Show HN: Hodor – a 701KB native macOS prompt launcher for AI tools https://ift.tt/usmvrHy

Show HN: Hodor – a 701KB native macOS prompt launcher for AI tools Hodor is a tiny macOS app that launches saved AI prompts into any text field — from the screen edge, keyboard shortcut, or keyword such as ;git. I work with different AI tools every day, and had prompts scattered across Raycast snippets, Apple Notes, and Notion — notes that kept getting longer and unmanageable. Raycast snippets are useful, but cumbersome to browse and edit. I wanted one local place to save and review them, and one click to paste them into whatever AI tool I'm using. The test I set was whether I could actually stop using Raycast snippets for this. I think I fulfilled my goal. Hodor has been my daily tool for 3 months now. The app is 701 KB — SwiftUI + SwiftData, no web views. Zero network requests anywhere in the code: no analytics, no telemetry, no update checks. You can verify - search the source for URLSession, it's not in code. Runs on macOS 15+, with native Liquid Glass on macOS 26+. Free and open source. GitHub: https://ift.tt/vyOGSHQ Let me know if you have any suggestions — I'd love to hear how you solved the scattered-prompts problem. https://hodor.design May 27, 2026 at 11:30PM

Show HN: Demon – open-source real-time music diffusion engine, 25Hz local GPU https://ift.tt/VOa1Qys

Show HN: Demon – open-source real-time music diffusion engine, 25Hz local GPU YO, I’m Ryan, lead author. I’ve been contributing open source generative audio stuff for a while now, audio reactive Comfy nodes, extended ACEstep support in Comfy, etc.. I just opened-sourced a new audio project that I've been working on for a few months and I want to tell y'all about it. WHAT IS IS DEMON: Diffusion Engine for Musical Orchestrated Noise This is StreamDiffusion but with audio instead of images, and ACEStep 1.5 instead of Stable Diffusion. It’s responsive enough that you can play it like an instrument, and remix in near real-time. I also distilled the ACEStep VAE: it’s faster at the expense of some quality. I also trained something like 200 lora/dora for ACEStep 1.5 and 1.5XL: I will release these in batches of 5 or 10 or something WHY IT IS Two reasons: 1) Making music is an inherently real-time activity 2) Why not bro SOME RUNTIME CAPABILITIES -Real-time remixing of songs -Denoise, structure, timbre strength adjustment -Reference track swapping -Prompt blending, parameter scheduling with curves -LoRA hotswapping, runtime strength adjustment -Latent channel (research preview) -Feedback -Vocal stem cutting/pasting with melformer (s/o u/BuffMcBigHuge) -XL support (its less stable, working out VRAM pressure issues and whatnot) -Lyrics/vocals SOON -Spectral quality SOON -Other stuff SOME LIMITATIONS -ACEStep (correctly) ‘begins’ and ‘ends’ the song. This system is optimized for remixing either an entire song, or continuously remixing a loop. The loop works fine, but this is not pure, continuous music. Autogression wins here. -Many others, for a more exhaustive list, please see the full writeup via the project page -Please let us know if you find any, I would love to try and address them if possible LINKS My YouTube (DEMON tutorial): https://youtu.be/FBv1b5gmjcE Github: https://ift.tt/NlJWkQw Project page: https://daydreamlive.github.io/DEMON LoRA: https://ift.tt/Go1tPR9 DreamVAE: https://ift.tt/gY0UWu3 Try it w/o installing: https://music.daydream.live https://daydreamlive.github.io/DEMON/ May 27, 2026 at 11:17PM

Show HN: OAuth 2.0 framework for MCP servers https://ift.tt/75FeMfW

Show HN: OAuth 2.0 framework for MCP servers https://ift.tt/Q8KRH2w May 27, 2026 at 11:35PM

Show HN: Gochan – A library of channel architectures for Go, inspired by Rust https://ift.tt/CwFkzcq

Show HN: Gochan – A library of channel architectures for Go, inspired by Rust Hi All, I felt like I was re-inventing the wheel by bolting similar channel architectures onto different Go structs repeatedly so I decided to extract some common types into into one library so that they would be easier to re-use: - oneshot - spsc - spmc - mpsc - mpmc - broadcast - watch The types are inspired by Rust channels so if you're coming from Rust they should feel familiar. So far I'm really enjoying using them but it'd be great to get some external feedback if you have time! https://ift.tt/Quix647 Andres https://ift.tt/Quix647 May 27, 2026 at 11:06PM

Show HN: NeuroFlow 55.8x video inference speedup for Vision Transformers PyTorch https://ift.tt/dWvnj52

Show HN: NeuroFlow 55.8x video inference speedup for Vision Transformers PyTorch https://ift.tt/bj86Mzl May 26, 2026 at 11:04PM

Show HN: WYSIWYG markdown editor for any GitHub repo https://ift.tt/JDHcmaX

Show HN: WYSIWYG markdown editor for any GitHub repo replace any github.com url with dunkdown.com https://ift.tt/Vvz5Lde https://dunkdown.com May 26, 2026 at 08:47PM

Show HN: Write your BPF programs in Go, not C https://ift.tt/njBJQhD

Show HN: Write your BPF programs in Go, not C https://ift.tt/98lOnt5 May 21, 2026 at 11:25PM

Show HN: I made Pokémon but with real animals in the real world https://ift.tt/ZCE5nAw

Show HN: I made Pokémon but with real animals in the real world Firstly, apologies, it's not free. It would be difficult to support this for free, it's a paid game. I will now share the technical details, which will probably be most of interest for HN readers. I previously made a carbon footprint tracking app where you photo objects and it tells you the carbon footprint by using an LLM to estimate the data on the fly, e.g. 32kg CO2e / kg of beef, in the UK. At some point, I realised that it is possible to make a Pokémon-style game, but capturing real animals in the real world. This is now possible because: - image recognition is cheap, i.e. identifying animals, and the models (gpt-4o) can detect a (surprisingly) large number of animals and output their exact species. - LLMs can output a species' full taxonomy, pretty reliably. And, more importantly, they can generate game data quickly, on the fly. It would unfeasible to generate the game sprites (images) for every species (millions, worldwide) and their full evolution chain, e.g. caterpillar, chrysalis, butterfly, ahead of time. I realised it's possible to do this in real time. General game flow: - photo animal - send to gpt-4o - return species - send species to LLM, create evolution chain, plus attributes, types and moves. - in parallel, create sprites. All data is cached. The aim of the game is to build up your team and compete with other players to take over gyms. The game is based in the real world, I had to come up with a way to have health centres and shops. These must both have decent coverage, globally. The solution is health centres are places of worship, e.g. churches, mosques, temples etc and shops are real world grocery stores. Every country as far as I can tell has places of worship, with good distribution, which was surprising. Gyms are located in every park worldwide. Challenges: How to get players outside: - I use openstreetmap for the game map, but I overlay my game design on top of it. - To physically make players go out into nature: I use openstreetmap area types to only allow capturing animals when your GPS location is in natural areas, e.g. woodland, parks etc. The aim of the game is to get you out into nature and appreciating animals. - Level system: The solution I came up with is to set the animal levels based on the proximity to built-up areas, e.g. Every ~500 meters you go away from built-up areas, the animal level bands increase by 5 levels. - It would be expensive to render the entire physical world in my game map, so I instead render the map on the fly, deterministically. I also fetch animal calls in real time so that when they enter battle you hear a pigeon cooing, for example, which is pretty cool. I also fetch the animals conservation status, i.e. how endangered is it, and give you more reward (leaves, in-game currency) for capturing rarer animals. I "launched" the game about a month ago, but have not really been publicising it as I've been working on various updates and improvements, but now I am sharing it more openly. It's got about 20 players so far, from around the world, and around 500 unique animal species have already been encountered. Challenges have been keeping the costs low. Servers cost about $200 / month, text-gen is basically free as I get free tokens from OpenAI for sharing data, it's not privacy-related, and image-gen costs about $0.04 per sprite (2 per animal). My background: not a programmer, originally a mechanical engineer and then business development manager, then started learning programming and building apps with AI in the last few years. Feel free to ask me any technical details, happy to share. https://ift.tt/kPSNmTA May 26, 2026 at 02:48AM

Show HN: Cursed Browser – a VLM reads the HTML and hallucinates the page https://ift.tt/24tGusS

Show HN: Cursed Browser – a VLM reads the HTML and hallucinates the page https://ift.tt/vVpG5dT May 26, 2026 at 12:53AM

Show HN: NanoApps: Run custom homebrew apps on iPod nano 7th generation https://ift.tt/WJO47Kq

Show HN: NanoApps: Run custom homebrew apps on iPod nano 7th generation NanoApps is an early developer preview for hobbyists and tinkerers who want to build and run custom apps for iPod nano 7th generation. Contributions are very welcome. https://twitter.com/freemyipod/status/2058920520708468974 May 25, 2026 at 09:46PM

Show HN: Replacing a 3.4MB video with 40kb of GSAP https://ift.tt/RUKeVS7

Show HN: Replacing a 3.4MB video with 40kb of GSAP https://ift.tt/kw6rSvG May 25, 2026 at 03:59AM

Show HN: Baby's First Cards – real photo flash cards for toddlers https://ift.tt/dJvAPbh

Show HN: Baby's First Cards – real photo flash cards for toddlers App maker here. I built this because most flash card apps use cartoonish illustrations that don't help babies recognize real objects. This app lets you take photos of real things around the house or pick from curated real photo sets. Key features: • Take your own photos as flash cards • Record your own voice for each card • Pre-loaded kits with high-quality real photos and real animal sounds • Bilingual (English and Chinese) mode • Fully offline, no ads, no data collection • One-time purchase, no subscription Happy to answer questions or discuss the development process! https://ift.tt/gca3KJj May 24, 2026 at 08:13PM

Show HN: Audiomass – a free, open-source multitrack audio editor for the web https://ift.tt/wfq5Isz

Show HN: Audiomass – a free, open-source multitrack audio editor for the web https://ift.tt/yxpbAmu May 24, 2026 at 10:25PM