Product Hunt 每日热榜 2026-03-29

PH热榜 | 2026-03-29

#1
Clico
Every textbox, supercharged
367
一句话介绍:Clico是一款浏览器扩展,通过将AI深度集成到浏览器文本框中,在用户浏览网页时直接提供上下文感知的写作与生产力辅助,解决了因频繁切换标签页和复制粘贴文本而导致的AI工具使用流程中断痛点。
Chrome Extensions Productivity Writing Artificial Intelligence
浏览器扩展 AI写作助手 生产力工具 上下文感知 无摩擦交互 文本增强 实时辅助 智能伴侣 工作流集成 Chrome插件
用户评论摘要:用户普遍赞赏其无缝集成和解决“标签页切换”痛点的理念。主要问题与建议集中在:1. 新用户引导不足,安装后首次使用路径不清晰;2. 对隐私边界、数据存储及本地部署可能性的关切;3. 多标签页上下文管理的具体机制;4. 目前仅支持Chrome,对其他浏览器平台的兼容性需求。
AI 锐评

Clico瞄准了一个真实且日益凸显的“工作流摩擦”痛点:AI能力强大,但调用过程笨拙。其核心价值并非提供了新的AI功能,而是对AI交互范式进行了一次“空间重构”——将AI从独立的“应用”或“标签页”中解放出来,将其嵌入每一个输入框。这本质上是将“人找AI”变为“AI随人”,试图让AI辅助像呼吸一样自然,而非一次需要刻意启动的仪式。

然而,其面临的挑战同样尖锐。首先,**“集成优势”与“隐私顾虑”是一体两面**。产品引以为傲的“读取网页上下文”能力,恰恰是用户安全神经最敏感的部分。尽管团队声称通过“@”指令进行显式控制,但作为浏览器扩展,其潜在权限边界仍需极其透明和坚固的架构设计与用户沟通来保障。其次,**“无所不在”可能意味着“缺乏焦点”**。评论中提及的新用户引导问题,暴露了其作为多功能工具面临的“能力过载”风险。当AI可以处理太多事情时,用户反而可能不知从何开始。产品需要找到一个如同“魔法时刻”般的杀手级用例,作为用户认知的锚点。

从长远看,Clico的赛道竞争将异常激烈。它不仅要与Notion AI、Grammarly等垂直写作工具竞争,更是在与浏览器厂商(如Edge的Copilot)和操作系统级AI集成赛跑。其生存空间在于极致的轻量化、响应速度和上下文理解的精准度。如果它能将“@引用多标签”这类功能做到极致流畅,真正成为跨网页信息处理的“中枢神经”,而非又一个浮于表面的文本补全工具,才有机会建立起壁垒。目前看来,其理念超前,但产品成熟度与用户信任的建立,仍是漫长的上坡路。

查看原始信息
Clico
Clico is a powerful Browser extension designed to be your ultimate writing and productivity partner. Unlike traditional AI tools that require you to copy and paste text back and forth, Clico lives directly inside your browser. It reads and understands the context of the webpage you are currently viewing, allowing it to perform tasks with an unmatched level of relevance and intelligence.
Hey everyone, Alex from Clico here. We are thrilled to finally introduce Clico to the PH community. We built Clico out of our own frustration with constant tab switching and the repetitive cycle of copying and pasting text into AI tools. We wanted an AI that actually lives where we work and understands the full context of our browser. We vibe coded this product ourselves, and it gave us that immediate aha moment the first time we used it. We are so excited to bring this to a broader community so you can all experience having an intelligent companion right by your side. We highly recommend trying the @ feature to pull in different tabs as context and the Memo It feature to summarize complex pages in seconds. We cannot wait to hear what you think! Join our discord at https://discord.gg/yeaVWQ8wzd for more product updates and talk with us directly. We are a small team and trying to figure things out:) Let's clicooooo
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@alex_tao all in one extension for text operations in computer I see. I might needed this. I want to know how does context management work. Is it external LLM API integration?

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@alex_tao When Clico pulls in multiple tabs as context, how do you handle the privacy boundary, does it only read tabs you explicitly @ mention, or does it have passive access to everything open in the browser at all times?

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@alex_tao Wow, i try and I love the seamsless integration but i see that is only on google do you not cover other platform like edge

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Hey PH! We are so excited to finally bring Clico here!


We built Clico because the best AI in the world still made us leave the page to use it. That felt wrong. So we put it inside the page. Plus there's so much more we want to improve, which is exactly why we're here.


Clico is free while we're in beta, and your feedback is what shapes what it becomes. Feel free to join our discord and come build it with us!


Let's clico!

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Huge thanks for all the support, everyone! Building Clico has been a labor of love, we really wanted to kill the friction of constant tab-switching. If you hit any bugs or have a feature you’re dying to see, drop a note in our Discord or ping us right here. We’re building this for you, so your feedback is literally our roadmap. Stoked to see how you use it to clear the clutter. let’s clico!

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Thank you all so much for the incredible support here on PH! Clico is a product built with heart.
We realized that our interactions with AI were always so fragmented—constantly switching between tabs just to feed context into an AI tool. It was the number one frustration my team kept bringing up, so we decided to build Clico internally to solve it for ourselves.

The moment our colleagues started using it, the feedback was instant: "Oh my god, this is exactly the productivity tool I’ve been waiting for." Seeing their reaction and those thumbs-up gave us the confidence to open it up to everyone. We truly hope you feel that same sense of ease and excitement in your own workflow.

Without further ado, it’s time to dive in—start using it, and we hope you fall in love with it!

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That's a handy extension. All the best for your launch 🎉

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@basharath Thanks Basharath! Hope you like it:)

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Installed it and went through the flow. The product itself works well, but there's a drop-off waiting to happen right after install. You land with four shortcuts to learn, ⌘+O, Double ⌘, Hold ⌘, Highlight, but no clear signal for which one to try first. A new user opens a tab, nothing looks different and within 48 hours the extension is forgotten.

The gap is the bridge between install and first value. One forced first action right after install, pick your strongest use case, put it directly in front of the user, make it the only thing to do in that moment. That would close that gap before the user even has a chance to drift. What does your Day 1 usage rate look like on new installs?

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@arun_tamang Hey Arun, good catch! Currently we'll direct users to a playground where we provide a input field and they can try out features themselves. But we do considering making it more intuitive so that ppl know what to do after installing it

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This looks really clean. I like the idea of it living directly in the browser instead of constantly copying things back and forth. That friction adds up more than people realise.

How do you handle context across different tabs or sites? That feels like the bit that makes or breaks tools like this.

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@becky_gaskell Hey Becky, thanks for the comment! Currently Clico can use multiple tabs as context with a simple at when using clico it feature. The feedbacks that we are getting is kinda good. Try it out and let me know what you think:)

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How does this handle complex pages like dashboards or long data filed docs? Congrats on the launch!

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@jasonhowie Thanks for the kind words,! To answer your question, we handle complex pages by parsing the DOM directly to extract the most relevant content. We’ve also built custom optimizations for high-frequency use cases and implemented context compression to ensure the model stays focused on what matters most. Hope you enjoy using Clico!

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Loving the seamless integration, but how does Clico handle context-switching when multiple tabs are open with different topics? That could be tricky to manage!

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@trydoff Hey Trydoff, good question! You can directly tell Clico which tab you are using with a simple @ and it will automatically know what to do. Try it out!

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Good.

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Wishing luck with your launch :)

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@busmark_w_nika Appreciate that Nika!

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Huge congrats on the launch! I’ve seen how much work went into this, and it’s awesome to see it finally live. Love the concept, and I think a lot of people will find it genuinely useful. Rooting for you today Alex!

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@sylvia_sheng I'm literally crying haha. Big time thank you Sylvia!

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super clean, happy launch day! quick one on the voice input - when you hold ⌘ and speak, does it still use the page context to understand what you're asking, or is it just transcription at that point?

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@jens_deryckere1 Thanks for the hype and the kind wishes! Yes, it definitely uses the page context—holding ⌘ acts as an entry point for the AI to process what's on your screen, so it provides a relevant, context-aware response rather than just transcribing.

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Big fan of this direction, AI works best when it lives inside the workflow, not outside it. Congrats on the launch 🚀

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@mikita_aliaksandrovich Thank you Mikita!

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The context-switching problem is real. I've been working on writing tools myself and the friction of copy-paste to AI just kills momentum. Love that you built this directly into the browser where the work actually happens. The @ feature for pulling in multiple tabs is clever—will definitely try that. Congrats on the launch!

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@plutarco glad you like it!

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Love Clico's approach to building the personal context layer and helping users utilize it for everyday work, but where would Clico store my personal information? Could it be deployed locally?

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@jinhao_bai2 hey jinhao, good point! currently we don't store user's sensitive personal information and the only thing that we need to use is the custom instruction that you set up previously, which is kinda like a system prompt. Also local deployment is something we've thought about before, might considering supporting that in the future

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Love the idea of AI living inside the browser instead of switching tabs. Does it work well with long-form content like blogs or docs?

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@yetahost Thanks for the kind words, Ankit! We’ve implemented a context compression mechanism and specific optimizations for high-frequency use cases and long-form content. If you have any specific use cases in mind, we’d be happy to provide tailored support and optimizations for you. Hope you enjoy using Clico!

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Can I use it to write a natural email fast from Gmail?

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@charlenechen_123 bet! you can even do it with 50 RE:RE:RE:RE sequences without losing the context ;)

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Nice idea, having the AI read the page context instead of copy-pasting text back and forth is a smart approach. How does it handle pages with a lot of dynamic content like SPAs where the DOM changes frequently?

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@thomasnowhere Thanks for the great question! To keep things private, we only capture the DOM when you actually trigger the AI to use it. Hope that clears things up!

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What about outlook web client?

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@yoel_bennesher yeahh it works just as in Gmail. Try it out and let me know if you like it:)

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This is exceptional man, you're lifesaver, you have no idea how many times I have copy pasted the text from ChatGPT to the comment box!

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@nayan_surya98 totally feel you broooo

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Cool, I like this super chrome extension.

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@zhitao_yan for sure Tony:)

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congrats for the launch! excited!

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@ethan_zheng Hey Ethan! Glad you like it!

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The in-browser approach is smart for reducing friction, always a win for user adoption. I'm curious about the specific security model for parsing context directly in the browser, especially with sensitive data.

How does Clico maintain context across multiple sites or tabs, as Becky Gaskell touched upon? This is an area where these tools typically succeed or fail long term.

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Congrats on the launch and hitting #1 today! The approach of living directly inside the browser instead of requiring copy-paste into a separate AI tool is a huge UX win — that context switching adds up fast. The @ feature for pulling in content from other tabs sounds really powerful too. As someone who builds Chrome extensions, I know how tricky it is to get reliable content injection across different web apps. How are you handling compatibility with sites that have heavily customized text editors (like Notion or Google Docs)?

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@roman_builder Thanks for the kind words and the support! That's a great question. We've run into the same challenges—since every site has a unique DOM structure, we've built a flexible core architecture and then handle things case-by-case. We've specifically optimized our approach for complex editors like Notion and Google Docs to ensure it works smoothly. Thanks again for the feedback!

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#2
Sheet Ninja
Ship vibe-coded apps. Your data stays in Google Sheets.
307
一句话介绍:一款将Google Sheets秒变为实时API的工具,让非技术用户和“氛围编程”开发者无需后端即可构建数据驱动的轻量级应用,解决了在快速原型和MVP开发中数据管理与应用层脱节的痛点。
API No-Code Development
无代码开发 Google Sheets集成 实时API 氛围编程 快速原型 MVP工具 数据同步 轻量级数据库 生产力工具
用户评论摘要:用户普遍赞赏其简化流程、赋能非技术客户的价值。主要问题集中在数据冲突处理、错误兜底机制、性能与扩展性(如速率限制、缓存)以及从Sheets向专业数据库迁移的路径。
AI 锐评

Sheet Ninja的精明之处在于,它没有创造新需求,而是精准地缝合了一个长期存在的断层:将全球最普及的“平民数据库”Google Sheets,与当下最热门的AI驱动式“氛围编程”工作流连接起来。它的核心价值并非技术颠覆,而是工作流哲学的转变——承认并拥抱了数据所有权与应用开发权的分离。

产品看似简单,实则切中了几个关键趋势:其一,AI编码工具(如Replit、Lovable)降低了前端构建门槛,但数据层管理仍是混乱之源。Sheet Ninja将数据层“隔离”在Sheets中,实质上是为AI代理的“破坏性创造”划定了安全区,提升了开发过程的稳定性。其二,它服务于日益增长的“构建者-客户”协作模式。客户在熟悉的表格中维护数据,应用实时同步,这从根本上消灭了琐碎的更新工单,重构了代理关系。

然而,其光环也受制于Google Sheets的天花板。评论中关于冲突处理、模式错误静默失败的担忧,直指其作为“生产级”工具的软肋。它本质上是一个出色的**加速器**与**过渡方案**,而非终极解决方案。它的最佳场景是原型、内部工具、低频更新的展示型页面或由非技术主体主导数据的MVP。团队对引入缓存和提供迁移文档的规划是明智的,这承认了工具的生命周期——当项目成功到需要突破Sheets限制时,Sheet Ninja的使命便已完成。它真正的成功,将取决于能否让用户足够平滑地“毕业”,并在此过程中建立起足够的用户忠诚度。

查看原始信息
Sheet Ninja
Sheet Ninja turns any Google Sheet into a live API in seconds. Your data already exists. Stop rebuilding it in clunky databases. Paste a link, get endpoints. Build with Lovable, Bolt, or Replit and your data stays in Sheets. Your clients edit like a spreadsheet. Your app reflects it instantly. No backend, no redeployments, no calls from confused clients.

Hey Product Hunt 👋,

Really excited to launch Sheet Ninja today - a simple way to use your Google Sheets data in vibe coded apps.

Why we built it

We vibe code apps all the time and love the platforms - Replit, Bolt, Lovable. The most annoying part is making tiny updates - e.g. changing text, updating values, or pulling reports.

You have to dig into the files or prompt the agent to do something that takes two seconds in a spreadsheet. And those agent calls add up.

So we stopped fighting it

Sheet Ninja turns any Google Sheet into a live database by providing a simple, secure API. Paste it with your prompt into whatever builder you're using this month and your AI hooks it up. You just edit a row, the app updates live.

It also means you can move between platforms without loading all your data again. The tools keep changing. The spreadsheet doesn't.

Check out the blog for step-by-step builds — a restaurant menu, a waitlist, a job board, a testimonials page. All vibe coded, all powered by Google Sheets.

Looking forward to seeing all the cool things you'll build.

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@taariqismail 💯 - The biggest win for me is the stability this adds to the workflow. When you are 50 prompts deep into a vibe coding session, AI agents often subtly break the backend or change a variable name while you are busy fixing the UI.


Keeping the data in a Google Sheet puts it safely outside the agent's blast radius. I feel much more confident letting the AI go wild on the frontend because I know it cannot accidentally mess with the core database structure. It saves so much time on debugging those invisible errors that agents tend to create.

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@taariqismail Really like how streamlined my workflow is now because of SheetNinja - perfect for entrepreneurs like me who like to build, iterate and move quickly!

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Thrilled to hunt the Sheet Ninja team on their Product Hunt launch. Sheet Ninja is the backend vibecoders already have. This isn't "connect your tools,". This is starting with where your data actually lives, and building on that foundation. The unlock is treating Google Sheets as a first-class API. One that agents, apps, and non-technical clients can all read and act on. Your app gets live endpoints. Your clients get a spreadsheet. Nobody has to redeploy to change a price. This adds up to: - Instant API from any Sheet. Paste a link, go build. - Works out of the box with Lovable, Bolt, Replit, v0, and Cursor. No new tools to learn. - Full CRUD support: read, write, update, delete. Your Sheet is your database. If you're building with AI coding tools or tired of rebuilding data your clients already manage in Sheets. Sheet Ninja is the missing layer between your spreadsheet and your app. Try it now: sheetninja.io
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@byalexai How does Sheet Ninja handle real-time sync or conflicts when multiple non-tech clients edit the same Sheet simultaneously, does it prevent data overwrites like a proper DB would?

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@byalexai congrats!! quick one here; When a client edits the Sheet directly and breaks the expected schema; wrong column names, merged cells, deleted rows ; how does Sheet Ninja surface that error to the app before it causes a silent failure downstream?

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@swati_paliwal Sheet Ninja is built specifically for non-techies. It allows you to use all the controls that Google Sheets gives (eg protected cells, validation). For conflicts, it will take the latest state that’s in the Sheet at a given time.
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This looks really useful. I spin up little projects all the time so I’ll definitely give this a try. Out of curiosity, how does this hold up as projects start to grow? And if something outgrows Sheets, how easy is it to move to something more robust?
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@martyn_johnson thanks! Looking forward to hearing about all the things you’ll build. Google Sheets API has a rate limit of 60 requests per min per user, and there’s a 10 million cell limit in Google sheets. Longer term we’re looking to introduce caching to help power users scale to thousands of requests per second if needed Where we can, our plans have no limits though - unlimited projects, unlimited rows. In terms of migrating to something more robust we offer detailed documentation (https://docs.sheetninja.io) so users can quickly recreate their APIs against a production DB if needed
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Really cool idea! Reminds me of how levels.fyi was running their whole operation from a Google Sheet for a pretty long time.

Going beyond the basics - can you also write back to the sheet and how does authentication work?

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@camin_mccluskey Thanks!

Exactly - you don't need a lot of sophistication to get something off the ground.

Sheet Ninja supports both read and write + there's bearer authentication (and you can control which operations the authentication applies to). Here's a quick screenshot.

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This is interesting. I work with large spreadsheets for tracking things like invoices and cancellations, and managing that manually becomes painful at scale.

Could this help automate those kinds of workflows and keep everything in sync without extra effort?

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@yetahost Yes - this sounds like the perfect use case for Sheet Ninja + your favourite vibe coding tool

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Thanks for launching, it’s been a useful product for me. I’ve used Sheet Ninja on some products i’ve been playing around with on Replit and found the tool useful for the database side and keeping data in Google Sheets. Keep it up and looking forward to new features!

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@hamza_zaveri2 Thanks for the support - glad to know you're using it to avoid the database hassle. Excited to see what you'll build.

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Thanks @hamza_zaveri2 ! Glad you've enjoyed using the tool 🙇

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This could be really useful for agencies that build MVPs for clients -- the client keeps editing their product catalog or pricing in Sheets, and the app just reflects it. No more "can you update one field" tickets. How does it handle rate limits or larger sheets with thousands of rows? Any caching layer involved?

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@greythegyutae Yep exactly! it's a breeze for clients to update their own data. Right now it supports the maximum Google Sheets API rate limit of 60 requests per min per user, however we do plan to introduce a caching layer in the near future. We also support the maximum Google Sheets limit of 10 million cells

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This looks really useful! Love how it turns Sheets into an API so quickly. Super practical and clean idea!!

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@santifarre thanks!
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Congrats on the launch 🚀 Smart & scrappy builders have been using google sheets as a flexible db for ages, and you’re bringing it to the masses for this new age!

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@wilhelmklopp 100% - everyone deserves to use their data wherever they want.
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This is smart. Curious if there's a rate limit on API calls or if it can handle decent traffic on a live site?

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@vibiter thanks! Google Sheets API has a rate limit of 60 requests per min per user, and there’s a 10 million cell limit in Google sheets. Longer term we’re looking to introduce caching to help power users scale to thousands of requests per second if needed Right now - where we can, our plans have no limits though - unlimited projects, unlimited rows.
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Been building with Sheet Ninja for a few weeks now and it's genuinely changed my client projects. Built a full private dental practice dashboard with tons of details all powered by a single Google Sheet with Sheet Ninja. The best advantage is that non-technical business owners can update their own data in a spreadsheet they already know, and see it reflected instantly in a frontend app. Congrats on the launch.

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@yaqoobahmad38 thanks. The dental dashboard sounds cool. Thanks for sharing what you’ve built.
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I like about the honesty of the approach. It doesn't pretend to be something crazy. It's just: your data is in a sheet, your app needs that data, here's the bridge.

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@magonads yep - it does exactly what it says on the tin!
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Loving seeing this. It's a problem I've had for a while but it always too complex for a non techy to do anything about it... This changes that 👏🏽

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@mujjahiid Thanks! Yep - we built Sheet Ninja specifically for non-techies
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Interesting direction. Tools like this reduce dev time, but risk & data validation becomes even more important at scale. Curious how you're solving that?
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I build a lot of small apps and most of the time I have to import data into wherever I'm building it. Sheet Ninja is much simpler. Just created a test app and it worked immediately.
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Nice one@leonardoubbiali glad it was a breeze to setup. We're looking forward to seeing all the cool stuff you'll be building 🚀

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Interestimg. Is there a direct-sync Supabase connection, too?
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Thanks @moritz_dsc - not at the moment but this is something we can explore!

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The live API from Google Sheets idea is genuinely clever. Curious how it holds up when clients start editing data simultaneously from different tabs. Have you stress-tested concurrent writes? There's a free tool where you can post your URL and let people try to find those exact edge cases. Screenshots come in, structured reports. Worth running while you've got PH traffic.

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@onryo_builds thanks! Right now appends are atomic via Google's Sheet API, but updates/deletes are currently positional based on row ID. It's 'last-write-wins' for now if there are multiple concurrent updates.

Could you share the name of that tool please and we can give it a spin 🙏

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love that you can keep your data -- even if you stop using the app!

i have an expense tracking app with 10k+ rows that I've been using for years -- and Google Sheets isn't going anywhere!

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I appreciate the focus on keeping data within Sheets, especially for the vibe coding scenarios Shikeeb mentioned where AI agents might unexpectedly mess with backends. For many small projects, the Google Sheets API rate limits and cell limits Taariq highlighted are perfectly acceptable. My main concern would be when a project scales aggressively; while the documentation for migrating to a production DB is helpful, the process itself can still be a significant lift for a team used to sheet-native operations.

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What if someone deletes some column? will this break the API?

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#3
SUN
Personalized AI audio lessons generated on demand
280
一句话介绍:SUN是一款按需生成个性化AI音频课程的App,通过整合用户笔记、邮件等个人数据,在通勤、运动等碎片化场景中,为用户提供免屏幕、互动式的持续学习体验,解决了传统音频内容千篇一律、无法与个人知识体系和生活节奏深度结合的痛点。
Android Artificial Intelligence Audio Online Learning
个性化学习 AI生成内容 音频课程 互动音频 知识管理 终身学习 碎片化学习 AI集成 音频流 内容生成
用户评论摘要:用户反馈积极,认可音频学习方向。主要问题集中于:与NotebookLM等工具的核心差异;内容深度与个性化程度的演进机制;事实准确性保障;以及Android版本和更多应用集成的计划。团队回复详细,强调了无需预设资料、主动推荐和持续自适应等差异化点。
AI 锐评

SUN的野心并非再造一个音频平台,而是试图成为基于个人数字足迹的“认知外挂”。其真正价值不在于“按需生成音频”这一表层功能,而在于构建一个动态的、植根于用户个人上下文(笔记、邮件、AI对话)的“知识生成引擎”。它挑战了“人找知识”的传统模式,意图迈向“知识找人”甚至“知识自我衍生”的新阶段。

当前产品呈现出一个关键矛盾:宣传上强调深度个性化与上下文理解,但初期体验被用户指出仍停留在“入门导论”水平。这揭示了其核心挑战:从“接入数据”到“理解意图”再到“生成适配认知曲线的连贯内容”,每一步都存在巨大的技术鸿沟。其宣称的“Audio Flows”(音频流)模式,类似TikTok的算法推荐,但用于知识学习,风险在于可能滑向碎片化与娱乐化,牺牲了知识体系的深度与结构性。

与NotebookLM的比较是不可避免的。SUN的差异化叙事是“无预设、主动式、生活化”,这使其更轻量、更具侵略性,旨在融入生活流。然而,这也意味着它可能更依赖于大语言模型的原始能力,在专业深度和准确性上面临更严峻的考验。用户关于事实准确性的质疑直指其阿喀琉斯之踵。

总体而言,SUN描绘了一个诱人的“被动学习”未来,但其成功与否取决于算法对复杂个人上下文的理解精度、内容生成的深度控制能力,以及能否在“个性化流”与“系统性学习”之间找到平衡。它不止是一个产品,更是一场关于未来知识获取方式的实验,其路途注定漫长。

查看原始信息
SUN
SUN creates interactive audio content on demand. Generate podcasts, audiobooks, or courses on any topic, ask questions while listening, and learn in the context of your life. Unlike static platforms, SUN understands your world—from notes, emails, and AI tools—to deliver truly personalized audio experiences. Built for continuous, screen-free learning that helps you grow every day.

Hey Product Hunt! 🎉

I'm Artin, co-founder and CEO of Sun, an intelligent audio app for curious minds eager to learn something new every day in an immersive, audio-first way.

⭐️ The founding story

We're a team of eager learners who live inside audiobooks, podcasts, and research papers. But today's audio isn't designed for people like us. Or like you. It's the same for everyone, same format, same pace, same assumptions about who you are and what you need.

You have a favorite AI, favorite sources, a life schedule that's uniquely yours, a way of thinking no one else shares, and a life that couldn't pause for decision paralysis when browsing to decide what to listen to next.

Sun is built around that reality.

⭐️ What's live today

🪄 Generate whatever you want to listen to, just by speaking to Sun. Type a topic, ask a question, follow a rabbit hole, Sun turns it into a crisp, engaging audio lesson in seconds. No searching, no scrolling, no settling. If you can think it, Sun can teach it.

🤖 Your favorite AI integration Sun's users are mostly AI enthusiasts, so we leaned in. Sun learns about you through the AI you already love. Just copy a prompt that works best with Sun, paste the response from ChatGPT, Claude, Gemini, whatever you use, and Sun builds your learning profile your way.

🎧 Audio Flows Think audio TikTok. One tap starts an endless, personalized stream of bite-sized audio lessons. Each one flows into the next, built around your interests, your level, your curiosity. It's the easiest way to learn something new without even trying.

💬 AI conversation

☀️ Sun Originals for the PH Community We're launching with exclusive content made for builders and curious minds: deep-dive case studies on the hottest companies, breakdowns of iconic product decisions, and stories behind the startups you follow. This is our gift to the Product Hunt community.

⭐️ Coming soon

🔗 More integrations, connect the tools you already live in: note-taking apps like Notion, devices like Plaud, your email, and more

✨ Instant recommendations, Sun surfaces what you should learn next before you even ask

⭐️ A final note

Our dream is a world where in-context learning, delivered through the healthiest medium, audio, drives continuous growth for everyone, every day. We'd love every curious mind in the PH community to join us and help make this real. Try Sun today with invite code PHFRIENDS and share your feedback.

PS: A huge shoutout to our beta users. We wouldn't be here without you. 🙏

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@artinbogdanov Quick question: How does Sun adapt pacing or depth based on my profile, and what's one beta tweak that boosted retention most?

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@artinbogdanov When Sun generates an audio lesson from a spoken prompt, how do you ensure factual accuracy, especially for fast-moving topics where the underlying model's training data might already be outdated?

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Interesting. I see a little overlap with Shazam – is there any possibility to find music that way too and then customise it accordingly?

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@busmark_w_nika Thanks for the question! Right now, SUN focuses on non-fiction audio, like podcasts, courses, and audiobooks for curious learners. Music isn’t part of the experience yet, but we love the idea and might explore it in the future, since music is such a big and fun part of audio!

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@busmark_w_nika We generate and deliver spoken audio like podcasts, audiobooks, and audio experiences, created specifically for you.

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People often ask: how is SUN different from NotebookLM? Here’s the scoop 😎

  1. Tool integrations — we connect with your favorite tools (like note-taking apps), so your knowledge flows in automatically. No manual uploads, no hassle!

  2. Learns about you — SUN actually understands your context and proactively generates personalized audio content just for you. 🪄

  3. Community-curated content — beyond your own stuff, you get access to high-quality content from the community. Learn from the best!

  4. Audio-first experience — SUN isn’t just analysis. Think podcasts, courses, and audiobooks — all ready to listen anytime. 🎧

In short: less uploading, more learning, all audio, all personalized. ☀️

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@amy_wenyan_hua Thanks Amy.

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Really like what I'm seeing so far. My only question is how it handles depth over time. First lesson felt like a solid intro but I want to know if it gets harder as it learns about me.

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Hi @jiaqichen , first of all, thank you for giving it a try. Personalization and adaptive learning are our top priorities for upcoming releases. The promise of SUN goes beyond a single session. We want you to get real value from every lesson and interaction, while SUN continuously learns about you as you explore each topic. I’d love to hear your feedback and learn how we can make SUN the perfect audio experience companion for you.

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This is a nice direction turning learning into something you can just listen to fits really well into daily life curious how personalised the experience feels over time as you use it more

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@simon_clarkson So glad our mission resonates with you! We actually had a slogan: “Learn while you live your life.” SUN constantly learns about your preferences and emerging context, adapting as you go. Can’t wait for you to try it and see how it evolves!

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@simon_clarkson Thank you, Simon. Excited to get you feedback.

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Congratulations on the launch!

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@igor_ryabenkiy Thank you, Igor! Really appreciate the support.
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@igor_ryabenkiy Thank you, Igor. SUN is rising! :)

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Wow! I’m more of an auditory learner, and your concept really resonates with me. Congrats on the launch, I’ll definitely give it a try!

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@a_hryshchenia Thank you, Ana. Looking forward to getting your feedback.

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@a_hryshchenia Ana, SUN is perfect for you! We’d love to hear your thoughts on the audio quality once you've had a chance to dive in.
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Looks promising, congrats guys! How is it different than NotebookLLM audio generation?

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@farbodsaraf that was my first thought too!
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@farbodsaraf great question. Here’s how SUN is fundamentally different:

  1. No dataset required
    You don’t need PDFs, notes, or existing content. Just describe what you want, and SUN creates it instantly.

  2. You don’t need to know what to ask
    Most people don’t wake up knowing exactly what they need. SUN proactively surfaces what’s relevant based on your behavior, goals, and interests.

  3. Fully customizable experience
    Control duration, depth, voice, language, and structure. It adapts to you, not the other way around.

  4. Continuous, not one-off
    SUN isn’t a single session. Every interaction builds on the last, creating a compounding, personalized stream over time.

  5. Built for real life
    Designed for moments that usually go unused. Commuting, walking, working out. It fits seamlessly into your day.

  6. Community layer
    Discover what others are generating, what’s trending, and explore beyond your own prompts.

  7. Integrations
    Connect tools like Plaud. SUN turns your captured content into structured audio experiences and recommendations.

  8. Hybrid content model
    Not everything is generated. SUN can also surface high-signal snippets from original content when it adds value.

In short, you don’t search for content. You generate it, and over time, it starts generating itself for you.

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Hi everyone! 🚀 Ahmed here, Founding AI Engineer at SUN.

We built SUN because we wanted to turn "dead time" into learning time, without adding more screen fatigue to our lives.

With SUN, you can turn literally any topic into a personalized, AI-generated audio course. It goes beyond standard audio because it's fully interactive, you can ask questions right in the middle of playback. It’s built entirely for continuous, hands-free learning that fits naturally into your commutes, gym sessions, and daily routines.

We're so excited to get this into your hands. Give it a spin and let me know what you think in the comments! What's the first thing you're going to learn about?

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@ahmedtammaa Can’t wait to see all the creative audio courses people come up with using SUN. Let’s go! 🚀

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@ahmedtammaa well said!

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Interesting! Much needed concept, but how it is different from notebookLM?? There I can generate podcast, notes and quiz etc.

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@lak7 Responded to this question below. Here's the copy of my response:

"
No dataset required
You don’t need PDFs, notes, or existing content. Just describe what you want, and SUN creates it instantly.

  1. You don’t need to know what to ask
    Most people don’t wake up knowing exactly what they need. SUN proactively surfaces what’s relevant based on your behavior, goals, and interests.

  2. Fully customizable experience
    Control duration, depth, voice, language, and structure. It adapts to you, not the other way around.

  3. Continuous, not one-off
    SUN isn’t a single session. Every interaction builds on the last, creating a compounding, personalized stream over time.

  4. Built for real life
    Designed for moments that usually go unused. Commuting, walking, working out. It fits seamlessly into your day.

  5. Community layer
    Discover what others are generating, what’s trending, and explore beyond your own prompts.

  6. Integrations
    Connect tools like Plaud. SUN turns your captured content into structured audio experiences and recommendations.

  7. Hybrid content model
    Not everything is generated. SUN can also surface high-signal snippets from original content when it adds value.

In short, you don’t search for content. You generate it, and over time, it starts generating itself for you.
"

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Congratulations on the launch!!
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@chimwemwe thanks!!

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Hey this is cool. How many apps today i can connect with Sun?

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@shubham_kukreti you can connect any AI chat app, Plaud, and we are working on adding more notetakers.

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congrats on the launch!

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@junyu_huang2 thank you!

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The AI profile idea is genius. Does it continuously update as I use the app or is it a one-time setup?

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@amraniyasser yes, plus you can connect your notetakers for additional context.

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Any Android plans? Asking for someone I want to share this with.

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@jinhao_bai2 Yes! We’re actively working on an Android version. coming soon!

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I really like this product. On-demand audio content is enjoyable while driving.

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@andyfuture driving is one of our main use cases.

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Wow! Such a great idea 🔥
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@dmitry_zakharov_ai thanks, Dmitry. Looking forward getting you feedback.

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Congrats on shipping this Artin!

The AI integration approach where users can paste responses from their preferred models like Claude or ChatGPT to build their learning profile is clever since it meets people where they already are, though I'm wondering how you balance maintaining that personalization without the audio content becoming too narrow or echo-chambery over time? 🤔

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@zerotox Great question, and thanks so much!

When we think about personalization, we’re very intentional about balancing it with exploration. We don’t just optimize for what you already like. We also introduce adjacent topics and new directions to keep the experience fresh. We also group users by similar interests, so you benefit not only from your own preferences but also from patterns we see across people with overlapping curiosity. This helps avoid the experience becoming too narrow while still staying highly relevant.

Excited for you to try it and see how it evolves!

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Great idea! Was just thinking about this, but for the content creators I've subscribed to through SRS, would be lovely if this becomes supported someday (e.g., RSS integration that turns your subscribed articles to podcast, like what's jellypod is aiming to do: https://www.reddit.com/r/rss/s/Y...)

Nevertheless, cool idea!

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@odyash Oh we love this idea! RSS → audio is such a natural fit. Adding it to our roadmap!

And appreciate the kind words, glad it resonates

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Happy launch day! Used PHFRIENDS. First lesson was great. Already thinking about what to ask next.

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Congrats on this launch!

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@peng_wood Thank you!

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Can I configure interests in the flow?

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Congratulations on launching! Can you add ability to listen a topic with a group of people? Chatting and discussing topic?

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@den_go goes to the backlog.

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I am currently trying it out right now! It is a really fun product concept. Something that I was reaching for almost immediately was a transcript or captions though. I am not sure if there is a setting available currently that I am missing.

I was planning to go through a few different 15 minute lessons to see what kind of different lesson structures it builds.

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Downloaded this morning. The onboarding took me a second to understand. The AI integration step wasn't immediately obvious. Once I got it though, it clicked.

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@mingjian_li Totally hear you on the onboarding. The AI integration step is a key part of the experience, so if it’s not immediately obvious, that’s on us to make it clearer and more intuitive.

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Just downloaded. Is there a way to save lessons I like? Heard something interesting and wanted to bookmark it but couldn't find the option.

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@jennyxxie thanks for trying SUN, Jenny! 🙏 Right now, bookmarking/saving lessons isn’t fully built out yet (you’re not missing anything). We’ve heard this request a lot, and it’s high on our roadmap!

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Okay I just tried the Audio Flows and did not expect to sit here for 20 minutes straight.

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Really like the concept and the first lesson was great. My only question is whether it gets deeper over time or stays at the same introductory level. Hoping it learns fast.

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@shijun_liu yes, SUN is designed to adapt depth based on you!

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I need invite code 🤓
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I love that someone made the idea I had! I started doing this same thing with a set of prompts that I built for myself! Great idea guys, keep going!

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#4
Google Search Live
Interactive, multimodal conversation in AI Mode
252
一句话介绍:Google Search Live 是一款集成语音和摄像头的多模态AI搜索工具,允许用户通过实时对话与视觉交互获取信息,解决了在动态、复杂或难以用文字描述的现实场景中即时获取答案的痛点。
Android Search
多模态AI搜索 实时对话 语音交互 视觉搜索 全球发布 移动应用 Gemini模型 Google Lens升级 自然语言处理 情境感知
用户评论摘要:用户普遍肯定其全球发布和对话式交互的价值,认为摄像头集成巧妙。核心关注点在于其在实际混乱场景(如嘈杂市场)中的识别与多语言处理能力,这指向了产品真实落地的技术挑战。
AI 锐评

Google Search Live的全球铺开,远不止是一次功能更新,而是Google将搜索从“信息索引”推向“情境理解”的关键落子。其核心价值在于“Live”——它试图捕捉并处理那些转瞬即逝、难以结构化描述的实时现实需求,比如对着杂乱冰箱询问晚餐创意,或在异国街头即时翻译标识并询问历史。

然而,产品光鲜的“多模态”与“自然对话”宣传之下,潜藏着巨大挑战。用户关于“在嘈杂印度市场识别印地语食材”的评论,一针见血地刺破了演示视频的理想泡沫。这考验的不仅是Gemini 3.1 Flash的模型能力,更是对复杂光线、遮挡、方言口音、文化特定物品等长尾现实场景的鲁棒性。目前的技术能否在“真实世界的混沌”中保持流畅体验,而非仅适用于演示中的整洁环境,是其能否真正取代传统搜索习惯的关键。

从战略看,这是Google对Perplexity等对话式AI搜索产品的防御性反击,也是将AI从聊天机器人(Bard/Gemini)无缝植入其最核心、最高频入口(搜索)的必然一步。其风险在于,若体验不够精准可靠,频繁的语音与视觉交互可能带来更高的认知负担与失望感,反而损害搜索的“即得性”金字招牌。成功与否,将取决于其技术深度能否支撑起其宣称的“自然”,否则它可能只是又一个炫技而脆弱的AI功能。

查看原始信息
Google Search Live
Google is expanding Search Live globally which was teased during the event last year, to all languages and locations where AI Mode is available.

**Search Live** is now available globally — 200+ countries, all languages, voice and camera included.

Powered by Gemini 3.1 Flash Live, conversations are more natural, multilingual by default, and work the way you think: just speak.

**How it works:**
- Open the Google app on Android or iOS and tap the Live icon under the Search bar
- Ask questions out loud and get audio responses, with follow-up support and web links
- Enable your camera to add visual context — Search sees what you see and responds accordingly
- Already using Google Lens? Tap Live at the bottom to start a real-time conversation about what's in front of you.

Check out the video demo here

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@adithya How well does the camera handle real-world chaos, like identifying ingredients in a busy Indian market while chatting in Hindi?

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It's super cool man!

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Congrats on the global rollout, this is huge for making AI search actually conversational instead of just typed queries. The camera integration sounds really clever for those moments when you need to ask about something right in front of you but can't quite describe it in words.

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#5
Genzi
The social app built around music
195
一句话介绍:Genzi是一款围绕音乐构建的社交应用,通过在听歌分享、音乐发现、风格社区和线下活动等场景,解决音乐爱好者听歌体验孤立、难以基于音乐兴趣进行深度社交连接的痛点。
Music Events Social Media
音乐社交 兴趣社区 线下活动 音乐发现 听歌分享 社群互动 生活方式 文化娱乐 垂直社交
用户评论摘要:用户肯定音乐社交方向及线下活动结合点,但普遍质疑核心用户行为动机(为何分享而非私密收听)及与Spotify等现有功能的差异化。团队回应将依赖个性化算法进行发现,并强调其集社区、活动、社交于一体的整合性。
AI 锐评

Genzi试图切入一个被反复验证为“陷阱”的赛道:纯音乐社交。其核心矛盾在于,听歌行为本质是私密、沉浸且非即时交互的,这与社交平台要求的公开、互动、即时性存在深层冲突。历史上Last.fm、Spotify的社交尝试均未成主流,便是明证。

Genzi提出的“社区”和“线下活动”看似是破局点,将社交从“同步听歌”的伪需求转向“以音乐为标签的兴趣图谱”和“线下场景导流”。这确实更接近真实需求——人们因相似品味产生归属感,并渴望在线下场景中兑现。然而,这使其商业模式与产品重心变得模糊:它是在与豆瓣小组、Meetup、甚至票务平台的部分功能竞争,而非直接挑战流媒体巨头。

用户评论中的犀利提问直指命门:用户主动分享听歌状态的动力究竟是什么?是寻求认同、塑造人设,还是发现同好?若缺乏独特的价值锚点,Genzi极易沦为另一个信息流噪音源。团队回应的“个性化算法”是标准答案,但非竞争优势。

真正的机会或许在于,能否将“音乐身份”转化为一种高粘性的社交货币,并在线下活动中形成闭环体验。否则,它很可能只是又一个看到了真实痛点(音乐孤独),却提供了无力解决方案(泛社交功能叠加)的案例。其成败关键,不在于功能多寡,而在于能否定义一个无需费力解释、用户自发愿意重复的“核心社交动作”。

查看原始信息
Genzi
Genzi is the social app built around music. Share what you're listening to, discover new music and artists, join communities built around your style, and find events where music brings people together in real life.
Genzi started in 2022. We had the idea, validated it, and then had to pause. Budget ran out and life happened. For four years the app sat there, unfinished. We never stopped thinking about it though. Music is too social to not have a place built around it, and that kept pulling us back. So we rebuilt it. And here we are.
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@rigoc hey!! Spotify and last fm have been trying to crack social music for years and mostly failed because listening is inherently private, what's the specific behavior that makes someone want to share what they're hearing rather than just passively consume it?

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@rigoc The taste of music means a lot glad to see apps being built around it!

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I like this angle. Music is already social, but most apps still feel quite isolated in how you experience it. The idea of connecting people around shared taste and real-world events makes sense.

How are you handling discovery though? That’s always the bit that either keeps people coming back or not.

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@becky_gaskell Thanks! Discovery will be based on personalized algorithm based on your favorite artists, genres, music, and similar events/communities you show interest in!

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@becky_gaskell 

"Great launch! Upvoted and supported. I just launched my platform yesterday too! Would love to have you visit my profile and connect. Keep up the great work!"

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Curious how you differentiate from Spotify social features or existing music communities.

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@ion_simion_bajinaru Spotify's social feature is quite limited. We combine communities event and social interaction in a centralized app.

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Cool bro
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@krystian_n_l_ thank you

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Music has always been social
but most platforms made it feel personal and isolated.

Turning music into a shared experience again
with communities and real connections
feels like the right direction.

Curious how you plan to keep it from becoming
just another feed.

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Congrats on launching! A whole app built around sharing music. I love it! Do the communities form around specific artists or more around genres?

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@aya_vlasoff the user decides :) could be about an artist, a genre, or even both.

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Cool idea! Congrats on the launch!

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@basharath thanks!

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Such a cool concept! Android when?

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@lak7 coming soon ;)

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#6
Parallel Code
Use Claude Code, Codex, and Gemini in parallel
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一句话介绍:Parallel Code 是一款 macOS 应用,通过为每个AI编程助手自动创建独立的Git分支和工作区,让开发者能并行使用多个AI模型进行编码,解决了多任务并行时管理混乱、上下文冲突和效率低下的痛点。
Open Source Developer Tools GitHub
AI编程助手 开发效率工具 并行计算 Git工作流 macOS应用 开源软件 键盘优先 代码审查 终端集成 远程监控
用户评论摘要:用户普遍认可其核心的Git工作区隔离理念,认为能有效管理多个并行任务。主要关注点包括:不同模型输出质量对比、上下文隔离与共享机制、潜在的技术稳定性、团队协作可能性,以及具体功能细节如手机监控和冲突处理。
AI 锐评

Parallel Code 的聪明之处在于,它没有选择去“重构”或“包装”AI编程助手的工作流,而是选择成为现有工作流的“交通管制系统”。这看似保守的设计,恰恰是其最大的价值:零切换成本和对AI工具快速演进的兼容性。它精准地戳中了当前AI辅助编程的一个核心矛盾:开发者渴望并行利用多个模型的“集体智慧”来提升效率,但终端、Git和文件系统的线性管理方式却成了瓶颈。

产品将“分支”和“工作区”这两个成熟的Git概念作为隔离单元,是一个极具工程思维的解决方案。它本质上是在管理“计算过程”的副作用(代码变更),而非过程本身。这使得它可以冷静地旁观Claude、Codex、Gemini等模型在各自的沙箱里“狂奔”,无论它们内部如何迭代,最终只需验收其产出的代码差异即可。这种架构让工具本身避免了与AI模型发展的深度绑定,降低了被淘汰的风险。

然而,其真正的挑战或许不在于技术。评论中关于“模型间上下文传递”和“团队协作”的疑问,暗示了更深层的需求。当前的设计是极致的“隔离”,但复杂的软件开发往往需要“协作”与“共识”。当多个AI对同一模块做出不同架构决策时,开发者仍需扮演最终的仲裁者和系统架构师。工具提高了“尝试”的吞吐量,但并未降低“决策”的认知负荷。它是一款优秀的“想法验证加速器”,尤其适合探索性编程和独立开发者,但在需要高度一致性和架构约束的团队生产环境中,其价值可能需要更复杂的协作层来实现。它的成功,反映了当前AI编程工具从“单点智能”向“流程与编排”演进的重要趋势。

查看原始信息
Parallel Code
Parallel Code is a macOS app that gives every AI coding agent its own git branch and worktree — automatically. Use Claude Code, Codex, and Gemini in parallel. Free and open source.

Why I built Parallel Code


I've been maintaining an open source productivity app (Super Productivity) for 9 years and working as a programmer for much longer than that. When AI coding agents came along, they changed how I work - but the other tools and habits I grow comfortable with over the years, weren't a good fit anymore.

One agent works on a feature. I wait, get distracted, start something else. Finally, I come back, review, start the next one. Wait again. I had a backlog of ideas and the tools to build them, but things got messy. I was doing a lot, but I felt like I'd lost control compared to how I used to code.

I tried the obvious fixes. Multiple terminal windows were my new go-to solution, but got chaotic fast - which terminal was working on what? Tmux helped organize it, but I was still cycling through panes, switching tools for reviewing diffs and history, losing track of context, and dealing with merge conflicts when agents touched the same files.

So I built Parallel Code to fix this for myself.

The core idea: every task gets its own git branch and worktree automatically. Agents work in complete isolation - they can't conflict. I kick off 5, 8, 10 at a time, watch them all in a tiled view, and review diffs as they finish.

One design decision I'm particularly proud of: it runs your real terminal CLIs. Claude Code, Codex CLI, Gemini CLI - whatever you use today works exactly the same inside Parallel Code. Same behavior, same config, nothing changes. I didn't want to build another wrapper or chat UI. If you don't like the app, go back to raw terminals. Zero switching cost.

Some things I added along the way also turned out very useful:

- Phone monitoring - Scan a QR code, watch all your agent terminals from your phone. Sure there are other ways to do this, but this is really comfortable.

- Keyboard-first design - 40+ shortcuts. When you're managing 10 agents, reaching for the mouse is too slow. Best part is to navigate panes with just Alt+Arrow-keys.

- Built-in diff review and merge - The merge step is where quality happens. So having a quick way to do a code review is very useuful.

Parallel Code is free, open source (MIT), and always will be. No subscriptions, no platform fees, no telemetry. Your API keys stay on your machine.

I built this because I needed it. I'm sharing it because I think other developers - especially solo devs and indie hackers - hit the same problems I did. If you're running AI coding agents one at a time and don't have your tools setup in an optimal way, you're leaving a lot on the table.

macOS and Linux. Windows is on the roadmap.

Happy to answer any questions about the tool, the technical decisions, or why I chose to make it free.

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@johannesjo I am wondering how fast are the tokens getting burned, and how good are the limits?

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really cool concept, using multiple models in parallel makes so much sense because each one has different strengths. do you notice big differences in output quality between claude and gemini for the same task?

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I’ve tried using Claude and Codex together, but they often lose context when switching between them.

Curious how Parallel Code handles this. Do agents share context or is everything isolated per branch?

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The git worktree isolation is the real killer feature here. I've been juggling tmux panes with Claude Code and it gets messy fast once you go past 3-4 parallel tasks. Having built-in diff review on top of that is a nice touch - that's usually where I lose the most time. Gonna try this out today.

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Nice work shipping this. Running agents in isolated worktrees is the right call. The next 48 hours are when you find out what breaks under real load. Different OS environments, edge cases in the worktree management, sync issues. There's a free community stress-testing page where you post your URL and people try to find bugs. Findings come with screenshots. Saved me a few fires.

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I've been doing this manually with tmux panes and git worktrees, so seeing it packaged as a proper tool with diff review is nice. The "zero switching cost" angle is key -- keeping agents as raw terminal CLIs instead of wrapping them in some custom UI means you're not betting against the pace these tools evolve at. What does the mobile monitoring actually show you -- just status, or can you intervene mid-task?

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Running Claude Code and Codex side-by-side has become my default for anything non-trivial - they catch different things and the diff between their outputs is often the most useful signal. The context handoff between models is where it gets tricky, especially when they diverge on architecture decisions.

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@mykola_kondratiuk Yes, I feel you. Model handoff is still tricky to solve. Personally I do this via dedicated skills (on claude code's end, which my main agent these days).

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The isolated git worktree approach for running 10 agents in parallel is genuinely clever — no conflicts because each agent works in its own branch is the kind of thing that sounds obvious in hindsight but takes real thought to execute well.

I'm building CVDebug, an ATS resume scanner with Robot View that shows candidates exactly what Workday, Taleo and 50+ ATS bots see when they parse their CV, with an ATS score 0–100. Very different space, but I love the MIT open-source angle — transparency in how tools work is something I try to bring to the resume/hiring side too. Great launch Johannes!

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@aherme13 Thank you very much albert! <3 Best of luck in your endevours!

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This looks great for solo devs. Any plans to support team setups where multiple people dispatch agents to the same repo?

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@ermakovich_sergey Interesting direction! This hasn't popped up yet as a feature request tbh, but if there is interest, I am definitely open in exploring that option.

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40+ keyboard shortcuts?? ok you have my attention 😂 I'm building a productivity app myself and I'm obsessed with keyboard-first workflows — reaching for the mouse when you're deep in flow is painful. The Alt+Arrow navigation between panes sounds super smooth. Definitely trying this out, congrats on the launch! 🚀

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The automatic git branching is a solid idea, but how do you handle potential merge conflicts when multiple AIs are working on the same codebase?

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@trydoff I just tell AI to rebase on master/main (there is also a button for it in the merge dialog). It usually autofixes any merge conflicts very well.

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#7
Cline Kanban
CLI-agnostic kanban for multi-agent orchestration
150
一句话介绍:Cline Kanban 是一款将多AI智能体开发任务从终端命令行可视化到看板上的工具,解决了开发者在并行协调多个AI编码代理时终端混乱、状态难以追踪的核心痛点。
Productivity Artificial Intelligence Development
AI智能体编排 开发运维可视化 多代理协作 看板管理 Git工作流 开发工具 Claude Code集成 终端增强 任务链依赖
用户评论摘要:用户普遍赞赏其通过Git工作树隔离实现代理并行不冲突的设计,认为它提供了急需的多代理操作可视化。核心关注点在于依赖任务失败时的处理逻辑、状态持久化机制,并提出了依赖关系视图、API/webhook触发等高级功能建议。
AI 锐评

Cline Kanban 的实质,并非简单的终端日志可视化,而是试图为当前混乱的“多智能体编程”范式建立一套工程纪律。其核心价值在于两个关键设计:一是将每个智能体任务强制隔离于独立的Git工作树,这从物理层面规避了代理间的文件冲突,将智能体的“野性”输出约束在版本控制的沙箱内;二是将抽象的“链式调用”转化为看板上可拖拽、可链接的卡片,为不可预测的AI过程提供了可中断、可审查的人机交互点。

产品敏锐地抓住了当前AI编码从“单代理提示”迈向“多代理协作”过程中的真空地带。开发者不再只是与一个AI对话,而是在导演一群能力各异、状态不稳定的AI演员,传统终端显然已无法承载这种复杂度。看板模式在此提供了稀缺的“全局状态感知”,而内嵌的Diff审查与评论功能,则试图将人类监督无缝嵌入到AI的自动化流程中,确保最终控制权。

然而,其真正的挑战在于“状态管理”的深度。评论中关于任务失败重试、依赖阻塞的疑问直指要害:当智能体任务因意外输出而中断,看板如何管理这种“例外状态”?是简单地标记失败,还是能引导进行智能回滚或重试?产品目前依赖Git作为状态持久化层是一个巧妙的取舍,但Git管理的是结果,而非智能体推理的中间过程。这或许意味着,它更擅长管理已明确分解的、颗粒度合适的任务,而非高度动态、探索性的复杂工作流。它是一套优秀的“多AI代理运维系统”,但能否成为定义下一代AI协同开发模式的“操作系统”,取决于其能否从可视化协作层,下沉到更稳固的智能体状态与异常处理协议层。

查看原始信息
Cline Kanban
Cline Kanban brings your agents out of the terminal and into the board. Create, manage, and chain agent tasks within a single view. Claude Code and Codex compatible.

Long time user of Cline now. Kanban looks really cool, excited to try

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@shubham_kukreti Thanks Shubham, let us know how you like it! 💪

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Hi everyone!

Cline Kanban is exactly the multi-agent UI I’ve been wanting.

You get a proper Kanban board where every card spins up its own git worktree and terminal. Agents run in parallel without stepping on each other. You can link cards for dependencies, review diffs and leave inline comments, and ship commits straight from the board.

It works cleanly with @Claude Code, @OpenAI Codex CLI, and @Cline right now. No more drowning in a sea of terminals while trying to keep track of everything.

npm i -g cline

then just run cline from any repo.

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@zaczuo Curious, how does it handle agent conflicts or retries on failed tasks in linked dependencies?

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@zaczuo When two parallel agent cards have a dependency link and the upstream one produces unexpected output, does the downstream card pause and wait for human review or does it try to adapt and keep running automatically?

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@zaczuo This will be so much helpful while debugging since it takes multiple AI models to think from different perspective to resolve critical issues.

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The git worktree isolation per card is a smart design choice -- that's the part most multi-agent setups get wrong by letting agents collide in the same working directory. One thing I'd love to see is some kind of dependency graph view so you can visualize which tasks are blocking others. Are there plans for webhook or API triggers to kick off cards programmatically?

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@greythegyutae Webooks are coming! I'm curious to see how people use them to add even more autonomy to kanban.

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Finally a proper visual way to manage multi-agent chaos. I've been running Claude Code sessions in separate terminals and it's basically "hope I remember which tab is doing what" 😅 The kanban approach with isolated git worktrees per card is such a natural fit. Being able to review diffs and leave comments right from the board instead of switching to another tool is a nice touch too. Trying this tonight!

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@thenomadcode Reviewing diffs is the new software engineering, welcome to the future! 🚀

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Multi-agent orchestration visibility is still pretty rough in most setups - you end up with a bunch of terminals and no real picture of what each agent is doing. How are you handling state persistence between sessions? That seems like the hard part when agents get interrupted mid-task.

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@mykola_kondratiuk The agents can pick up that they're working in a worktree so intelligently resolve merge conflicts. And git is the best state persistence between tasks! I find agents look at recent commit history to get its bearing, and kanban enforces good git hygiene to get this working squeeky clean.

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#8
Peopling
Practice difficult conversations before they happen
127
一句话介绍:Peopling是一款AI驱动的语音角色扮演应用,为管理者及职场人士提供了一个私密空间,用于预先演练棘手的职场对话(如反馈、对齐、一对一沟通),帮助用户在实际发生前练习并提升沟通能力,从而避免因沟通不善带来的问题。
Productivity Online Learning Career
AI教练 职场沟通训练 语音角色扮演 管理者工具 软技能提升 对话模拟 绩效反馈演练 一对一会议准备 情商训练 个人成长应用
用户评论摘要:用户普遍认可产品价值,尤其对内向者和新晋管理者是福音。有效评论集中在功能询问与建议:包括能否自定义对话方人格与态度、AI是否支持实时动态反应、以及场景能否扩展至客户/合作伙伴谈判等。开发者确认支持自定义人格和动态对话。
AI 锐评

Peopling切入了一个长期被理论培训占据、却缺乏有效训练方法的痛点:高风险职场对话的实操演练。其真正价值并非简单的“AI陪聊”,而在于将教练服务的核心——安全环境、即时反馈、重复练习——产品化、民主化。它用动态AI角色扮演替代了脑海中虚幻的排练,创造了可量化的“沟通肌肉记忆”训练场。

产品聪明地避开了试图替代人类教练的陷阱,而是定位为“练习工具”,这降低了用户预期和伦理风险。其“自定义人格”功能是点睛之笔,它承认了艰难对话的症结常在于特定的“人”,使得训练更具针对性。从评论看,用户已自发将其使用场景从员工管理延伸至客户谈判、甚至减少口头禅,这揭示了产品底层逻辑的延展性:任何需要预演的真实人际沟通。

然而,其面临的挑战同样尖锐。首先,对话质量的“真实性”天花板受限于AI对复杂人性、办公室政治微妙之处的理解深度。其次,作为训练工具,其效果难以量化,需要更科学的反馈机制(如语音分析、策略建议)来构建竞争壁垒。最后,当前模式可能陷入“场景库”扩张的军备竞赛,而更深层的价值或许在于对用户沟通模式的长期追踪分析与个性化改进路径的生成。

总体而言,Peopling代表了AI应用从替代重复劳动(如写作、编程)向替代“高风险试错”迈出的有趣一步。它能否从一款新颖的工具成长为必备的职业技能平台,取决于其能否将训练数据沉淀为不可替代的个性化沟通洞察。

查看原始信息
Peopling
Most managers learn to have hard conversations by having them badly. Peopling gives you a private space to practice.AI-powered voice roleplay for the conversations that actually matter: the feedback you've been avoiding, the alignment talk you keep rescheduling, the 1:1 that's quietly going sideways. Built by a coach who's worked with engineers and managers across Stripe, Netflix, Roblox, Headspace, and more. Less theory. More reps.
Coaching changed how I show up at work. I want that for everyone — not just the people lucky enough to have a great manager or mentor. That's Peopling.
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This is a good idea – esp. when you are an introvert like me and had to come up with 5 possible scenarios and answers to each of them. Now, you do not have to retain everything in your head but split parts. 😅 introverted people know :D

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Congrats on the launch and the product! It seems super helpful, and I really appreciate that you took what worked for you and turned it into a product for everyone to have access to it 🙌

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As an introvert, I used to rehearse conversations in my head, this product changes that.
You don’t have to keep everything in your head anymore, just show up more confidently.

Introverts will definitely get this. 🙂

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This is a brilliant idea! I think this is particularly great for those new to leadership positions and aren’t yet comfortable or skilled in these conversations. Is there a way to input the behaviours/attitude of the person users would be having the conversation with, so the AI can adapt to match that energy?
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@leah_dyke Yes! I have these in the form of "personas." You can select from the pre-baked ones I have per scenario or you can create your own!

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I love the concept, but will Peopling adapt to real-time feedback and emotions during a conversation, or is it strictly pre-scripted scenarios?

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@trydoff Yes! The Agent is fully dynamic and will react to realtime conversations. The video I shared shows this dynamic conversation in action.

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So great to see this live @kent_wills
I know how such programs can be transformative for people and this is a clever way to use AI for self growth.

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hey @kent_wills great concept. I actually needed something like this two days back for a negotiation call.

if this was a legit startup, I would have pitched to be a founding designer, honestly.

went through the onboarding and had tons of thoughts about making it better, so I built a quick prototype to give you an overview of what the experience could be, and what it could do for conversion.

Recorded a short Loom walking you through it: https://www.loom.com/share/45bb54b1819c47369f8ad437722d4866

LMK your thoughts🙌

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Congrats on the launch Kent!! This is a fantastic idea ⭐ - I've been looking for something similar to help coach me out of saying filler words in my sentences, perhaps this could be an expansion!

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Really like that this is voice-based and not just text chat. There's something about actually saying the words out loud that builds the muscle memory for real conversations. The custom persona feature is smart too - every difficult conversation has a specific person on the other end with their own style.

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As a solo founder, the hardest conversations aren't with employees -- they're with churning customers or partners where you need to push back on scope. The voice roleplay angle makes this way more realistic than just reading a script. Does the AI adapt its pushback based on how the conversation is going, or does it follow a fixed scenario?

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@greythegyutae Yes! The roleplay agent adapts! That being said I have some more agreeable agents and less agreeable agents so depending on which one you pick the difficulty can really get hard! You can also create a custom persona that mimics the current situation you are dealing with.

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Isn't this the same as https://drobinin.com/apps/murmur/ that was promoted here too a few days ago ?

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@nabu_chodonosor Not sure, but the more of these types of apps for people being created, the better!

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#9
Pensieve
Full company context for every AI agent
125
一句话介绍:Pensieve通过连接企业现有工具并构建动态知识图谱,为AI智能体提供深度的公司业务上下文,使其能像资深员工一样理解组织内的人员、项目、决策与客户关系,解决了AI智能体因缺乏业务背景而需反复手动提供上下文、无法自主进行深度推理和关联的痛点。
Developer Tools Artificial Intelligence Business Intelligence
AI智能体平台 企业知识图谱 业务上下文理解 组织智能 AI赋能工具 多工具集成 无平台费 自主推理 团队协作 数据蒸馏
用户评论摘要:用户肯定产品概念,核心问题集中在:1. 如何自动提炼信息关联而无需手动标注;2. 如何实现基于角色的访问控制,防止敏感信息泄露;3. 创始团队回应将探索数据层权限隔离,但承认技术挑战。用户期待更多集成。
AI 锐评

Pensieve瞄准了一个真实且日益尖锐的痛点:当前接入企业工具的AI智能体,本质仍是“高级搜索器”,缺乏对业务脉络、历史决策和人际关系的系统性理解。其宣称的价值不在于简单的工具连接,而在于“蒸馏”和“维护”一个动态的知识图谱,这试图将AI智能体从“临时工”提升为“正式员工”。

然而,其面临的挑战极为严峻。首先,技术层面,“自动蒸馏”与“精准权限控制”存在根本性矛盾。知识图谱的价值在于发现隐式关联,但这过程很可能无意中混合了不同权限级别的数据。创始人承认的“数据层边界”难题是关键,若处理不当,要么图谱价值大打折扣(因过度过滤),要么酿成严重的数据泄露风险。其次,产品定位上,“免费+自带推理”模式降低了试用门槛,但也将核心收入压力后置,其长期商业模式和作为“平台”的护城河尚不清晰。最后,价值验证层面,用户需要看到智能体基于其图谱做出的、超越简单信息检索的“洞察”或“行动”案例,否则它可能只是另一个结构更复杂的知识库。

真正的颠覆性在于,如果Pensieve能成功将分散、非结构化的企业数据流,转化为AI可原生理解且安全可控的“组织记忆”,它将可能成为企业AI时代的“操作系统级”基础设施。但目前,它仍处于用精巧概念挑战复杂工程与组织伦理的早期阶段。成功与否,取决于其能否在“理解深度”与“安全边界”之间找到那个微妙的、可信的平衡点。

查看原始信息
Pensieve
AI agents are getting smarter, but they still don't understand your business. Every conversation starts with copy-pasting context and re-explaining the backstory. MCP gives agents tool access. Pensieve gives them understanding. We connect your tools and build a living picture of your organisation. People, projects, decisions, customers and how they all relate. Agents reason over the full picture and surface what nobody sees alone. Free. Bring your own Anthropic, OpenAI or Google inference.

Hey Product Hunt! I'm Euan, co-founder of Pensieve.

AI agents are incredibly intelligent but they don't understand your business. You can give an agent access to your tools via MCP, and it can pull data from Slack or Linear. But that's not the same as understanding. A new hire can access your Slack too. It doesn't mean they know what's going on.

What makes an employee effective isn't tool access. It's the context they build up over months and years. Who's working on what, why that decision was made in January, how the sales pipeline connects to the engineering roadmap, which customer relationships matter. That's what lets them make good judgment calls.

We built Pensieve to give AI agents that same understanding. We connect to the tools you already use, but we don't just make them searchable. Think about the difference between a raw codebase and a well-maintained CLAUDE.md. One is searchable data, the other is understanding. Pensieve curates and distils your company knowledge into a format AI natively understands, so an agent can operate like a fully onboarded employee, with the intelligence of a frontier model.

Once agents have that depth of context, they can work in the background and surface things no single person catches. Connecting what customers say on calls with what engineers discuss on Slack with what the usage data actually shows.

Pensieve is free. Bring your own Anthropic, OpenAI, or Google inference. No platform fee, no credit card.

What's the biggest limitation you've hit trying to get AI agents to actually work in your business?

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@euan_cox13 How does Pensieve auto-distill those interconnections without manual tagging?

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Cool concept! We've been planning to build a contextual knowledge base internally, so this caught my attention.

Quick question though: how do you handle role-based access control? We have context that should only surface for Project Managers (client budgets, escalation notes) and other stuff that's strictly Leadership-level. If everything gets ingested into one knowledge graph, how do you prevent the agent from leaking restricted context to someone who shouldn't see it?

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@michal_kukul Really good question, and a genuinely hard problem to solve well. We've thought about this a lot.

For most teams, the default is a shared organisation where you connect data sources you're happy for the whole team to see. We've found that a lot of companies are fine with this. Project updates, engineering discussions, customer feedback, product decisions. Most of it is shared context anyway, and that's where the bulk of the value comes from.

If you do care more about the permissions side, each user can connect their own tools and create their own organisation in Pensieve. You can have as many organisations as you want. All the data within that organisation comes only from tools they have access to, so it's a completely isolated context layer. You still get a full organisational picture, it's just built from everything that user can personally see.

Longer term, the direction we're exploring is a shared context layer where each user connects their own tools and we tag entities with their source permissions so we can filter at the data layer and only surface information to a user if they have access to all the source materials used to derive it. You raise a good point about leakage though: even with filtering, the agent has technically seen restricted context while researching, and there's a risk of that bleeding through. That's exactly why we haven't rushed it. Getting the filtering right so it's a real data-layer boundary and not just a prompt-level one is the hard part.

I'd be curious to hear more about how you're structuring your internal context layer?

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Hey PH! James here, co-founder of Pensieve.


We're heavy Claude users, and the thing that transformed our coding workflow wasn't better search over our codebase — it was maintaining architecture files. A good CLAUDE.md means an agent drops into a session already understanding what the codebase does, what the product goals are, and how everything fits together. It doesn't need to grep through every file to build that picture from scratch each time.


Most AI-for-business tools today are search layers. They let agents query your underlying data, which is useful, but it's the equivalent of giving a new developer grep access and calling them onboarded. What's missing is the pre-researched, maintained understanding — the business equivalent of those architecture docs.


That's what we're building. Pensieve connects to your tools and continuously maintains a living knowledge graph of your organisation. People, projects, customers, decisions, and how they all relate. So when an agent starts a conversation, the context is already there — not searched for, already understood.


Would love to hear what integrations you'd want first — that's what we're prioritising next.

:pray:
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#10
GuideYou
Guidance for everyday technology
116
一句话介绍:GuideYou是一款通过创建可视化分步指南,帮助家庭成员在无需反复求助的情况下,独立完成日常技术操作(如登录、设备设置)的工具,解决了非技术用户反复求助、指导者重复解释的痛点。
Home improvement Family Community
家庭科技支持 可视化操作指南 分步教学工具 数字扫盲 远程协助 SaaS 用户体验优化 私人家教 生产力工具 家庭工作区
用户评论摘要:用户共鸣强烈,认可其解决“为家人重复提供技术支持”的核心痛点。一条有效反馈指出Gmail注册流程存在“无效访问”错误,建议检查或保留传统密码注册方式。
AI 锐评

GuideYou看似是一个解决“家庭科技支持”场景的垂直工具,但其真正价值在于将非结构化的、高时间成本的隐性知识(个人经验)转化为可复用、可迭代的结构化知识产品。它本质上是一个极简的“知识沉淀与交付”系统,瞄准的是传统图文教程与实时视频通话之间的巨大空白——即时性要求低、但容错率也低的日常操作指导。

产品聪明地避开了复杂的屏幕共享或实时通讯,采用“截图加热点”的异步模式,这降低了使用门槛,但也将成功与否高度依赖于指南创建者的抽象与教学能力。其宣称的“AI生成素材”功能是关键的潜在增长点,若能根据文字指令自动生成示意界面图,将大幅降低创作成本,从“记录工具”转向“创作工具”。

然而,其最大挑战并非技术,而是用户习惯。它要求指导者从“接电话-口头解答”的被动反应模式,转变为“预先创建-系统管理”的主动建设模式。这种心智转换的门槛很高。此外,其商业模式和场景扩展性存疑:在家庭场景外,能否渗透至企业内训、客户成功等领域?面对更复杂的流程,其简单的热点标注是否足够?它需要证明自己不仅仅是“孝顺工具”,而是一个普适性的轻量级知识传递基础设施。

当前版本是一个精准的痛点切入,但要从“贴心产品”成长为“可持续业务”,必须在降低创建负担、拓宽应用边界以及构建可网络效应的公共指南库上,找到更深的护城河。

查看原始信息
GuideYou
GuideYou helps you create simple visual step-by-step guides your family can follow without calling you every time. Upload screenshots, highlight what to tap, and share guides in a family workspace. Works on any device, supports feedback when screens change, and stays signed in for easy access. Explain things once and let others follow anytime.
A few months ago I realized I was basically doing tech support for my parents every other night.It was always the same: “TV is not working” “How do I log into my bank?” “Why does this look different?” I tried everything - screenshots, phone calls, even writing steps in notes but nothing really stuck, they were always lost somewhere and... a couple of weeks later, same problem again. So I built GuideYou - a simple way to create step-by-step visual guides that anyone can follow. Now instead of explaining things repeatedly, I just create a guide once and my parents use it whenever they need. So basically, my parents are now my QA team 😄 ✨ What GuideYou does - Create visual step-by-step guides - Upload screenshots/photos and highlight exactly where to tap - Interactive guidance - Use glowing hotspots and simple instructions - Family workspace - Share guides with family members (Admin / Editor / Viewer roles) - Real-time feedback loop - “This doesn’t look right” button sends feedback instantly - Works on every device - It’s a web app - you can even add it to your home screen like a native app - Stay signed in - No constant logins — designed for non-technical users - Private by default - Guides are only visible within your family - Public guide library (small but growing) - Share useful guides with others - AI asset generation - Generate visuals for guides when screenshots aren’t enough 💡 Why I built this The real problem isn’t explaining something once. It’s explaining the same thing over and over again. GuideYou turns that into: explain once → reusable forever 🎯 Who it’s for - People helping parents or grandparents with tech - Families supporting each other - Anyone tired of repeating instructions - Non-technical users who need simple guidance 🚀 What I’m looking for I’d love feedback on: - onboarding & first-time experience - guide creation flow - clarity of instructions - anything confusing or unnecessary
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@gosu94 How familiar this is (when loved ones call with requests like this! A video about me)))

Good job coming up with this! Good luck

2
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Love this!
The Gmail sign up flow currently returns invalid access may want to check that out or leave the traditional sign up with password only.

0
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#11
CodingPrep
Open Source coding interview prep tool with AI interviewer
102
一句话介绍:CodePrep是一款开源AI面试陪练工具,通过模拟真实技术面试场景(语音对话、代码编写、测试与反馈),解决求职者在传统刷题模式中缺乏互动演练和针对性反馈的核心痛点。
Software Engineering Developer Tools GitHub Audio
技术面试准备 AI陪练 开源工具 编程练习 实时反馈 语音交互 代码执行 学习进度追踪 开发者工具 模拟面试
用户评论摘要:用户反馈两极。支持者认可其解决真实面试演练痛点的理念;批评者指出产品存在严重漏洞、语音不自然、费用消耗快。有效建议包括支持本地模型、扩展编程语言、按公司定制题库。
AI 锐评

CodePrep试图用AI agent重构技术面试准备流程,其真正价值不在于“又一个刷题平台”,而在于将“单向解题”转变为“双向互动面试模拟”。这直击了传统LeetCode模式的最大短板:算法正确性不等于面试通过率,沟通与思维过程展示才是关键。

然而,产品目前陷入“概念惊艳,执行粗糙”的典型AI初创陷阱。创始团队用AI agent快速构建产品的故事很吸引人,但用户尖锐的“vibecoded slop”评论揭示了致命伤:基础体验崩坏。语音不自然、高额API消耗($0.22/8次请求)暴露了其过度依赖单一外部AI服务且缺乏成本优化,这直接侵蚀了工具的可重复使用性。更严重的是,仅支持Python与“完全开源”标语存在潜在矛盾,因为核心智能仍绑死在商业API上。

产品的未来取决于能否在“快速原型”与“可靠产品”间找到平衡。它必须回答:是做一个展示AI整合能力的酷炫demo,还是一个能承受每日高频练习的稳健工具?若选择后者,则必须解决模型本地化部署、多语言支持、成本控制等工程问题,否则其“真实感”优势将被糟糕的可靠性与经济性彻底抵消。在AI编程工具泛滥的当下,解决真问题需超越技术噱头,回归稳定与实用。

查看原始信息
CodingPrep
CodePrep helps you practice coding interviews in a way that actually feels useful. Instead of grinding random problems, you can talk through solutions, write code, get tested, ask for hints, and receive clear feedback on what to improve. It includes voice mode, built-in code execution, study mode, and progress tracking, so you can practice like a real interview and get better faster.
Built this for a few friends who were prepping for coding interviews and kept saying the same thing: most prep tools help you solve problems, but not actually practice interviewing. So I made CodePrep to feel a lot closer to the real thing. You can talk through your solution, write code, get tested, ask for hints, and get feedback that’s actually useful afterward. The fun part: this was built entirely with AI agents. That made it possible to move fast, experiment a lot, and turn an idea that started as “this would be useful for my friends” into a real product. Would love to hear what you think: does this feel more useful than the usual coding prep flow? what would make you actually come back and use it regularly?
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This product literally doesn't even work. Completely bug riddled across so many cases, the voice interviewer feels so unnatural, and it burns through credits at an unbelievably fast rate (8 requests so far have cost me $0.22). Pure vibecoded slop that was evidently not even tested.

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Congratulations on the launch! It's a very cool idea. I'm curious why you went for just OpenAI rather than e.g. supporting ollama or custom endpoints to make it fully local? Also, in your FAQ about "why Python only" it implies that actual python code is run, not just assessed: Is that just for user code or does the application write and run arbitrary code?
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Cool idea. Suggestion/question: could it search the web and find suitable interview code questions to prepare on, for the particular company someone is aiming to join?

0
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#12
Dipshot
Capture, Annotate & Export
94
一句话介绍:Dipshot是一款macOS菜单栏轻量级应用,通过一站式截屏、标注和添加定制背景,解决用户在分享截图时因切换工具而中断工作流的痛点,尤其适合开发者、独立创作者等需要快速产出精美视觉内容的场景。
Productivity Menu Bar Apps Maker Tools
截图工具 macOS应用 菜单栏工具 效率工具 图片标注 视觉美化 工作流优化 轻量级应用
用户评论摘要:用户普遍认可其菜单栏集成、不打断工作流的核心设计。有效反馈集中在功能询问:支持的导出格式、批量处理能力、与系统内置工具的速度对比,以及设置常用标注模板的可能性。
AI 锐评

Dipshot切入的是一个看似微小却真实存在的效率缝隙:从“功能性的截图”到“传播性的视觉内容”之间的最后一公里。其真正的价值并非简单的标注功能,而是将“美化”这一通常需要跳转到专业软件(如Figma)的高成本动作,降维成菜单栏内的“一键式”操作,从而将截图分享的体验从“生产流程”无缝过渡为“沟通动作”。

产品聪明地抓住了现代工作流中“上下文切换”这一隐形杀手。然而,其面临的挑战也同样清晰。首先,其核心功能“背景美化”的壁垒并不高,容易模仿。其次,用户评论已触及工具类应用的核心:规模化与自定义需求。询问批量处理和模板功能,正说明早期采纳者已不满足于单点优化,而希望将其嵌入更重复、更批量的工作场景中。这意味着如果停留在v1的“单张图片精修”模式,它可能只是一个“不错的甜点应用”;若能向“批量化、模板化、自动化”演进,才有机会成为工作流中的“基础设施”。

此外,其与系统原生截图工具的“速度对比”将直接决定用户的去留。在效率工具赛道,快0.5秒即是护城河。总体而言,Dipshot展现了一个优秀工具应用的起点:精准切入痛点、极致简化路径。但其长期价值,取决于它能否从一个“精美的包装器”,进化成一个“智能的视觉内容流水线”。

查看原始信息
Dipshot
Dipshot is a lightweight macOS menu bar app for capturing and annotating screenshots. Add arrows, text, shapes, and callouts, then export clean, polished visuals — all without breaking your flow.
Hey Product Hunt! 👋 I'm the maker of Dipshot — a macOS menu bar app that turns plain screenshots into beautiful, share-ready visuals. The idea came from a simple frustration: every time I wanted to share a screenshot — for a tweet, a changelog, or a product update — it looked boring and raw. I'd have to jump into Figma or another tool just to wrap it in a nice background. That breaks the flow completely. With Dipshot, you capture your screen and instantly get a polished result with a customized background — gradients, solid colors, wallpapers — right from your menu bar. No context switching, no extra apps. Perfect for: - Developers sharing project progress - Indie makers posting on social media - Anyone who wants their screenshots to look intentional and professional This is v1, and I'd love your feedback. What backgrounds or customization options would make this a must-have for you? 🙏
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Clean execution on this — a menu bar screenshot tool that handles capture, annotation, and export without leaving your flow is exactly the kind of utility app that becomes indispensable once you start using it. I take a lot of annotated screenshots for bug reports and docs, and the friction of opening a separate app every time is real. The fact that it lives in the menu bar and does everything inline is the right call. What export formats do you support? And is there any way to set up quick templates for recurring annotation patterns (like always adding the same type of callout)?

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Congrats @abduns on the launch! I like the menu bar approach. How you handle batch processing when you need to annotate multiple screenshots at once?

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The app looks great and has very good UI. Congrats on the launch 🎉

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Nice and practical keeping everything in the menu bar and not breaking flow is a big win for this kind of tool curious how it compares speed wise to the built in screenshot tools

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#13
Habit Streaker
Streak Your Way Towards Success
25
一句话介绍:一款基于Notion的模板,通过可视化的“连续打卡”机制,帮助用户在单一页面集中追踪习惯养成进度,解决习惯难以坚持和进度分散的痛点。
Health & Fitness Productivity Notion
习惯追踪 Notion模板 生产力工具 个人成长 习惯养成 打卡 自我管理 生活仪式化 模板 进度可视化
用户评论摘要:评论以祝贺为主,创始人强调这是其自用的强大系统。有用户指出“连续打卡”是养成习惯的简单有效技巧。整体反馈积极,但缺乏具体功能讨论或改进建议。
AI 锐评

Habit Streaker本质上是一个封装了“连续打卡”理念的Notion模板,其核心价值在于将流行的行为设计学方法(如“不要打破链条”)产品化、模板化。它巧妙地利用了Notion的普及性和灵活性,降低了用户构建个人管理系统的门槛。然而,其“产品”属性非常脆弱——它并非一个独立APP,功能深度完全受限于Notion平台,可替代性极强。任何熟悉Notion的用户都能在短时间内自行复刻。

它的真正卖点并非技术或创新,而是“预设的系统”和“开箱即用”的便利性,为目标用户(渴望自律但畏惧复杂设置的人)节省了时间与心智成本。创始人作为“Notion顾问”的身份,为模板的权威性和设计感做了背书。但风险也同样明显:其长期价值完全依赖于用户对Notion的持续使用粘性,且商业模式天花板极低,极易被复制。它更像一份精心包装的“数字指南”,其成功更多是内容营销和社区推广的胜利,而非产品力的颠覆。在习惯追踪这个红海市场,它提供了一个极轻量级的切入点,但要想从“模板”进化为“解决方案”,前路漫漫。

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Habit Streaker
Streak Your Way Towards Success Do you have problems with tracking your habits? Do you want to see your habit streaks in a simple way and in one place? Good habits are important. They are your fuel and drive you to become the best version of yourself. And tracking their progress keeps you motivated at all times. That's why I created this template. Where your habit progress and streaks are organized in one place. Are you ready to gamify your life and become the best version of yourself?
Hi ProductHunters and everyone else 👋 I'm Matthew, Notion consultant and creator of this product. This is the exact system I use to stay disciplined and create good habits for my success. Now I want to share it with you :) What you'll get? 🔹 Habit Streaker Notion template where you can organize your habits, streaks, highest score and notes and store everything in one place 🔹 Guide with explanation of each module 🔹 Instructions how to use the template You can also customize this product for your needs, because this isn’t something that’ll help you for a mere few weeks or months. It’s something I’ve designed with the aim to last for years and decades. Who is this for? 🔹 People who want to track their habit progress and take accountability 🔹 People who want to know exactly what they need to focus on in order to progress in their lives 🔹 Anyone who's serious about their habits and wants to become more organized 🔹 You! What are you waiting for? Streak Your Way Towards Success Grab your Habit Streaker today! Click "Visit" above to grab your Habit Streaker. Any feedback appreciated :))
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One of the most powerful yet simple tricks to build good habits or remove bad ones is knowing your streaks; you never want that number to go down to 0. Congrats, Matthew, on the launch

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@olsnotion Indeed, that's a very powerful system!

Thank you bro! :))

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Congrats on your launch!!!
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@chape Thank you David! 😎

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Congrats on the launch!

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@basharath Thank you!

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#14
Struere
Make your spreadsheets work like software
16
一句话介绍:Struere利用AI将电子表格转化为实时仪表盘、自动化提醒和工作流,为那些已超越Excel能力但尚未准备好采用复杂昂贵企业软件的中小团队,提供了平滑过渡的解决方案。
Analytics SaaS Artificial Intelligence
表格智能化 AI仪表盘 工作流自动化 中小企业工具 Excel替代品 低代码平台 数据可视化 团队协作 SaaS 效率工具
用户评论摘要:用户认可其精准定位了中小团队在Excel与大型企业软件间的过渡痛点。主要问题集中在AI生成仪表盘的自动化程度(是否需手动定义),创始人回复可自动生成并支持用户提示调整。评论普遍认为其是Airtable等产品的轻量替代。
AI 锐评

Struere切入了一个经典且顽固的市场缝隙:“Excel失灵”与“企业级软件过载”之间的无人区。其宣称的“AI原生”与5分钟部署是核心卖点,但也是最大的风险点。

产品价值不在于其技术有多颠覆,而在于其路径依赖的巧妙利用。它不要求用户改变以表格为核心的数据结构和操作习惯,而是试图为这些静态表格注入“软件”的交互与自动化能力。这降低了迁移的心理门槛和操作成本,是典型的“包裹进化”策略,而非“颠覆革命”。

然而,其真正的挑战也在于此。首先,“AI自动构建仪表盘”的智能程度和可靠性存疑。通用表格数据结构杂乱,AI能否准确理解业务逻辑并生成有意义的视图,是产品能否兑现承诺的关键。其次,其定位的“过渡性”可能成为增长天花板。当团队真正成长后,是选择继续深耕Struere,还是必然迁移至更强大的平台?这决定了它最终是一个“跳板”还是一个“终点”。

评论中透露的“随着用户学习而增加组件”的发展思路,显示了其产品迭代将与用户生态深度绑定。成功与否,取决于它能否在“足够轻便”与“足够强大”之间找到那个精妙的平衡点,并快速形成核心用例的闭环。它面临的不是技术竞争,而是对中小企业复杂、模糊、动态的需求的洞察与抽象能力之战。

查看原始信息
Struere
Struere turns your spreadsheets into live dashboards, automated alerts, and workflows using AI. Built for teams who have outgrown Excel but are not ready for complex and expensive enterprise software.
In my experience, small teams and small businesses rely on Excel to run their operations. It works until it doesn't. As complexity grows, Excel's capability shrinks and the team starts hitting walls. The obvious alternatives, Monday, Airtable, ServiceNow, are expensive, rigid, and take months to migrate to. Most small teams are not ready for that. Struere is AI-native and takes less than 5 minutes to set up. Upload your data and it builds live intelligent dashboards on top of it. We layer in role-based access, automated alerts, and workflow automations so teams can run their operations exactly how they already work, without adapting to someone else's SaaS framework.
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The gap between "Excel is breaking down" and "we're ready for a full enterprise migration" is where so many small teams get stuck for way too long, and this seems to hit that exactly. When you upload existing spreadsheets, does the AI figure out the dashboard structure on its own or do you still need to define what you want to track?

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@simonk123 It figures out on its own and on top of the user can prompt each component to bring specific data only. Also add more components that are called widgets on the platform. As we learn from more user we will bring more components to solve those use cases.

And I appreciate your comment, that's the gap where I am trying to come in.

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This is a great alternative to Airtable. All the best!

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Thank you @basharath I appreciate your comment. Let me know if you or any of your friends need help signing up.

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#15
talk.
Get paid to talk.
14
一句话介绍:一款通过付费预约一对一视频通话,让任何人能够出售自己的时间与经验、或获取外部建议与陪伴,解决特定场景下寻求跨圈层、即时性、高质量对话需求的市场平台。
Social Media Marketing Education
知识付费 一对一咨询 经验共享 时间交易 视频通话平台 轻咨询 陌生人社交 C2C服务市场
用户评论摘要:用户认可“人与人真实对话”的不可替代性,认为其是连接优质人才的潜力市场。有效提问指向平台最佳适用领域(细分市场)及互动机制(如何启动)。整体反馈积极但较为笼统。
AI 锐评

Talk. 所标榜的“为谈话付费”模式,实质是将“时间”与“经验”商品化的C2C平台,其野心在于构建一个万物皆可咨询的轻量化市场。它瞄准的痛点是真实的:在高度垂直化与算法茧房化的当下,获取跨领域、非功利性的即时性对话机会成本极高。产品逻辑清晰,将门槛降至最低——任何人可设价出售时间,这使其理论上具备了海量SKU(咨询者)的可能性。

然而,其真正的挑战也在于此。首先,**平台价值与监管难度成正比**。当对话主题从“职业规划”延伸至“任何事情”,内容边界与合规风险将呈指数级增长。其次,**双边冷启动的经典困境**。早期“专家”供给质量决定平台调性,若缺乏高质量供给,将迅速沦为零散、低质的闲聊场,而高质量供给往往已被垂直平台(如Upwork、Clarity.fm)或私人网络垄断。评论中关于“哪个细分市场最有效”的提问,恰恰击中了其定位模糊的核心问题——试图服务“所有人”,往往难以精准服务“任何人”。

其宣称的“AI无法取代”是动人的情感牌,但忽略了一个事实:大量标准化、信息型的对话正被AI高效替代,人类对话的溢价恰恰存在于深度、信任与复杂问题解决中,而这些需要强大的筛选与信任机制。目前其模式更接近于将Fiverr的“微服务”概念极端化为“时间切片”,能否建立起可持续的供需生态,而非一时新鲜感的偶发性交易,仍需观察其运营能否在“开放市场”与“质量管控”间找到精妙的平衡。

查看原始信息
talk.
It’s a platform where you can share your time, help others, and get paid for it. It’s for engineers, students, creators, founders, doctors… basically everyone.
One of the few things AI will never fully replace is people. How many times have you been in a situation where you needed advice, feedback, or just wanted to talk to someone outside your network… and it felt impossible? Now imagine being able to book a 30‑minute 1:1 video call with anyone you want, about anything. On the other side, you can offer your time, help others simply by talking, and get paid for it (you set the price 😉). Talk wants to be a place to make conversations possible… the rest is up to you ;) PS: Already 200 users
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This would be a great marketplace to connect with amazing people.

All the best for the launch!

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@basharath Which niche do you think would perform the best?

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This is a cool concept. 
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@sudhir_p when interact on product hunt?

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#16
VibecodedHub
The discovery platform for AI-built products
14
一句话介绍:VibecodedHub是一个专为AI生成产品打造的发布与发现平台,解决了“氛围编码”浪潮中快速诞生的项目缺乏持久曝光渠道和专属社区的痛点。
Developer Tools Artificial Intelligence Vibe coding
AI产品发现平台 氛围编码 产品发布 项目展示 AI工具生态 开发者社区 初创项目 产品猎手垂直化 AI辅助开发 构建故事
用户评论摘要:用户肯定平台需求,祝贺发布。主要反馈包括:主页滚动存在卡顿(开发者已跟进测试);核心问题是质疑平台如何区分“AI构建”与“AI辅助”的验证机制。
AI 锐评

VibecodedHub试图捕捉一个新兴且模糊的趋势——“氛围编码”,其核心价值主张在于为AI工具快速催生的、往往是一次性曝光的项目建立一个沉淀与筛选层。这确实切中了当前AI产品从构建到分发的链条中的一个缺口:噪音之上的有效发现。

然而,其面临的根本性挑战与机遇同样尖锐。首先,品类定义的模糊性是一把双刃剑。评论中关于“如何验证AI构建”的提问直击要害。若标准宽松,则平台易沦为普通产品列表,失去独特性;若标准严苛,则可能极大限制内容供给和社区规模。平台需要建立一套可信的、可操作的“AI构建”认证或披露标准,这将是其构建壁垒的关键。

其次,其模式可视为Product Hunt在“AI原生构建”领域的垂直化尝试。垂直化能带来精准社区和更高粘性的可能,但同时也放弃了广度,其天花板取决于“AI构建”这一细分领域本身的规模和发展速度。目前,它更像是服务于一个特定技术圈层的“展示橱窗”,而非一个具备强大网络效应的市场。

最后,其自身作为用Claude Code构建的首个项目,是一次巧妙的元营销。但这同时暴露了其早期阶段的本质:内容生态冷启动的挑战巨大。平台的价值将完全取决于能否吸引到高质量、持续的项目提交,并形成积极的反馈循环。否则,它可能只会重复其试图解决的问题——项目发布后迅速沉寂。

总而言之,这是一个在正确时机切入细分赛道的敏锐尝试,但产品愿景的落地高度依赖于其运营能力,尤其是在品类定义、质量控制和社区激活上。它不是一个颠覆性的模式创新,而是一个试图在AI开发范式变革中提供基础设施服务的利基玩家。成败在于执行细节。

查看原始信息
VibecodedHub
The vibe coding movement ships real products every week. They get posted once and disappear, no discovery layer exists for this category. VibecodedHub fixes that. Submit your AI-built project, share your build story and tools, and get discovered by a community that gets how it was made. Built with Next.js, Prisma, Stripe, and Claude Code. The platform is the first project posted on its own feed.

A much-needed marketplace now. Congrats on the launch!

Btw, the landing page looked a bit laggy when scrolled, please check.

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@basharath Thank you i appreciate it! What part is laggy? i just tested in 3 different browser and its fine on my end :/

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Hi Product Hunt, I built VibecodedHub because I kept watching good projects get lost. Every week people ship real things with Claude, Cursor, and other AI tools. They post once on X, maybe get a few likes, and that's it. There is no discovery layer for this category of product — no place where vibe-coded projects live, get ranked, and find an audience. So I built one. VibecodedHub is a launch and discovery platform specifically for AI-built products. Think Product Hunt but focused on the vibe coding era, with build stories, tool tagging, and a community that understands how these products are made. The platform itself was built entirely with Claude Code across a series of focused sessions. It is the first project posted on its own feed. If you have built something with an AI tool, no matter how small, this is where it belongs. I am happy to answer any questions about the product or the build. And if you try it, I would love to hear what you think.
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Discovery is the real gap right now - vibe-coded products are shipping fast but hard to find outside PH and Twitter noise. A curated layer that filters by AI-built specifically makes sense. How are you verifying what counts as AI-built vs just AI-assisted?

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#17
GetNextRole
Apply smarter, not more. Quality job search platform.
12
一句话介绍:一款集成AI简历优化、智能职位匹配、个性化求职信生成等全流程功能的免费求职平台,旨在通过提升申请质量而非数量,帮助求职者高效斩获面试,解决海投耗时、回复率低的痛点。
Productivity SaaS Career
AI求职助手 简历优化 智能职位匹配 求职自动化 申请追踪 面试辅导 免费求职平台 北美求职 ATS优化 个性化申请
用户评论摘要:用户反馈积极,认可其简历优化建议具体、一站式整合节省时间、界面简洁。创始人自述源于被裁后求职困境,强调与竞品“重数量”的核心差异在于追求高“面试转化率”。有效评论集中于对实际效果(如30天内找到工作)的证实及对“自动申请”等即将上线功能的期待。
AI 锐评

GetNextRole的叙事和产品逻辑直击了现代求职市场的核心矛盾:求职者倾注心力的“个性化申请”与雇主端ATS系统冰冷的“关键词过滤”之间的巨大断层。它聪明地避开了已被卷成红海的“一键海投”赛道,转而打出“质量优于数量”和“面试转化率”这张牌,这不仅是差异化的营销话术,更是对求职服务本质的回归——结果导向。

其宣称的50%面试转化率是最大爆点,但也需冷静看待。该数据目前缺乏独立验证,且高度依赖于用户基础质量、目标职位范围及“申请”的定义口径。然而,其产品架构确实系统性地围绕“提升质量”构建:从ATS关键词优化解决简历入库问题,到基于多平台聚合的智能匹配减少无效投递,再到结合公司研究的AI求职信实现初步个性化。它将分散的工具链整合,确能提升求职者体验和效率。

真正的挑战在于可持续性与规模化。深度个性化与高转化率在早期用户和有限申请量下可能实现,但随着用户量激增,AI生成的“个性化”内容是否将流于新的模板化?其算法对“质量匹配”的界定能否适应千变万化的职位描述?此外,“免费”模式如何支撑长期研发与数据合规成本(如PIPEDA)亦是隐忧。

总体而言,GetNextRole展现了一个更健康的求职辅助思路:它不是鼓励内卷和焦虑的“申请永动机”,而是试图用技术赋能,让求职者的每一次出击都更具价值和尊严。其成败关键在于能否在扩张中坚守“质效”承诺,并将数据转化为更深度的洞察,而非沦为另一个流量入口。

查看原始信息
GetNextRole
GetNextRole uses AI to optimize your resume, generate cover letters, match you to jobs across 20+ boards, track applications, and prepare you for interviews. Everything job seekers need in one free platform. Auto-apply coming soon.

Resume score + real suggestions? This is huge. Most tools just give you generic feedback but this one hits specifics.

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@officiallearnsimplified Thanks! Specific, actionable feedback is exactly what job seekers need. Glad it helped!

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@officiallearnsimplified Thank you for your feedback

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Hey Product Hunt! 👋 I'm Shakir, founder of GetNextRole. THE BACKSTORY: I got laid off for 6 months ago. Started job hunting. Applied to 200+ companies. Each application took 30-45 minutes. Customize resume, write cover letter, fill out the same info on 10 different portals. After 5 months, I got an offer. But here's what I learned: 75% of my applications got auto-rejected by ATS software I didn't even know existed. Not because I was unqualified. Because my resume didn't have the "right" keywords. I kept thinking: There has to be a better way. THE REALIZATION: Then I looked at competitors. They all brag: "Apply to 500 jobs a month!" I did the math: 500 × 2% response rate = 10 responses. Still terrible. That's when it hit me: The problem isn't volume. It's quality. WHAT MAKES GETNEXTROLE DIFFERENT: Most tools compete on how many applications they can send. We compete on interview conversion rate. ✅ Personalization at Scale Every application is unique. AI researches the company before writing the cover letter. No templates. While competitors send the same resume to 500 companies, we send 500 unique applications to 30 companies. ✅ Complete Journey One platform for everything: → Resume optimizer (pass ATS filters) → Smart job matching (quality over quantity) → AI cover letter (30 sec, company-researched coming soon) → Professional follow-up (post-interview emails) → Application tracker (Kanban-style & Timeline-style) → Interview coach (practice with AI feedback) → Career coach (salary negotiation, offer evaluation) Most tools do ONE thing. You pay for 5 subscriptions. GetNextRole does it all. ✅ Canadian-Built Trust GetNextRole: → PIPEDA compliant (data protection) → Canadian & US job boards integrated → Quality filtering (no scam listings) → Built for CA + US markets ✅ Measurable Results Competitors hide their conversion rates (2-3%, embarrassing). We lead with ours: 50% average interview conversion. Success metric: Interview bookings, not application volume. THE COMPARISON: Competitor: 500 applications → 10 responses (2% rate) GetNextRole: 30 applications → 15 interviews (50% rate) Which would you rather use? CURRENT STATE: Everything above is LIVE and FREE right now. → Auto-apply with AI personalization coming soon (Chrome extension pending Google approval). → AI cover letter (company-researched coming soon) WHAT I NEED FROM YOU: → Try it: getnextrole.com → Give me honest feedback (even harsh stuff helps) → Upvote if you think this is useful I'll be here ALL DAY answering every question and comment. While competitors count applications, we count interviews. Apply smarter, not more 🎯 Thanks for checking it out! 🙏
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Real story:

My first beta tester (and also my toughest critic 😄) tried GetNextRole and the first thing she said was:


“This is actually good.”

A few weeks later… she landed a new role in Governance, Risk & Compliance — all within 30 days using GetNextRole.

Coming from her, that meant everything. She doesn’t hype things.

That’s when I knew we had built something real.

Would truly appreciate your support today 🙏

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Really excited to see GetNextRole launching! 🎉

As someone close to the project, I’ve seen how much thought has gone into making the job search less overwhelming and more effective.

The combination of AI-powered resume optimization, tailored cover letters, and smart job matching across multiple boards genuinely saves time and removes a lot of guesswork.

What stands out most is how everything is brought into one place—from tracking applications to preparing for interviews. It’s built for real job seekers who want results, not just tools.

If you're currently job hunting or even casually exploring opportunities, this is definitely worth checking out 👀

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@adewunmi Thank you so much, Adewunmi! 🙏🔥

You’ve seen the journey from the inside, so this means a lot.

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This is a great idea and Congratulations on your launch. This, there are many competitors out there, what different your application from them ?

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@dgame Thank you for your comment and a good comparison! Here's the key difference:

Competitor focuses on volume - how many applications can they send. Result: 2-3% response rate VS. GetNextRole, we focus on conversion, how many interviews can we get you. Result: 50% response rate.

We apply to fewer jobs, but each one is:
• Personalized (AI researches company)
• Optimized for that role
• Quality filtered (only where you fit)

Would love your feedback if you try both! Thanks

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I have used GetNextRole to apply to 12 companies. My first observation was that my resume had optimized versions ready in minutes. The job matching pulled roles from 20+ boards, which saved me from tab-hopping across LinkedIn, Indeed, and Employer sites. The application tracker also kept everything in one place so I stopped losing track of where I stood. So far, this has been making my life easier. Thank you GNR team.

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@dimeji_ph Thank you so much for sharing your experience 🙏 Hearing that GetNextRole helped you streamline applications and stay organized means a lot to us.

Our goal is exactly that - reduce the stress, save time, and make job searching easier.


We’re just getting started, and feedback like yours keeps us building.

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@dimeji_ph I had fun working in this project and looking forward to getting more features roll out

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I came across GetNextRole this week and decided to give it a try. What stood out to me right away was how simple everything felt. I didn’t have to jump around different platforms or dig through tabs just to find roles that fit what I’m looking for. The app brings everything together in a very clean, straightforward way.

I’m still exploring all the features, but so far it’s been super helpful and way less stressful than my usual job search routine. Really looking forward to seeing how the platform evolves — great job to the GNR team!

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@arimran Thank you so much for trying GetNextRole! 🙏

Glad to hear the simple and stress-free flow is helping — that’s exactly what we’re building for.

Appreciate your support and excited to keep improving! 🚀

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#18
Ideahunt
Validate ideas before you build
11
一句话介绍:Ideahunt为独立开发者和初创者提供了一个实时市场,让他们在投入大量时间开发前,通过收集真实的点赞、承诺兴趣和有上限的小额支持来验证产品概念的可行性,解决“闭门造车、市场不买账”的核心痛点。
Crowdfunding SaaS Business
创意验证 产品众筹 早期市场测试 独立开发者平台 最小化可行产品(MVP) 客户承诺 微支持 市场信号 初创工具 概念孵化
用户评论摘要:发布者介绍了产品核心逻辑并邀请用户参与。唯一有效评论来自用户@ashutosh_tiwari4,其指出产品存在多处明显Bug(如按钮无法点击、无法查看想法详情页),并警告不应让产品在此状态持续过久。评论无点赞,讨论热度低。
AI 锐评

Ideahunt瞄准了一个真实且痛苦的痛点——如何低成本、高效率地进行“创意验证”,但其当前的发布状态恰恰成为了其理念的反面教材。产品试图将模糊的“验证”转化为由点赞、承诺和微支持构成的实时市场信号,这个方向具有洞察力。它本质上在贩卖“确定性”,试图降低独立开发者最大的风险:时间机会成本。

然而,其Product Hunt首秀暴露了致命矛盾:一个旨在帮助他人避免推出漏洞产品的平台,自身却以充满明显Bug的状态上线。用户评论一针见血地指出了这种不成熟性。这不仅损害了初始信任,更引发了对平台能否有效筛选高质量创意的质疑——如果平台自身都无法践行“先验证,再构建”的原则,其说服力将大打折扣。

更深层看,Ideahunt的核心挑战在于构建“双向冷启动”生态:既要吸引足够多且有深度的早期采用者(提供高质量反馈和承诺),又要吸引足够多坦诚且优质的原始创意。目前11票的低热度反映了生态的冷清。其“有上限的微支持”功能颇具巧思,试图将情感支持货币化,并可能过滤无效投票,但这在生态繁荣前意义有限。

产品的真正价值不在于功能本身,而在于能否形成高信噪比的社区文化。如果最终沦为另一个“点子点赞厂”,而非能产生严肃承诺和犀利反馈的“压力测试场”,它将无法从众多的众筹和展示平台中脱颖而出。建议团队立即全力修复产品,并以最透明的方式展示这一“验证-迭代”过程,这或许能将其当前的尴尬转化为一次生动的理念实践。

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Ideahunt
Discover early-stage concepts, commit as a future customer, and back ideas with capped micro-support. Ideahunt turns vague “idea validation” into a real-time marketplace of upvotes, and committed interest. It is designed for solo founders and indie hackers to post raw problems, audiences, and pitches, and to watch live signal—upvotes, commitments, comments, and optional capped backing—aggregate across ideas before they invest weeks into a build.
Launching Ideahunt on Product Hunt today – thanks for checking us out. Ideahunt is a marketplace where solo founders and indie hackers post raw concepts - problem, audience, pitch and get upvotes, committed interest, and optional capped backing before they invest weeks into the wrong build. If you’re a builder, try posting one “messy but honest” idea; if you’re an early adopter, browse the ideas and leave one piece of specific feedback or a small commitment to any concept you’d actually want to see in the world.
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@ashutosh_tiwari4 Good job on launch, however, I see lots of bugs (cannot press certain buttons or access the product idea detailed view, and others). Please be careful with leaving the product in this state for too long!

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#19
PackGoat
Pack in minutes. Forget nothing.
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一句话介绍:一款通过可复用模板、智能数量调整和实时重量追踪,帮助“拖延症”打包者在旅行前快速、无遗漏地整理行李的移动应用。
iOS Productivity Travel
旅行打包 效率工具 清单应用 模板复用 智能数量 行李称重 防遗忘 个人整理 出行规划 iOS应用
用户评论摘要:有效评论仅开发者自述。其阐述了开发初衷(自身打包痛点)、核心功能理念(打包一次,永久复用)及早期数据(首周下载57次,转化率7.53%),旨在收集反馈,未提供其他用户问题或建议。
AI 锐评

PackGoat精准切入了一个微小但普遍存在的痛点——非频繁旅行者的打包焦虑。其真正的价值并非在于“清单”这一古老形式本身,而在于通过数字化手段,将一次性的、充满不确定性的打包任务,转化为结构化的、可重复使用的个人出行数据资产。

“模板复用”和“智能数量”是产品的双引擎。前者对抗的是“从零开始”的启动阻力与记忆疏漏,本质是用户行为的沉淀;后者则试图用简单规则(如“X件/天”)解决过度打包或准备不足的问题,将行程时长这一变量与物品数量动态关联,引入了初步的智能化。而“实时重量追踪”功能,则是将打包从“物品罗列”提升至“重量管理”的务实一步,直击机场托运的经济与体验痛点。

然而,产品面临深层挑战。其一,场景壁垒:用户旅行频率、目的地差异(商务/海岛/滑雪)极大,模板的普适性与个性化之间存在矛盾。其二,数据录入成本:构建初始模板仍需用户投入精力,这恰恰是目标用户(讨厌打包者)可能缺乏的动力。其三,竞争维度单一:作为工具,其功能容易被成熟笔记或清单应用通过文件夹复制等功能部分替代,重量追踪也严重依赖用户自备蓝牙秤等外设。

当前,其7.53%的下载转化率是亮点,说明概念能有效打动初期用户。但长远看,它必须超越“更聪明的清单”,向“个性化出行装备中枢”演进。例如,通过对接天气API推荐物品,整合航班行李额度信息,或形成用户私人的“物品-行程”数据库,才能构建更深的护城河。目前,它是一个构思精巧的“止痛药”,但能否成长为旅行前的“必备维他命”,取决于其数据沉淀与场景扩展的深度。

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PackGoat
PackGoat is a packing list app for people who hate packing. Create reusable templates so you never start your packing list from scratch. Build a "Toiletries" list once, reuse it every trip. Smart quantities adjust to your trip length. Set "2 per day" for socks, change your trip from a weekend to a week, and the quantities update automatically. Know exactly how heavy your bag is before you leave with real-time weight tracking. No more overweight baggage fees or surprises at the airport scale.
Hey Product Hunt! I'm Fredrik, a solo iOS developer from Norway. I built PackGoat because I always pack last-minute, forget things, and overpack. Every trip I'd start my packing list from scratch, even though I'm packing the same toiletries and chargers every time. The core idea is simple: pack once, reuse forever. Templates let you save your go-to lists and add them to any trip. Smart quantities adjust to how long you're going. And weight tracking shows your total luggage weight before you leave. 57 downloads in the first week. 7.53% conversion rate. Still early, but the feedback has been great so far. Would love to hear what you think. Happy to answer any questions about the app or building it solo.
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#20
Compeddit — Reddit Competitor Monitor
Earn a customer everytime your competitor gets mentioned
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一句话介绍:一款通过AI 24/7监控Reddit上竞争对手提及情况,并在用户表达不满、比较或寻求替代方案时发送即时Telegram警报的工具,帮助产品经理、营销人员和独立开发者主动拦截销售线索,从竞争对手处夺取客户。
Marketing SaaS Artificial Intelligence
竞品监控 销售情报 Reddit监听 市场预警 客户获取 营销自动化 SAAS 创业工具 商业智能 舆情监测
用户评论摘要:用户认可Reddit作为用户情绪和销售线索金矿的价值,认为该工具是“作弊码”。主要问题集中于功能细节:是否支持同时监控多个竞品,以及工具是否提供回应建议而不仅仅是通知。
AI 锐评

Compeddit精准地切入了一个锋利但狭窄的赛道:将Reddit这一庞大的、充满自发意图表达的论坛,转化为实时的竞品客户流失预警系统。其核心价值并非技术上的颠覆,而在于对“销售时机”的极端优化——将传统的广撒网式社交媒体监听,聚焦于“寻找替代品”、“对X不满”等高转化意图信号。产品逻辑直白且功利:在客户与现有供应商关系最脆弱的时刻,提供最快的“挖墙脚”服务。

然而,其天花板也显而易见。首先,市场容量受限,严重依赖Reddit单一平台,且目标用户(有明确竞品、客单价足以支撑此类工具费用的B2B或高端B2C团队)规模有限。其次,价值可持续性存疑。一旦多个竞品都使用类似工具,Reddit上的“蓝海”将迅速变为“红海”,演变为一场警报速度的军备竞赛,最终可能损害平台用户体验。最后,从评论的提问可以看出,用户需求已从“发现”向“行动”延伸,仅提供警报可能很快不够,如何集成自动化互动或销售话术建议,将是其下一步必须面对的挑战。

本质上,Compeddit是一个极致的“机会主义”工具。它在当前市场信息不对称的缝隙中提供了可观的短期战术优势,尤其适合敏捷的初创公司和独立黑客。但长期来看,它更像是一个功能模块,而非一个独立的生态产品。其真正出路或许在于被整合进更广泛的客户成功或销售情报平台,成为其中监听用户生命周期的“耳朵”。作为独立产品,它需要快速拓展数据源(如Twitter、专业论坛)并深化响应闭环,才能从“聪明的监控器”进化为“自动化的商机捕获系统”。

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Compeddit — Reddit Competitor Monitor
Compeddit Catch buying signals before your competitors even know they're losing customers. Get instant Telegram alerts when people complain about their service, compare them to others, or admit they're ready to switch. One user intercepted a 847-upvote thread looking for alternatives and closed 12 deals in 48 hours. get complete dashboard of all your competitors and stay 2 steps ahead.
I built this tool to help PMs, marketers and indie hackers keep a track upon their competitors and stay ahead. While your competitors sleep, Compeddit is hunting. This AI-powered intelligence machine monitors Reddit 24/7 and alerts you the SECOND someone says "Looking for a [competitor] alternative" or "I'm done with [competitor]." Catch buying signals before your competitors even know they're losing customers. Get instant Telegram alerts when people complain about their service, compare them to others, or admit they're ready to switch. One user intercepted a 847-upvote thread looking for alternatives and closed 12 deals in 48 hours. one time $59 or monthly 15.99$ Unlimited competitors. Unlimited opportunities to poach their customers.
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Congrats on launching! Reddit is my go-to for raw, unfiltered user sentiment so the fact that this monitors it 24/7 for competitor mentions is kind of a cheat code! Can you track multiple competitors at once or is it one at a time?

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Congrats on the launch. Reddit is genuinely one of the most underused sales channels. People are publicly announcing they're done with a product and ready to switch, and most companies never even see it. The 12 deals in 48 hours story makes a lot of sense when you think about the intent level of someone posting "looking for an alternative". When you get alerted to a thread, does the tool suggest how to respond or is it just the notification and you take it from there?

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