The best Hacker News stories from Show from the past week

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Show HN: Lathe – Use LLMs to learn a new domain, not skip past it

Hey HN!<p>Lathe is an experiment in using LLMs to teach me something new, instead of doing the work for me. It generates a hands-on, source-backed tutorial for any technical topic you want to learn. Then you work through it yourself by reading and typing the code by hand (<i>gasp</i>) in a local UI built for exactly that.<p>It's a Go CLI plus LLM agent skills (Claude Code / Cursor / Codex). You prompt something like "/lathe build a 3D slicer in Erlang", run `lathe serve` to spin up a local webapp, and read it in your browser. Every tutorial comes with the things that have made self-learning a pleasant experience for me in the past:<p>- table of contents that follows along as you scroll - side-notes that nudge you to think - exercises for the reader - sources backing up the content that you can use to take you deeper<p>To help make up for the lack of human brainpower behind the tutorial, you can also ask questions about the content, have another LLM verify the tutorial actually compiles and runs, or extend it with another part (no more "Part 4 of 6" that hasn't seen an update since 2021).<p>I didn't build lathe to replace human-written tutorials. I built lathe because I _love_ human-written tutorials, but wanted to learn technical domains where no good human-written tutorial exists yet (building a 3D slicer from scratch, making embedded Zig approachable, etc). There's a longer story in the README about how I got started with programming through PSP homebrew tutorials, and why losing that to LLMs bugged me enough to build this.<p>I'm not here to sell you anything (there's nothing close to a VC-backed startup here :D). It's an LLM, and its output is usually good but not perfect by any means. So far, my experience is that because you're the one typing and actually engaged, you catch the weird stuff (and I'm finding that pushing back on it is its own kind of learning). And yes, it's vibecoded, because it's low scope, low risk, and scratching a personal itch. I run it on Claude Code + macOS personally, other setups should work but I haven't been able to verify them yet.<p>If you can find resources to learn something that was written by a human, read that first. But Lathe is here to fill in the gaps when that isn't the case, and I hope it serves as an example where LLMs can help us think better, rather than less.<p>Repo: <a href="https://github.com/devenjarvis/lathe" rel="nofollow">https://github.com/devenjarvis/lathe</a><p>Would love your feedback if you decide to check it out!

Show HN: Lowfat – pluggable CLI filter that saved 91.8% of my LLM tokens

Hi HN, not sure if anyone would be interested, but just wanted to share that I've been maintaining my small tool called 'lowfat' that helps me filters some of my verbose CLI output. It's a single binary, works as an agent hook or a shell wrapper. It has a plugin system to customize filters per command.<p>The idea is pretty simple: agents don't need the full kubectl get -o yaml or any 10k-line dump to make decisions. So that lowfat sits in between, strips the noise, and passes through what matters. Here's my real report after 2 months of personal use:<p><pre><code> lowfat history --all lowfat plugin candidates ───────────────────────────────────────────────────────── # command runs avg raw cost savings source status 1 kubectl get 101x 14.4K 1.5M 93.9% plugin good 2 grep 103x 13.5K 1.4M 96.2% plugin good 3 git diff 81x 995 80.6K 57.9% built-in good 4 kubectl 90x 485 43.6K 33.6% plugin good 5 docker 127x 5.5K 693.6K 96.1% built-in good 6 ls 489x 117 57.3K 56.2% built-in good 7 find 30x 16.5K 495.0K 95.5% plugin good 8 git show 63x 490 30.9K 38.0% built-in good 9 git 177x 368 65.2K 76.1% built-in good 10 git log 86x 556 47.8K 78.5% built-in good 11 kubectl logs 5x 3.6K 17.8K 43.0% plugin good 12 git status 86x 152 13.1K 58.0% built-in good 13 docker ps 20x 467 9.3K 52.8% plugin good 14 kubectl describe 6x 656 3.9K 1.2% plugin weak 15 docker images 9x 940 8.5K 61.8% built-in good 16 k get 2x 2.1K 4.2K 35.9% plugin good 17 terraform 10x 395 3.9K 32.1% plugin good 18 git commit 32x 77 2.5K 0.0% built-in weak 19 docker build 8x 487 3.9K 37.6% built-in good 20 docker compose 22x 979 21.5K 89.4% built-in good total: 4.4M raw → 4.1M saved (91.8%) </code></pre> My toolset above is kind limited, but it works pretty well for my usecase without any interruption Kinda help me not reaching the token limit for my company Bedrock limit usage and keep optimizing the saving on the go for later usage.<p>But, why not alternatives (<a href="https://github.com/zdk/lowfat#alternatives" rel="nofollow">https://github.com/zdk/lowfat#alternatives</a>) ? The answers are: - My goal is to make the core lightweight but extensible via plugins i.e. not trying to bundle every command in the installed binary so that people own their output filters. - Customizable per usecase via plugin or filter pipelines as I am using my own toolset. - Customizable for non-public CLI tools, for example, some enterprise might have their interal CLI tools that public won't have access. - People should own their data. So the design is local-first, No telemetry forever. - I kinda love UNIX-style composible pipes, so lowfat-filter has implemented this style. - Be able to adjust aggressiveness of the filter, so we can control that we won't strip something the agent needed.<p>GitHub: <a href="https://github.com/zdk/lowfat" rel="nofollow">https://github.com/zdk/lowfat</a><p>Anyway, if anyone is interested, feedbacks and questions are welcome!<p>Thanks!

Show HN: Boxes.dev: ditch localhost; run Claude Code and Codex in the cloud

Hi HN, we’re Nick and Drew, and we’re building boxes.dev – the first cloud-only agentic dev environment (ADE) that gives every Codex and Claude Code agent its own cloud computer.<p>We’re two engineers who previously built Gem (co-founder/CTO and first hire), and we spent the last year coding almost exclusively using Codex and Claude Code. It’s been a huge change to how we code, and it’s been exhilarating seeing the models keep getting better – but we eventually realized that developing on localhost was holding us back:<p>- Git worktrees are clunky to set up and use for parallelizing work - It’s 2026, but somehow everyone is still walking around with laptops cracked open or SSHing into mac minis in their garage so their agents don’t stop working. - Mobile is treated like an afterthought even though coding is just texting now We started hitting resource constraints when multiple parallel agents test their own work by running the full app locally. - We tried different products, but couldn’t find any that solved all of our pain points – so we pivoted and decided to just build the ADE we wanted for ourselves.<p>Boxes.dev is a desktop and mobile app that lets you run Claude Code, Codex (using your subscription!), and the full dev environment for whatever you’re building, all on remote compute. It’s similar to Conductor or the Codex desktop app, except everything is in the cloud.<p>We use coding agents to scan your local dev setup and port it to the cloud. Then every Claude Code/Codex thread starts from a snapshot of the full setup, with its own filesystem and compute. No more git worktrees, no more cracked-open laptops, and your coding agents can actually test their work end-to-end because they can run your full app in isolation.<p>We’ve mirrored the Claude Code and Codex UX to feel natural to power users, and also have a fully-featured mobile app (no handoffs or remote control), plus scheduled automations and a Slack integration.<p>We’re obviously biased, but we’ve been building boxes.dev with boxes.dev for months and it’s honestly been a gamechanger. It’s hard to go back once you realize how much localhost has been limiting you; based on early feedback from beta testers, we’re increasingly sure that cloud is the future of agentic coding.<p>We’d love for you to experience it yourselves! Would appreciate any feedback – and happy to answer any questions on this thread.

Show HN: Uruky (EU-based Kagi alternative) now has Image Search and URL Rewrites

You can get a 2h free trial by solving a proof-of-work captcha when topping up your account for the first time.<p>If you'd like to learn more, an independent interview was posted a couple of weeks ago [1], and the FAQ [2] has a lot of information as well.<p>For the source code sharing, we've talked with lawyers and are inclined to no longer require the NDA/NCC for privacy reasons shared with us before (signing requires identification), but instead use a source-available permissive license that doesn't allow competition, like PolyForm Shield [3] (we do still have about 6 months before finalising a decision, here).<p>This does come with a lot more risks for us (it's harder to track down if someone publishes the code or uses it against the license), but given we've already passed 100 monthly active accounts, we're feeling more confident it's an acceptable risk.<p>The plan is to give logged in accounts (who are 12 months old or more) a way to download a ZIP of the current code base that's in the server.<p>Obviously there's no easy way to prove that's the case, but we're open to ideas/suggestions if someone here has them.<p>[1]: <a href="https://theprivacydad.com/interview-with-the-engineer-of-uruky-a-private-search-engine/" rel="nofollow">https://theprivacydad.com/interview-with-the-engineer-of-uru...</a><p>[2]: <a href="https://uruky.com/faq" rel="nofollow">https://uruky.com/faq</a><p>[3]: <a href="https://polyformproject.org/licenses/shield/1.0.0" rel="nofollow">https://polyformproject.org/licenses/shield/1.0.0</a>

Show HN: I reverse-engineered the world maps of Test Drive III (1990 DOS game)

Show HN: Edsger – A handwritten Clojure REPL for the reMarkable 2

Show HN: Eyeball

Show HN: Breathe CLI – Paced resonance breathing in the macOS terminal

I built a terminal app that paces slow breathing at 6 breaths per minute for vagal tone training. It's a single Python file, stdlib only, no dependencies — just run breathe and follow the bar.<p>I'm a cardiology patient (HFrEF). Slow breathing at resonance frequency is one of the few non-pharmacological interventions shown to improve cardiac vagal tone and baroreflex sensitivity (Bernardi et al., Circulation 2002; Lancet 1998). I wanted a frictionless daily habit tool — no app store, no account, no subscription, just open terminal and go.<p>Design constraints, all grounded in the clinical literature:<p>- No breath retention — Valsalva risk in cardiac patients<p>- No rapid breathing — minimum 8-second cycles<p>- Exhale ≤ 2x inhale — no evidence for extreme ratios<p>- Immediate exit, always — q or Ctrl+C restores the terminal even on crash<p>The README includes a resonance frequency measurement protocol for anyone with a chest-strap HRV monitor who wants to find their individual optimum instead of using the 6 bpm default.<p>macOS only (uses afplay for audio cues). MIT licensed.<p>pip install breathe-cli<p>or<p>brew tap marekkowalczyk/breathe && brew install breathe.

Show HN: 500 years of Joseon court omens as an observability dashboard

Show HN: Tiny-vLLM – high performance LLM inference engine in C++ and CUDA

Show HN: Tiny-vLLM – high performance LLM inference engine in C++ and CUDA

Show HN: Zot – Yet another coding agent harness

Show HN: TV Explorer. Adding advanced UI to free online TV

Show HN: Continue? Y/N: A 60-second game about AI agent permission fatigue

Show HN: Hallucinate – Massively Multiplayer Online Rave

<a href="https://github.com/stagas/hallucinate" rel="nofollow">https://github.com/stagas/hallucinate</a>

Show HN: I made an emergency page for my family

I have a bad memory and can't memorize some important numbers, so I created this project.<p>I've always been concerned about being without my phone (getting robbed - which is common in Brazil - running out of battery, having it break, etc.), so I decided to create a page that sends SMS messages (LLM-summarized) and emails with more detailed information such as geolocation, IP address, and the full message.<p>It’s a simple page that allows sending one or more messages, with recipients being myself and other people - for example, in case I or they need help or need to communicate something important.<p>The source code is available at <a href="https://github.com/skhaz/dokku/tree/main/apps/help" rel="nofollow">https://github.com/skhaz/dokku/tree/main/apps/help</a>

Show HN: Write your BPF programs in Go, not C

Show HN: Audiomass – a free, open-source multitrack audio editor for the web

Show HN: ShadowCat – file transfer through QR Codes in a Browser

Show HN: I Dedicated 4 Years to Mastering Offline Password Cracking

Hi everyone,<p>I am Bojta Lepenye, and first of all, I want to thank the core developers of Hashcat. In my experience, it is quite literally the most capable tool available for offline password cracking across a wide range of use cases.<p>I have spent the last 4 years (from age 14 to 18) extensively working with Hashcat and the tools surrounding it, and I have documented what I have learned throughout that time (since January 18, 2022) in my first book. During that period, I also had to continuously update and rewrite major sections as the field evolved. One example was the introduction of GPU support for Argon2 and other memory-hard password hashing algorithms, which significantly changed some cracking workflows.<p>My passion for this book, or its “quick starter,” if you will, came from an ethically conducted penetration test I performed with full authorization at my school. This is something I am both hesitant and quite proud to acknowledge.<p>At the beginning, I simply wrote down everything I had learned from YouTube videos and online blogs. However, not long after starting my project, I realized I practically knew nothing about password security, and that small 10 to 15 pages I had written would never be enough if someone was looking for a professional guide to cracking passwords.<p>The other main driving force behind the book was the fact that while researching online, browsing forums, reading academic papers and white papers, watching videos, exploring blogs, inspecting presentations, and examining infographics, I did not find a single source that comprehensively covers and explains everything one needs to understand about offline password cracking. Literally. Not one.<p>Therefore, I continued my research and learned about password hashing algorithms, the security properties of hash functions, advanced hash cracking techniques, password analysis, attack optimization, and much, much more.<p>From the very beginning, I wanted to share this knowledge with the community because having access to a resource like this would have helped me tremendously when I first started learning password cracking.<p>I sincerely hope this work will be useful to both beginners and experienced professionals alike, and I look forward to hearing your thoughts and feedback.<p>I have also put together a little video to give you a little sneak peek into it. It is on Google Drive. It is the official domain, and you do not need to download anything. Here it is: <a href="https://drive.google.com/file/d/13LeysSZO8Mx-LGKt8UQjUGBKOYH7MqiS/view?usp=sharing" rel="nofollow">https://drive.google.com/file/d/13LeysSZO8Mx-LGKt8UQjUGBKOYH...</a><p>If you are interested, the book is now publicly available on Amazon, and can be read for free with a Kindle Unlimited subscription: <a href="https://www.amazon.com/dp/B0GX36XRCD" rel="nofollow">https://www.amazon.com/dp/B0GX36XRCD</a>