Article URL: https://greatapps.net/ Comments URL: https://news.ycombinator.com/item?id=47814857 Points: 2 # Comments: 0
下载了个音乐app，要订阅才能使用网盘音乐的功能，订阅后发现不是那么回事，基本不可用。 当天AppStore申请退款，退款失败，二次申请，依旧失败。 店大欺客啊，都没有拒绝理由。逆天苹果。 下一步准备去投诉了。 4 个帖子 - 3 位参与者 阅读完整话题
Article URL: https://www.podwarden.com/ Comments URL: https://news.ycombinator.com/item?id=47812131 Points: 3 # Comments: 0
Article URL: https://apps.apple.com/us/app/memorable-ai-photo-search/id6762152034 Comments URL: https://news.ycombinator.com/item?id=47791221 Points: 2 # Comments: 0
appstore切换不同地区的apple id，每次总是导致音乐里面的已下载的歌被删了，很麻烦。一直困扰着 2 个帖子 - 2 位参与者 阅读完整话题
Article URL: https://www.rebuildtheinternet.com Comments URL: https://news.ycombinator.com/item?id=47778128 Points: 1 # Comments: 0
3月16日在尼区appstore开通的claude code 活满一个月了。 网页和app上用Hinet家宽，服务器上的claude code就用dmit 美西代理 每周周限都干满，24年年底创建的号 希望不要出kyc，不然有点难受！ 18 个帖子 - 9 位参与者 阅读完整话题
每次 codex 启动的时候都等很久，然后报错： ⚠ MCP client for codex_apps failed to start: MCP startup failed: handshaking with MCP server failed: Send message error Transport [rmcp::transport::worker::WorkerT ransport<rmcp::transport::streamable_http_client::StreamableHttpClientWorker<codex_rmcp_client::rmcp_client::StreamableHttpResponseClient>>] error: Client error: e rror sending request for url (https://chatgpt.com/backend-api/wham/apps), when send initialize request ⚠ MCP startup incomplete (failed: codex_apps) 不知道有没有佬友知道如何解决 3 个帖子 - 2 位参与者 阅读完整话题
Privacy-first analytics for websites, mobile apps, smart TVs, and IoT devices. Sub-second queries at any scale. Real-time dashboards. Combined views. Geo analytics. No cookies. GDPR compliant by design. Comments URL: https://news.ycombinator.com/item?id=47775772 Points: 3 # Comments: 2
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? Comments URL: https://news.ycombinator.com/item?id=47767606 Points: 25 # Comments: 10
Doors: Server-driven UI framework + runtime for building stateful, reactive web applications in Go. Some highlights: * Front-end framework capabilities in server-side Go. Reactive state primitives, dynamic routing, composable components. * No public API layer. No endpoint design needed, private temporal transport is handled under the hood. * Unified control flow. No context switch between back-end/front-end. * Integrated web stack. Bundle assets, build scripts, serve private files, automate CSP, and ship in one binary. How it works: Go server is UI runtime: web application runs on a stateful server, while the browser acts as a remote renderer and input layer. Security model: Every user can interact only with what you render to them. Means you check permissions when your render the button and that's is enough to be sure that related action wont be triggered by anyone else. Mental model: Link DOM to the data it depends on. Limitations: * Does not make sense for static non-iteractive sites, client-first apps with simple routing, and is not suitable for offline PWAs. * Load balancing and roll-outs without user interruption require different strategies with stateful server (mechanics to make it simpler is included). Where it fits best: Apps with heavy user flows and complex business logic. Single execution context and no API/endpoint permission management burden makes it easier. Peculiarities: * Purposely build [Go language extension]( https://github.com/doors-dev/gox ) with its own LSP, parser, and editor plugins. Adds HTML as Go expressions and \`elem\` primitives. * Custom concurrency engine that enables non-blocking event processing, parallel rendering, and tree-aware state propagation * HTTP/3-ready synchronization protocol (rolling-request + streaming, events via regular post, no WebSockets/SSE) From the author (me): It took me 1 year and 9 month to get to this stage. I rewrote the framework 6 or 7 times until every part is coherent, every decision feels right or is a reasonable compromise. I am very critical to my own work and I see flaws, but overall it turned out solid, I like developer experience as a user. Mental model requires a bit of thinking upfront, but pays off with explicit code and predictable outcome. Code Example: type Search struct { input doors.Source[string] // reactive state } elem (s Search) Main() { ~// subscribe results to state changes ~(doors.Sub(s.input, s.results)) } elem (s Search) results(input string) { ~(for _, user := range Users.Search(input) { ~(user.Name) }) } Comments URL: https://news.ycombinator.com/item?id=47762851 Points: 4 # Comments: 2
Hi HN! Sean from MindStudio here. I wanted to share something we've been working on that I think introduces some new ideas into the "AI coding agent" space. Remy is an AI agent that builds full-stack TypeScript apps from a spec written in a new flavor of annotated markdown. The spec has two layers: prose describing what the app does, and annotations that carry the technical precision (data types, edge cases, validation rules, code snippets). The agent then "compiles" this into code: backend methods, typed schemas, frontends, test scenarios, and everything else are derived artifacts of the spec. The idea is that this isn't no-code, and it isn't a shortcut for people who can't code. It's a step toward a new kind of higher-level programming language, one that happens to look like annotated prose instead of syntax with semicolons. The spec isn't a requirements document that generates code. It is the program. Code is compiled output, the same way nobody writes assembly by hand anymore but it's still running underneath. The spec and code stay in sync bidirectionally, and the same spec compiles into different interfaces (web app, REST API, conversational AI agent, MCP server, etc.) depending on what you need. We're obviously stretching the word "compile" here - the same spec isn't going to produce character-identical code each run. But we think it's an interesting mental model for thinking about where software is headed, and we think the gap between "functionally equivalent" and "effectively deterministic" is only going to continue narrowing with each generation of model. At their core, the apps Remy builds are git repos and markdown files, but we've also built a browser-based sandbox around them - editor, live preview, terminal, chat, and all the other bells and whistles - with managed infrastructure underneath: SQLite with automatic schema migrations, auth primitives (sms/email verification codes, sessions - you build your own UI and define your own user table), 200+ AI models and 1000+ integrations as SDK calls, deploy-on-push. Standard TypeScript, any npm package, any frontend framework. It's been really fun to see what is possible with all of these pieces connected. We're opening up in public alpha this morning. You can watch some demo videos, see some more details, and sign up to try it at: https://remy.msagent.ai (sign up for a free MindStudio account and then use "showhn" as the code to join the alpha without needing a paid account) There are also some more demo videos on YouTube: https://www.youtube.com/watch?v=2QJvBcAqQqA&list=PL1gRZlpf9_... As well as a tour of the interface: https://www.youtube.com/watch?v=ar724yPXgwU Would love to know what you think. Feel free to drop me an email at sean at mindstudio.ai too Comments URL: https://news.ycombinator.com/item?id=47751824 Points: 3 # Comments: 0
Comments URL: https://news.ycombinator.com/item?id=47750012 Points: 1 # Comments: 0
Hermes在阿里云上官方一键安装，卡在了what apps安装上，有没有什么办法能自定义选择安装的插件？ 1 个帖子 - 1 位参与者 阅读完整话题
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. Comments URL: https://news.ycombinator.com/item?id=47738583 Points: 2 # Comments: 1
到时上线后希望能留个方式互群一下 1 个帖子 - 1 位参与者 阅读完整话题
Article URL: https://apps.apple.com/us/app/purrrrrfocus-zen-cat-timer/id6753966008 Comments URL: https://news.ycombinator.com/item?id=47736094 Points: 1 # Comments: 0