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Show HN: NoSuggest – Watch YouTube without the recommendation algorithm

NoSuggest is a quiet act of resistance against YouTube algorithms always trying to pull you into a loop of unlimited videos in turn into unlimited screen time. With unending side cards of videos, auto-play, what's next suggestions, YouTube shorts and notifications, users will be doom scrolling for many hours in a day.<p>I faced the same problem. Acknowledging that, not all content in YouTube is bad. There are educational videos, genuine news contents without political bias which is very hard to find outside YouTube and many other good relaxing, entertainment stuff.<p>NoSuggest lets you only follow the YouTube channels you like and removes all types of recommendation YouTube has. So you don't waste time on watching things which you never wanted to watch anyways.<p>UI is very simple. You add your favourite channels in "Channels" tab and latest 5 videos per channel excluding shorts would appear in "Feed" tab. "Search" tab is to search for specific videos to watch and "Saved" tab is to bookmark any video you want to watch later. Intention of NoSuggest is to provide whatever is necessary to extract whats good from YouTube all inside NoSuggest and leave out bad parts.<p>NoSuggest works in any devices. Install it as an app (PWA) in android and iPhone, or simply open in browser in laptops. No sign-in, no account creation or no card details. NoSuggest won't even ask your name. Total privacy for the users.<p>Parents can add the channels and save some educational videos and lock it with the pin for kids mode. Kids won't be able access unwanted additive contents inside NoSuggest.<p>Completely free, no string attached. Source available in Github through NoSuggest website.<p>I would love genuine feedback. Thank you very much for your attention on this matter.

Show HN: Gitdot – a better GitHub. Open-source, written in Rust

What works now: user signups, org creations, private/public repos, and importing GitHub repositories (both as read-only mirrors and full migrations). So basically, you can create, push and pull to a repo, but we don't have many features quite yet (issues, PRs, CI).<p>What is a bit unique is: 1) we built it in Rust and 2) the website is a little odd. Its design is inspired by CLIs (e.g., fzf, broot, vim) instead of web apps, and as such, lacks some affordances that you might typically expect in favor of keyboard-driven instant navigations (we have the very ambitious goal of an FCP of 100ms). In case you're curious, here's how we we built it: <a href="https://gitdot.io/designs">https://gitdot.io/designs</a><p>We recognize that we're making some bold claims here and are also well aware that we have much to learn. Building software is still hard, and that's a fact we seem to relearn everyday.<p>But we wanted to share what we built so far nonetheless.<p>Cheers, thank y'all for reading, and till the next —paul & mikkel.

Show HN: Performative-UI – A react component library of design tropes

hope you enjoy

Show HN: Free animated icon library for Vue

Hi everyone!<p>Tim here, maintainer of the lucide-motion-vue library. I build this as a way to use nice animated icons in my webapps. We were already on lucide, and found animate-ui animated icons as a great collection, unfortunately React only or made to be used with shadcn.<p>So I ported the library to Vue, and combined it with another library (lucide-animated.com). As both libraries dont share the same animations and/or icons, this creates the largest animated icons library for vue that can be used from one source.<p>Additionally, I've made several quality of live changes to make it easier to use the icons: - drop-in replacement for lucide icons, or use a seperate namespace if you want - several animation variants - easy to be used standalone or in buttons - several animation triggers - comprehensive overview, playground and docs page, comes with llms.txt to be used by agents<p>Finally, the repo also contains a "forge". With this, you can<p>a) take any icon from the lucide library, or have ai suggest some b) autogenerate animations for these icons c) add them to the library with one click<p>We'll use the forge over time to hopefully create animated variants for all of lucides icons, if these icons are useful to be animated.<p>Looking forward to hear your feedback Cheers!

Show HN: Free animated icon library for Vue

Hi everyone!<p>Tim here, maintainer of the lucide-motion-vue library. I build this as a way to use nice animated icons in my webapps. We were already on lucide, and found animate-ui animated icons as a great collection, unfortunately React only or made to be used with shadcn.<p>So I ported the library to Vue, and combined it with another library (lucide-animated.com). As both libraries dont share the same animations and/or icons, this creates the largest animated icons library for vue that can be used from one source.<p>Additionally, I've made several quality of live changes to make it easier to use the icons: - drop-in replacement for lucide icons, or use a seperate namespace if you want - several animation variants - easy to be used standalone or in buttons - several animation triggers - comprehensive overview, playground and docs page, comes with llms.txt to be used by agents<p>Finally, the repo also contains a "forge". With this, you can<p>a) take any icon from the lucide library, or have ai suggest some b) autogenerate animations for these icons c) add them to the library with one click<p>We'll use the forge over time to hopefully create animated variants for all of lucides icons, if these icons are useful to be animated.<p>Looking forward to hear your feedback Cheers!

Show HN: Oproxy – inspect and modify network traffic from the browser

Show HN: Oproxy – inspect and modify network traffic from the browser

Show HN: Kyushu – A self-hostable WASM sandbox for JavaScript workers

Show HN: Kyushu – A self-hostable WASM sandbox for JavaScript workers

Show HN: I Derived a Pancake

After 25 years of making other people's pancake recipes - always yearning for more tang, more fluff, and more predictability - I decided to derive the pancake recipe from the chemistry.<p>You mark checkboxes for what you have on hand (ricotta, sour cream, kefir, buttermilk, yogurt, cottage cheese, lemon, cream of tartar, etc.) and it computes the best recipe based on targets for acid, fat, salt, sugar, and CO2.<p>My particular favorite are the yeast-raised lemon ricotta kefir pancakes - the best I've ever had.<p>The math is done in a small pure-ESM library: ingredient composition to component masses and acid moles, a stoichiometry layer, and a bisection solver for the target deficits.<p>I'm not a chemist, so if something is off, tell me and I will fix it!

Show HN: I Derived a Pancake

After 25 years of making other people's pancake recipes - always yearning for more tang, more fluff, and more predictability - I decided to derive the pancake recipe from the chemistry.<p>You mark checkboxes for what you have on hand (ricotta, sour cream, kefir, buttermilk, yogurt, cottage cheese, lemon, cream of tartar, etc.) and it computes the best recipe based on targets for acid, fat, salt, sugar, and CO2.<p>My particular favorite are the yeast-raised lemon ricotta kefir pancakes - the best I've ever had.<p>The math is done in a small pure-ESM library: ingredient composition to component masses and acid moles, a stoichiometry layer, and a bisection solver for the target deficits.<p>I'm not a chemist, so if something is off, tell me and I will fix it!

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: 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: I nerfed our coding agents on purpose

Tl;dr: I trained a classifier to route to the least expensive model and reasoning depth to complete the request. Coupling that with additional automated token efficiency techniques has yielded 3x usage for the same spend. For anyone interested in trying it themselves: <a href="https://nerfguard.com" rel="nofollow">https://nerfguard.com</a><p>Various teammates and I switched over to Codex from Claude Code recently. We still bounce between the tools, but Codex’s speed and steerability coupled with performance gains were hard to ignore. One of the downsides was that the per token pricing kicked in way sooner. This is happening across the board, but we felt it in Codex more acutely. We’re a startup filled with people who work around the clock and are obsessed with building — naturally our <i>daily</i> bill alone was striking.<p>Luckily we’re going after a big mission and speed matters significantly more than marginal token spend on the edges. Still, it got us thinking about how it was ludicrous that while our product has a side effect of decreasing token spend and speeding up agentic workflows by many orders of magnitude, we were using these top tier models for all types of internal coding tasks without any of those optimizations. The waste felt pretty ridiculous — the most glaring culprit was that we were seemingly using the max intelligence model on max reasoning for every task even when the task clearly didn’t require it. As a company who spends a lot of time on cached intelligence, it was also easy for us to see how there was plenty of other low hanging fruit as well.<p>So, on a recent weekend, I quickly built a tool to optimize our usage. At its core is a <i>very fast</i> classifier that classifies your requests to the least intelligence required for the task and includes some nice token optimizations on top. The result is roughly the same quality for multiples lower token spend. But even more exciting for us, is that the properly bin packed intelligence and reasoning levels meant our speed also went up considerably. This wasn’t negligible.<p>We’ve observed up to 3x savings and hours per day per person in saved time that we would have otherwise been waiting on tool turns and coding agent responses.<p>For us, that means improved engineering velocity and significantly higher usage for the same spend. It also means more usage before getting throttled.<p>As I told friends about this, they also wanted to start using it to maximize the usage they could get out of their coding agent plans. There are now engineers across many of the most cutting edge AI companies using this tool to optimize their token utilization in this way. Not just to save money, but to maximize output. Turns out that the best way to avoid getting nerfed by Claude is to intentionally nerf yourself selectively. We decided to release it for the rest of the builder community to use as well. You can now turn on Nerfguard for yourself and start getting more usage today.

Show HN: ABC Classic 100 Rankings visualised

This weekend is the ABC Classic FM countdown, which prompted me to dust off an old un-published data visualisation of rankings from previous years.<p>I've considered adding a search function, but I also kind of like that it requires a bit of exploration in the current form.<p>Some of the code is a bit clunky and I wouldn't mind refactoring it. I'm also not sure about browser compatibility - I've only got access to a couple of devices to test it on.

Show HN: ABC Classic 100 Rankings visualised

This weekend is the ABC Classic FM countdown, which prompted me to dust off an old un-published data visualisation of rankings from previous years.<p>I've considered adding a search function, but I also kind of like that it requires a bit of exploration in the current form.<p>Some of the code is a bit clunky and I wouldn't mind refactoring it. I'm also not sure about browser compatibility - I've only got access to a couple of devices to test it on.

Show HN: Soft Body Jiggle Physics

A simple and fundamental standard for dynamic soft body dynamics.

Show HN: Soft Body Jiggle Physics

A simple and fundamental standard for dynamic soft body dynamics.

Show HN: Infinite canvas notes in the non-Euclidean Poincaré disk

Hi!<p>This is an infinite canvas note-taking tool where notes are laid out in a non-Euclidean, hyperbolic geometric space. As you drag and navigate through the view, you’ll experience a unique fluid distortion that naturally leverages your brain's spatial memory.<p>I’ve been obsessed with the concept of space in HCI for years. Many modern UI patterns are essentially workarounds for the lack of screen real estate. While researching zoom-based UIs a while back, I stumbled upon old HCI papers that used the Poincaré disk model of the hyperbolic plane to organize data. It elegantly projects an infinite space into a finite disk, keeping everything contextually visible.<p>I wanted to build an experimental app around this concept years ago, but the non-Euclidean math was a significant roadblock. Recently, I decided to give it a shot with the help of LLMs. It turns out that LLMs can handle the mathematical heavy lifting quite well, specifically in designing the coordinate systems and optimization algorithms, provided that you guide them with a solid architectural design.<p>This is still an experimental demo, but I hope it leaves an impression. I’d love to know if you find this paradigm practical for organizing your thoughts.

Show HN: Infinite canvas notes in the non-Euclidean Poincaré disk

Hi!<p>This is an infinite canvas note-taking tool where notes are laid out in a non-Euclidean, hyperbolic geometric space. As you drag and navigate through the view, you’ll experience a unique fluid distortion that naturally leverages your brain's spatial memory.<p>I’ve been obsessed with the concept of space in HCI for years. Many modern UI patterns are essentially workarounds for the lack of screen real estate. While researching zoom-based UIs a while back, I stumbled upon old HCI papers that used the Poincaré disk model of the hyperbolic plane to organize data. It elegantly projects an infinite space into a finite disk, keeping everything contextually visible.<p>I wanted to build an experimental app around this concept years ago, but the non-Euclidean math was a significant roadblock. Recently, I decided to give it a shot with the help of LLMs. It turns out that LLMs can handle the mathematical heavy lifting quite well, specifically in designing the coordinate systems and optimization algorithms, provided that you guide them with a solid architectural design.<p>This is still an experimental demo, but I hope it leaves an impression. I’d love to know if you find this paradigm practical for organizing your thoughts.