggested replies, and recommended actions while support reps were on calls or handling emails. One lesson stuck with us: it's not enough for the AI to be right, the help has to show up where the work is happening.<p>So we added what we came to call “work surfaces”: dedicated areas for email, meetings, notes, browser, and parallel coding, where the assistant can help inside the workflow itself rather than only through chat:<p>- Email client: Rowboat has a simple email client that sorts incoming emails into important vs. everything else, and pre-creates drafts for important emails. As you edit and send emails, it takes notes on your style, so future drafts get closer to your voice.<p>- Meeting notes: We built a Granola-style local meeting notetaker. Notes are stored as plain Markdown files on your machine. After a meeting, Rowboat feeds the notes back into the knowledge graph and updates the relevant people, project, and topic notes.<p>- Browser: We added a built-in browser, isolated from your main one, where you can log in only to the accounts you want the assistant to help with. The assistant uses browser-use skills to navigate websites.<p>- Parallel coding: The code-mode inside Rowboat lets you spin multiple instances of Claude Code or Codex and either work with them directly or let Rowboat use your work context to orchestrate them. We built an ACP (Agent Client Protocol) client in Rowboat for this.<p>- Notes: Rowboat has an Obsidian-style local note-taking system. It comes with graph view, bases view, and voice notes. You can also sync Google Docs files and edit them inside Rowboat.<p>You can also build your own work surfaces inside Rowboat (web apps). Each app gets its own UI and a background agent, and can use all of Rowboat's tools, product integrations, and your work memory. For instance: an app to manage GitHub activity, project tracking, or ads campaign management. There are a few community apps at launch you can search and install, and you can publish your own by creating a GitHub repo for it and registering it.<p>Rowboat also indexes your work into a knowledge graph that all of the above surfaces use to have better context. We did a Show HN a few months back on this: <a href="https://news.ycombinator.com/item?id=46962641">https://news.ycombinator.com/item?id=46962641</a>.<p>As an example that ties some of these together: you can create an app inside Rowboat that collects feature requests from your email, meetings, and Slack and ranks them, then uses Claude Code to draft a first version of the top-ranked feature, pulling prior context about it from your knowledge graph.<p>Rowboat is local-first: data is stored as plain Markdown files you can read, edit, or delete anytime. It is Apache-2.0 and works with any LLM, including local models through Ollama or LM Studio.<p>We’d love to hear your thoughts, and contributions are welcome!
Show HN: Davit, a Apple Containers UI
Mostly vibe-coded Apple Containers front-end that I'd like to use myself. But if others want to use it, here's the source code.
Show HN: Homegames. An open-source game platform I've been making for 8 years
I'm making a platform for simple open source games you can play anywhere.<p>Games are all just JavaScript classes and you can read the source of every game on the platform.<p>I started working on initial "games" (mostly rendering tests) in 2018 and eventually built all of the platform stuff around it to make it easy to share games.<p>There's also an in-browser editor available for you to make and publish games all from the browser.<p>Would love some feedback on the games and studio features as well as the platform overall. All of the code is available at <a href="https://github.com/homegamesio" rel="nofollow">https://github.com/homegamesio</a>