GitByBit
GitByBit is an interactive course that teaches you Git by practice right in your code editor. You follow bite-sized instructions, run real Git commands in the terminal or click through your editor’s Git interface, and the course verifies what happened. When something breaks, it tells you why and how to get unstuck. It's well-designed and illustrated.
FluidCAD
Hello HN users, This is a CAD by code project I have been working on on my free time for more than year now. I built it with 3 goals in mind: - It should be familiar to CAD designers who have used other programs. Same workflow, same terminology. - Reduce the mental effort required to create models as much as possible. This is achieved by: - Provide live rendering and visual guidance as you type. - Allow the user to reference existing edges/faces on the scene instead of having to calculate everything. - Provide interactive mouse helpers for features that are hard to write by code: Only 3 interactive modes for now: Edge trimming, Sketch region extrude, Bezier curve drawing. - Implicit coding whenever possible: e.g: There are sensible defaults for most parameters. The program will automatically fuse intersecting objects together so you do not have to worry about what object needs to be fused with what. - It should be reasonably fast: The scene objects are cached and only the updated objects are re-computed. I think I have achieved these goals to a good extent. The program is still in early stages and there are many features I want to add, rewrite but I think it is already usable for simple models. Update to add more details: This is based on Opencascade.js WASM binding. So you get all the good things that come with any brep kernel. Fillets, chamfers, step import and export... The scene is webview but the editing is in your local file. You use your own editor and the environment you are familiar with. One important feature that I think make this stand out among other code based cad software is the ability to transform features not just shapes. More here: https://fluidcad.io/docs/guides/patterns You can see it in action in the lantern example: https://fluidcad.io/docs/tutorials/lantern
A WYSIWYG word processor in Python
Hi all, Finding a good data structure for a word processor is a difficult problem. My notebook diaries on the problem go back 25 years when I was frustrated with using Word for my diploma thesis - it was slow and unstable at that time. I ended up getting pretty hooked on the problem. Right now I’m taking a professional break and decided to finally use the time to push these ideas further, and build MiniWord — a WYSIWYG word processor in Python. My goal is to have a native, non-HTML-based editor that stays simple, fast, and is hackable. So far I am focusing on getting the fundamentals right. What is working yet is: - Real WYSIWYG editing (no HTML layer, no embedded browser) with styles, images and tables. - Clean, simple file format (human-readable, diff-friendly, git-friendly, AI-friendly) - Markdown support - Support for Python-plugins Things that I found: - B-tree structures are perfect for holding rich text data - A simple text-based file format is incredibly useful — you can diff documents, version them, and even process them with AI tools quite naturally What I’d love feedback on: - Where do you see real use cases for something like this? - What would be missing for you to take it seriously as a tool or platform? - What kinds of plugins or extensions would actually be worth building? Happy about any thoughts — positive or critical. Greetings
I built a site that shows every world event you lived through
Show HN: I built a site that shows every world event you lived through
Keyboard First Email Client
My email clients/inbox really fu*ing annoyed me. Tallyman is what happened next: a keyboard driven email client on top of Gmail and Outlook. Your vim muscle memory works (j/k, gg, relative line numbers, counts, ...) 39 rebindable shortcuts, command palette, email templates, themes ... No migration. OAuth only. Verified by Microsoft and live now. Google verification is under review. 30 day free trial, $9/mo per inbox after that. Write me an email if you need an extended trial: contact@tallyman.io
I'm organizing a vibe coding game dev competition
Hi everyone, I just saw a vibe coded game on HN, and thought maybe I should post about this here. I'm organizing a vibe coding game dev competition called Vibe Jam. Last year we did it too and there was 1000+ games submitted. This year the deadline is May 1 and you can submit your games until then. There's $35,000 in prizes with the Gold prize being $20,000. Let me know what you think! -Pieter
Oberon System 3 runs natively on Raspberry Pi 3 (with ready SD card)
Show HN: Oberon System 3 runs natively on Raspberry Pi 3 (with ready SD card)
boringBar
Hi HN! I recently switched from a Fedora/GNOME laptop to a MacBook Air. My old setup served me well as a portable workstation, but I’ve started traveling more while working remotely and needed something with similar performance but better battery life. The main thing I missed was a simple taskbar that shows the windows in the current workspace instead of a Dock that mixes everything together. I built boringBar so I would not have to use the Dock. It shows only the windows in the current Space, lets you switch Spaces by scrolling on the bar, and adds a desktop switcher so you can jump directly to any Space. You can also hide the system Dock, pin apps, preview windows with thumbnails, and launch apps from a searchable menu (I keep Spotlight disabled because for some reason it uses a lot of system resources on my machine). I’ve been dogfooding it for a few months now, and it finally felt polished enough to share. It’s for people who like macOS but want window management to feel a bit more like GNOME, Windows, or a traditional taskbar. It’s also for people like me who wanted an easier transition to macOS, especially now that Windows feels increasingly user-hostile. I’d love feedback on the UX, bugs, and whether this solves the same Dock/Spaces pain for anyone else. P.S. It might also appeal to people who feel nostalgic for the GNOME 2 desktop of yore. I started my Linux journey with it, and boringBar brings back some of that feeling for me.
ParseBench
Show HN: ParseBench – Document parsing benchmark for AI agents
Turn your favorite YouTube channels into a streaming experience
A minimalist way to watch YouTube with cinematic previews, an immersive interface, and zero distractions. Free, no accounts or subscription needed.
Ithihāsas
Hi HN! I’ve always found it hard to explore the Mahābhārata and Rāmāyaṇa online. Most content is either long-form or scattered, and understanding a character like Karna or Bhishma usually means opening multiple tabs. I built https://www.ithihasas.in/ to solve that. It is a simple character explorer that lets you navigate the epics through people and their relationships instead of reading everything linearly. This was also an experiment with Claude CLI. I was able to put together the first version in a couple of hours. It helped a lot with generating structured content and speeding up development, but UX and data consistency still needed manual work. Would love feedback on the UX and whether this way of exploring mythology works for you.
Kelet
I've spent the past few years building 50+ AI agents in prod (some reached 1M+ sessions/day), and the hardest part was never building them — it was figuring out why they fail. AI agents don't crash. They just quietly give wrong answers. You end up scrolling through traces one by one, trying to find a pattern across hundreds of sessions. Kelet automates that investigation. Here's how it works: 1. You connect your traces and signals (user feedback, edits, clicks, sentiment, LLM-as-a-judge, etc.) 2. Kelet processes those signals and extracts facts about each session 3. It forms hypotheses about what went wrong in each case 4. It clusters similar hypotheses across sessions and investigates them together 5. It surfaces a root cause with a suggested fix you can review and apply The key insight: individual session failures look random. But when you cluster the hypotheses, failure patterns emerge. The fastest way to integrate is through the Kelet Skill for coding agents — it scans your codebase, discovers where signals should be collected, and sets everything up for you. There are also Python and TypeScript SDKs if you prefer manual setup. It’s currently free during beta. No credit card required. Docs: https://kelet.ai/docs/ I'd love feedback on the approach, especially from anyone running agents in prod. Does automating the manual error analysis sound right?