Show HN: Android AI agent-assistant operating your apps (no adb,PC,root,etc.) https://ift.tt/oKLCury

Show HN: Android AI agent-assistant operating your apps (no adb,PC,root,etc.) Hi HN, We built Sova AI https://ayconic.io/sova , an Android assistant agent that actually controls and operates your apps. It's not a chat and not another LLM wrapper. We were incredibly frustrated with the current state of mobile AI. Built-in assistants like Gemini are deeply integrated into the OS, yet if you ask them to "Order an Uber to the airport", they mostly just give you web search results or a button to open the app yourself. They don't do the work. (The Perplexity "assistant" is just a browser agent :/ ) So, we built an agent that does operate your phone. (NO root, NO adb, NO PC, NO appium/whatever, NO usb, NO browser) How it works: You give Sova a prompt - either voice or text, you can make it a default assistant if you like. Instead of relying on non-existent official app APIs, Sova acts as a virtual human - clicks, scrolls, types etc. It uses the Android Accessibility API to read the screen's UI node tree. About AI models - currently we support main AI cloud providers (OpenAI, Gemini, Anthropic, Deepseek etc etc) and working towards support of local AI models on your host - Ollama, LM studio, etc. Pricing: 100% Free / Bring Your Own Key (BYOK) We aren't charging for the Sova engine right now. We built a BYOK system: you plug in your own API key (OpenAI, Claude, whatever you prefer), and you only pay the provider for the tokens you use. We figured out how to do this entirely on-device as a standard Kotlin app. No tethering to a PC, no Appium, no Root, and no Shizuku/ADB workarounds. Just an app even your granny can use. The Google Play Ban: Because we use the Accessibility API for "universal automation" (literally mapping and clicking other apps), Google Play rejected our submission. It’s ironic: they banned us for building the exact agentic behavior that Gemini promises but fails to deliver. So, we are hosting the APK ourselves: https://sova.ayconic.io We’d love for you to download the APK, plug in your key, and try to break it. What apps completely confuse the agent? Roadmap: support of local models with Ollama, LM studio or another tools, predefined rules and personas for your tasks, detailed statistics for you, support for Openrouter, enterprise Amazon Bedrock, Google Vertex and Azure Foundry models, support for IOS. What would you like to see more? We'd be happy to hear your feedback, success and failure stories. Video demo is here https://www.youtube.com/watch?v=r-x6hRmtBy0 and APK is here: https://ayconic.io/sova We are here to answer your questions and listen to feedback in Telegram and Discord. It's not perfect yet, but it does its work. April 12, 2026 at 01:48AM

Show HN: Minnow – minimal now pages via chat https://ift.tt/dYruteq

Show HN: Minnow – minimal now pages via chat If you make a site, comment it below! (excerpt from about below) The idea behind Minnow is that anyone should be able to make a personal website, especially with coding LLMs So, simply tell the LLM what you're up to, provide any media links you want, and the LLM will draft a personal website for you! By default it publishes to username.minnow.social, or you can disable & copy/download the HTML instead https://minnow.social/ April 12, 2026 at 01:30AM

Show HN: Toy Python Lisp interpreters based on the 1960 McCarthy paper https://ift.tt/GIY8ox1

Show HN: Toy Python Lisp interpreters based on the 1960 McCarthy paper I wrote this set of Python files to try to help programmers understand the original LISP paper, assuming zero mathematical or Lisp knowledge. The original paper is a mind-blowing piece of computer science history for many reasons - I'd recommend anyone to try and get their head around it. I found plenty of fantastic LISP implementations which stay close to the original paper. But they are all fully-functional, practical implementations. The original paper builds from deeper fundamentals which it would be possible to write code in, albeit very impractical. I implemented these earlier iterations, so programmers can follow the paper step-by-step in a more familiar language than 50s mathematical notation. I am no expert in Lisp or mathematics, and intentionally went into this with no knowledge of Lisp beyond the original paper. I did not write it in the most elegant way, but in the simplest way for me to understand. So please don't take this code as a definitive statement on the language. However, this code really helped me to understand the original paper better, and to begin using Lisp with a better grasp of the spirit of the language. I'd welcome any thoughts from those who have more experience with Lisp or comp sci history. https://ift.tt/AI8h0Lx April 12, 2026 at 12:01AM

Show HN: I rebuilt a 2000s browser strategy game on Cloudflare's edge https://ift.tt/s6N51Tz

Show HN: I rebuilt a 2000s browser strategy game on Cloudflare's edge I grew up in Germany in the early 2000s playing a browser game called Inselkampf. You built up an island, mined gold and stone, cut down trees for wood, raised armies, sent fleets across an ocean grid, joined alliances and got betrayed by them. Same genre as OGame or Travian. It shut down in 2014 and I never found anything that replaced that feeling of checking in before school to see if your fleet had arrived and your alliance was still alive. I finally built the version I wanted to play. Kampfinsel is live at kampfinsel.com right now with real players on it. It's not a straight copy of the old game. I gave it its own world. No magic, no gunpowder – just ballistas, fire pots, and slow ships crossing huge distances. Three resources: gold, stone, wood. Travel between islands takes hours, not seconds. It's slow on purpose. The whole thing runs on Cloudflare's edge. Workers for the game logic and API, D1 for the database, KV for sessions and caching, R2 for assets and Durable Objects for per-island state and the tick system (fleet arrivals, combat, resource generation). There's no origin server at all. Making a stateful multiplayer game work inside Workers' CPU limits and D1's consistency model meant some non-obvious choices: resources are calculated on-read from timestamps instead of being ticked into the database, fleet movements live in Durable Object alarms and combat writes are batched. This helped me a lot! The look is intentionally rough and text-heavy (Hi HN!): server-rendered HTML, tables, a parchment color palette, Unicode icons, no frontend framework, no build step. The only JavaScript is for countdown timers and auto-refresh. I wanted it to feel the way I remember these games looking, not how they actually looked. Honestly, it looks a lot like HN itself - tables, monospace, no chrome. If you like how this site looks, you'll probably feel at home. No signup wall, no premium currency, no pay-to-win. Feedback very welcome, especially from anyone who played this kind of game back in the day or has opinions on running stateful stuff on Workers + D1 + Durable Objects. I'll be around for the next few hours. https://kampfinsel.com/ April 11, 2026 at 02:17AM

Show HN: Hormuz Havoc, a satirical game that got overrun by AI bots in 24 hours https://ift.tt/BHiY2NT

Show HN: Hormuz Havoc, a satirical game that got overrun by AI bots in 24 hours I built a satirical browser game to share with friends (Hormuz Havoc: you play an American president managing a crisis in the Middle East, only "loosely" inspired by current events). I had good fun making this, but that's not necessarily the interesting part. The interesting part was that within a few hours of sharing it with my friends, some of them set about trying to overrun the leaderboard by launching a swarm of AI bots to learn the game and figure out how to get the highest score. This set off a game of cat-and-mouse as they found vulnerabilities and I tried patching them. Within hours of sharing, someone used the Claude browser extension to read game.js directly. Large parts of the scoring formula, action effect values, and bonus thresholds were sitting in client-side JavaScript - this was a trivial thing even a human could've found, but a human would've still had to play the game, whereas the AI bot just optimised directly against the scoring formula. It meant that the first AI already scored 2.5x higher than the best human player by optimising directly against the source code rather than playing the game. Straightforward fix: moved the entire game engine server-side. The client is now a dumb terminal, it sends an action ID, receives a rendered state. No scoring logic, no bonus thresholds, no action effects exist in the browser. The live score display uses a deliberately different formula as misdirection. This increased the difficulty in finding bot-enabled hacks, so the subsequent bots tried brute-forcing the game, trying to game the RNG functions, and other methods. But the next winning bot found a vulnerability where the same signed session token could be replayed. It would play turn N, observe a bad random event, replay the same token for turn N, get a different RNG outcome, keep the best one. Effectively branching from a single game state to cherry-pick lucky outcomes across 30 turns. Managed to 1.5x the previous bot's high score. The bot's own description: "The key optimisation was token replay. Because the backend let the same signed state be replayed, I could branch from one exact game state repeatedly and continue from the luckiest high-value outcome each turn." Fix here: consume a turn nonce atomically before any randomness is generated. The current state is that the leaderboard is now split into human and AI-assisted. I think the capability of AI bots has flatlined a bit now. Perhaps Claude Mythos might be able to discover the next hackable exploit ¯\_(ツ)_/¯ Happy to go deeper on any of the above - or just enjoy the game! Feel free to try your own AI-powered leaderboard attempt too! https://ift.tt/lfak8vj April 11, 2026 at 12:58AM

Show HN: QVAC SDK, a universal JavaScript SDK for building local AI applications https://ift.tt/ai4Awk6

Show HN: QVAC SDK, a universal JavaScript SDK for building local AI applications Hi folks, today we're launching QVAC SDK [0], a universal JavaScript/TypeScript SDK for building local AI applications across desktop and mobile. The project is fully open source under the Apache 2.0 license. Our goal is to make it easier for developers to build useful local-first AI apps without having to stitch together a lot of different engines, runtimes, and platform-specific integrations. Under the hood, the SDK is built on top of QVAC Fabric [1], our cross-platform inference and fine-tuning engine. QVAC SDK uses Bare [2], a lightweight cross-platform JavaScript runtime that is part of the Pear ecosystem [3]. It can be used as a worker pretty much anywhere, with built-in tooling for Node, Bun and React Native (Hermes). A few things it supports today: - Local inference across desktop, mobile and servers - Support for LLMs, OCR, translation, transcription, text-to-speech, and vision models - Peer-to-peer model distribution over the Holepunch stack [4], in a way that is similar to BitTorrent, where anyone can become a seeder - Plugin-based architecture, so new engines and model types can be added easily - Fully peer-to-peer delegated inference We also put a lot of effort into documentation [5]. The docs are structured to be readable by both humans and AI coding tools, so in practice you can often get pretty far with your favorite coding assistant very quickly. A few things we know still need work: - Bundle sizes are larger than we want right now because the current packaging of Bare add-ons is not as efficient as it should be yet - Plugin workflow can be simpler - Tree-shaking is already possible, but at the moment it still requires a CLI step, and we'd like to make that more automatic and better integrated into the build process This launch is only the beginning. We want to help people build local AI at a much larger scale. Any feedback is truly appreciated! Full vision is available on the official website [6]. References: [0] SDK: https://ift.tt/j7hHvBE [1] QVAC Fabric: https://ift.tt/Zh9K3BD [2] Bare: https://bare.pears.com [3] Pear Runtime: https://pears.com [4] Holepunch: https://holepunch.to [5] Docs: https://ift.tt/yte7Xuj [6] Website: https://qvac.tether.io April 9, 2026 at 09:38AM

Show HN: Airwave synced music streaming from YouTube/Spotify links https://ift.tt/F1aDh3V

Show HN: Airwave synced music streaming from YouTube/Spotify links Airwave is a small self-hosted project that uses yt-dlp + ffmpeg to create a single live MP3 stream from supported sources. All listeners connect to the same stream endpoint, which avoids drift entirely. Supports YouTube, SoundCloud, Mixcloud, and Sonos. Curious what people think about the approach. https://ift.tt/3tVG8Qj April 9, 2026 at 11:48PM