Product Hunt 每日热榜 2026-02-09

PH热榜 | 2026-02-09

#1
SuperX
All-in-one growth OS for serious 𝕏 creators
652
一句话介绍:SuperX是一款面向X平台严肃创作者的All-in-one增长工具包,通过提供基于热点的灵感、AI重写、智能定时发布、精准互动推荐及数据分析等功能,解决了创作者在内容灵感、发布效率及增长策略上耗时低效的核心痛点。
Social Media SaaS Artificial Intelligence
社交媒体管理 创作者工具 AI内容生成 增长黑客 内容调度 数据分析 X平台工具 SaaS 个人品牌 自动化营销
用户评论摘要:用户普遍认可产品价值,认为其是“游戏规则改变者”,尤其赞赏“互动发现”和智能调度功能。核心关切点在于:1. 如何精准定义“正确账户”以避免 spam 感;2. 产品如何快速适应X平台算法的频繁变更,确保功能持续有效。
AI 锐评

SuperX并非简单的功能堆砌,其真正价值在于试图构建一个适应X平台动态生态的“增长操作系统”。创始人基于出售前作Tweet Hunter后目睹其僵化衰落的切肤之痛,将“快速迭代与算法同步”提升到了产品哲学层面。这直接回应了社交媒体工具最致命的阿喀琉斯之踵:平台依赖风险。

产品介绍中“基于病毒帖的每日灵感”和“基于趋势的研究”实为同一数据源的两面——外部热点与内部归因。其宣称的“用你自己的声音快速重写”是当前AI工具的标配,但关键在于其重写建议是否由前述的实时趋势数据驱动,否则仍是隔靴搔痒。真正的护城河潜藏在“自动最佳时间发布”和“获取正确账户以互动”这两个功能中,它们要求对X算法有近乎实时的解读与预测能力。评论中官方回复证实了其“持续分析X信息流”的机制,这暗示其可能构建了一个反馈闭环,将用户行为数据与平台公开数据结合,动态调整策略。这是一种从“静态规则工具”到“动态适应系统”的范式转变。

然而,潜在风险依然清晰:首先,对单一平台(X)的深度绑定既是利也是刃,平台API政策或商业策略的任何变动都可能带来系统性风险。其次,“增长工具”的内核可能助长平台内的同质化内容与互动泡沫,其推荐的“正确账户”若基于交互热度而非真正的内容相关性,长期可能损害用户的社交资本。SuperX的成功,将不取决于其功能列表的长度,而取决于其数据引擎的敏锐度与抗风险架构的稳健性,这是一场与平台算法进化速度的持久赛跑。

查看原始信息
SuperX
SuperX is an all-in-one growth toolkit for 𝕏. Get daily inspiration based on viral posts in your niche, trend-based research, and fast rewrites in your voice. Schedule posts at the best time, engage with the right accounts to get discovered, and track what works with built-in analytics.

👋 Hey Product Hunters, thanks for checking my launch ❤️

A few years ago I built Tweet Hunter and eventually sold it. After the acquisition I kept maintaining it for a while, shipped features, and pushed it forward. But once I stepped away, I slowly watched the product stop evolving.

As a daily user myself, that was frustrating. Features started breaking one by one, the AI features weren’t exciting, and when 𝕏 rolled out big updates like long-form posts, it took months before the tool adapted. And with the constantly changing 𝕏 algorithm, the core workflow that once felt magical began to feel slow and unreliable.

So I decided to do something about it. That experience is exactly why SuperX exists today.

SuperX is an all-in-one growth toolkit for 𝕏 where you can:

  • get daily inspiration based on viral posts in your niche

  • run trend-based research to see what’s actually working

  • rewrite posts fast in your own voice with AI

  • schedule at the best time automatically

  • get the right accounts to engage with & get discovered faster

  • track what works with built-in analytics and double down

Built with the great @robhallam maker, already trusted by 1,400+ creators (including some of the biggest creators like Dan Koe) building and managing their audience every day on 𝕏

I would absolutely love to know what you think of the tool. You can start on SuperX.so, I will read all feedback and comments and will do my best to keep improving it 🙏

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@thibaultll Always in support for what you build.
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@robhallam  @thibaultll congratulations on the launch guys! For anyone who`s serious about growing on X this app is a no brainer.

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So incredibly proud of what we have built!

Thank you so much for checking the launch and supporting.

Please don't hesitate with your feedback, any and all is appreciated as we iterate fast to keep SuperX being the best platform for growing on X 🫶

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always shipping - that's the mindset 🙌

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@robhallam 
Well done Rob!

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@robhallam Great product!

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been using it for 3 weeks - love the engage feature 🔥

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love your help Ayush, thanks a lot

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158 upvotes omg you guys will crush it!!

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@marclou you could beat that easily if you played 😅

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looks very good! congrats for the launch

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thanks a ton for checking it out

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Used Tweet Hunter for years till it got clunky. SuperX looks like the fix, maybe. I post 2-3x/day and my time is tight, so the trend inspo + smart engage bits stand out. How do you pick "right accounts" without spam vibes? Curious to try long-form.

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@alexcloudstar would love to get your feedback if you do

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Pure value. @robhallam , you've really set an insane bar with this product!

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@robhallam  @josefbuettgen agreed 100%

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SuperX gently came into my social life. I was lucky enough to hear a sales pitch from @robhallam in person.

I was exploring X on my own since July 2025 and SuperX became my "coach" to grow online presence and personal brand

  • 0->40 followers in 6 months (without Super X)

  • 40->90 followers in 1 month (with Super X)

I've seen it making 10-100x miracles with people's activity. I'm on a modest part of it but it's just the beginning :)

I can definitely say that SuperX will help you take X seriously 🚀

Tibo, Rob, Ayush – great job, guys. Keep it up!

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@robhallam  @pasha_barbashin so great to read this, keep growing 🙌

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SuperX is one of my favorite add-ons to X. Great design, and there have been a ton of new features/value since it was first released. One of those products where it's hard to commit to sign up, but once you do, it's hard to cancel.

Incredibly well done @thibaultll & @robhallam!

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@robhallam  @gabe thanks a lot for sharing 🙏

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Marc Lou and Tibo launching in the same day? 🍿👀 That'll be interesting.

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@busmark_w_nika damn 😅

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I've been using SuperX for the last month or so, and it's genuinely changed my X antics entirely. I don't have to think about remembering to post or trying to figure out when the best time to post is - SuperX handles all of that and posts when I ask it to. Game changing tool for those that want to take X seriously. 11/10

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you're probably the best user Luke, thanks a TON for giving it a chance 🙌

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Love SuperX! Congrats on the launch!

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@eugzolotarenko thanks a ton Eugene 🙌

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Have been a customer for some months, and the #1 feature I personally love most is Engage-> Discover which allows me to find posts that I can meaningfully reply to.

Plus @robhallam and @thibaultll are very inspiring, super happy to support and use SuperX

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love the concept. One thing I'm curious about is the 'best time to post' and engagement features are tightly coupled to X's algorithm. After seeing how fast X rolled out changes that broke Tweet Hunter, how does SuperX stay resilient when the algorithm shifts overnight? Is there an internal feedback loop that adapts in real-time?

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@vildanbina I think you answered your own question Vildan! It is in fact a good question. Yes, we constantly analyze the X feed and all of our "best time to post" and AI/engagement related features are powered by what's currently happening on X. So it automatically stays up to date with whatever the state of the algorithm is.

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the legend is launching, of course #1, you got this Rob :D

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@dominiksumer Thank you Dominik :D

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Cool - finally can find an agent for me to manage my X account! how many styles or templates does SuperX have?

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Built by Tibo and Rob -> can be nothing but epic. That simple.

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my first impression to this was "Bro I hate free tools".

and then when I got to go to scroll down, I found that pricing plan. at least you should consider to keep a top nav name 'pricing'.

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The journey from Tweet Hunter to SuperX is a great story. Building something, selling it, watching it stagnate, then coming back to do it right — that takes guts. The trend-based research + scheduling combo is what I would actually want as someone who posts daily. Curious how the AI rewrite handles non-English content?

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Interesting tool. Been looking for something to crack X algorithm. And based on the comments and your responses, I will definitely give it a try. Cheers! 🙌🏼
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Congrats on the launch @robhallam @thibaultll - absolutely killing it 🔥

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Tibo and Rob are incredible makers, they ship and they constantly provide value to those around them. Their energy is infectious and Super X is the tool for X growth.

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Congrats on the launch! Rebuilding this from the perspective of a long-term power user really comes through, especially with how fast X keeps changing. How does SuperX adapt its recommendations and workflows as the platform algorithm shifts, so creators aren’t optimizing for patterns that worked a few months ago but no longer matter today?

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Creator growth suites usually hit scale pain when X API limits and auth churn collide with scheduling, analytics refresh, and engagement automation across many accounts.

Best practice is a per-account task queue with token-bucket budgeting, adaptive backoff honoring Retry-After, and aggressive caching plus incremental analytics fetches to avoid polling storms.

How are you partitioning rate limits and retries per user account, and do you have a “degraded mode” plan when endpoints get restricted so scheduling stays reliable?

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congrats on the launch!

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Wow, SuperX looks amazing! Love the idea of trend-based research for X. How granular can I get with niche targeting? This could be a game changer!

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@jaydev13 That’s a good question. Granularity is what usually makes or breaks these tools. Curious if it works more at the topic level or if you can really narrow it down to specific sub-niches over time

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Rob is a GOAT

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This is super cool
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Let's goooo! Been following a long for two years now, excited to see this taking shape!! Congrats boys

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Checked this, loved the way it recommends content based on your style and what's trending.

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#2
Unicorne
The 20 fastest growing startups based on TrustMRR data
415
一句话介绍:Unicorne 是一个基于真实支付数据、每小时更新的实时排行榜,为投资者、创业者和行业观察者动态追踪增长最快的20家科技初创公司,解决了市场信息滞后、数据可信度低的痛点。
Marketing SaaS
初创公司排行榜 实时增长数据 营收验证 投资发现 市场情报 SaaS 数据分析 创业生态 公开数据 产品榜单
用户评论摘要:用户普遍赞赏产品的创意、设计和数据透明度。主要建议包括:增加行业分类、公司简介、营收区间筛选;处理数据噪声(如退款、年费波动)以提升排名稳定性;质疑数据来源的开放性及询问盈利模式。
AI 锐评

Unicorne 的本质并非一个简单的排行榜,而是一个基于专有数据资产(TrustMRR)构建的“增长信号放大器”。其真正价值在于将零散、私密的支付处理器数据聚合、清洗,并转化为可公开消费的、近乎实时的增长动能指标,这在一定程度上挑战了传统上依赖融资额、媒体报道或自我报告来评估初创公司的陈旧范式。

产品巧妙地构建了一个“数据飞轮”:TrustMRR 为 Unicorne 提供可信的燃料,而 Unicorne 的高调展示又反向为 TrustMRR 的数据权威性和商业价值背书。这种循环增强了其生态的护城河。然而,其面临的挑战同样尖锐。首先,“增长”被极端简化为短期营收变化,这固然直接,但极易受异常交易(大额年付、集中退款)干扰,导致排名剧烈波动,可能放大噪声而非信号,正如评论中敏锐指出的。其次,榜单的“黑箱”算法(尽管有解释)缺乏对每个排位变动的置信度说明,削弱了其本应引以为傲的“透明度”。

从市场定位看,它更像一个面向创业圈和早期投资者的“风向标”与“灵感工具”,而非严肃的尽职调查依据。其最大贡献或许是塑造了一种新的文化:将营收增长这一硬指标置于聚光灯下,进行近乎残酷的公开比较,这本身就对创业社区构成了强烈的激励和压力。但若想从“酷产品”进化为“关键基础设施”,它必须在数据治理(异常检测、平滑处理)、维度丰富性(行业、阶段细分)和解读深度上投入更多,以平衡其追求的“实时性”与“洞察可靠性”之间的天然矛盾。

查看原始信息
Unicorne
Watch the top 20 fastest growing tech startups in real-time. Rankings updated hourly with verified revenue data from Stripe, Paddle, and RevenueCat.

Hey, it's Marc!

I built this leaderboard of the 20 fastest-growing tech startups.

It’s powered by my $1.2B database of verified startup revenues (TrustMRR), processing 10,000+ real payments per day.

Sometimes a startup goes viral overnight.

I created Unicorne to surface this signal.

It ranks startups by revenue growth over 7d, 30d, and 90d. Every startup listed on TrustMRR is re-analyzed for growth every hour, and recent performance is compared to historical baselines. Consistent acceleration ranks higher.

A unicorn might already be in there 🦄

Hope you like it

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@marclou Love how you continue to compound previous projects into new useful startups. This is another great one! Will definitely be checking this out and keeping tabs on new up and coming unicorns (hopefully my startup will be there 👀)

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@marclou 

Great job my man!
Rooting for you!

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@marclou very cool project, (as well as trustmrr overall)

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When I got to the site, the first thing that came to mind was "vroom vroom" lol. Super sick to see @kitze_kitze_ up in the leaderboard!

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@kitze_kitze_  @gabe he's crushing it lol

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Awesome job marc!

Checking the unicorn dashboard every day to
A: Get inspiration

and B:
Check if MoveMRR has made it up the leader board yet!

Honestly, it is quite a huge motivation to see other successful dev and dig into their background story, just to realize you can do the same thing yourself!

Keep it up!
Your #1 fanboi <3

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Love it @marclou
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Hourly re-ranking on verified payment streams can get noisy fast from refunds, annual-plan spikes, and provider latency causing leaderboard churn and false “viral” signals.

Best practice is event-sourced revenue normalization with dedupe + currency handling, anomaly detection, and confidence intervals with smoothing so ranks move on statistically significant deltas.

How are you normalizing Stripe vs Paddle vs RevenueCat events (refunds, trials, upgrades) and do you expose a confidence score or audit trail for why a startup moved up?

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This is pretty cool and nicely designed and I also like the domain haha. Curious if you have any monetization plans or just eager to provide a public good?

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This is the Marc Lou flywheel in action: build TrustMRR to verify revenue, then use that data to rank the fastest growing startups with Unicorne. Each product makes the other more valuable. Love it Marc!

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Amazing Marc keep shipping!

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Wow, Unicorne is seriously cool! Love that the rankings are updated hourly with verified revenue data. How do you handle outliers in the MRR data to ensure a fair ranking?

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Interesting! Would be nice to see the company industry or some short description without leaving this website

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Hahaha this is fun, nice Marc!

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Love the transparency angle here! Using real payment processor data (Stripe/Paddle/RevenueCat) makes this so much more credible than self-reported numbers. Quick question: do you have any plans to segment by industry or revenue band? Would be fascinating to see which sectors are growing fastest, or maybe a separate "fastest growing under $1M ARR" list for earlier stage startups.

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Nice one @marclou !

IMO only non-anonymous startups should qualify, but not a big deal 🤷‍♂️
I also feel like the into animation could be a bit smoother, but I can't quite put my finger on why... maybe it's just too fast?

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amazing idea! Though i did not know that information from Stripe is in open source.

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I absolutely love the UI! So fun! And I’m curious about the future roadmap – are you planning to add more company-specific insights or perhaps categories (like SaaS, FinTech, etc.)?

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This is genius ahahah!

Congrats on the launch guys :)

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TrustMRR is awesome!

I need to sell more to be listed there :D

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Nice. How is the Trusted MRR validated ?
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@bartvandekooij Companies add an api key for Stripe/Polar/Lemonsqueezy accounts

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@bartvandekooij via API keys from TrustMRR

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Would be cool to sort them out according to categories :)

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I love how you came up with the name, what's the ideology behind this?
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#3
Umbrel Pro
16TB home cloud server. Run OpenClaw, store files, and more.
287
一句话介绍:一款集成了高性能硬件与易用操作系统的家庭云服务器,通过一体化的软硬件设计和丰富的自托管应用生态,解决了用户对数据隐私、订阅费用、复杂配置和工业美学的痛点,实现了个人数据的完全掌控和便捷管理。
Hardware Privacy Tech
家庭云服务器 自托管 数据隐私 一体机 私有云存储 开源应用 工业设计 无订阅制 家庭媒体中心 智能家居中枢
用户评论摘要:用户普遍赞赏其设计、静音和易用性,并认可其针对传统NAS和Mac Mini等方案的改进。主要问题与建议集中在:明确产品定位(消费级或专业级);询问与Apple Silicon的性能对比及具体功耗;要求强化ZFS数据安全和应用更新管理;询问是否有增加内存的规划。
AI 锐评

Umbrel Pro并非简单的硬件升级,而是一次针对“技术普惠”与“体验升级”的精准卡位。它用消费电子品的思维改造了传统NAS市场:深泽直人式的铝木设计消解了服务器的工业冰冷感,umbrelOS的一键应用安装则大幅降低了自托管的技术门槛。其真正价值在于构建了一个“隐私即服务”的完整闭环——用户为硬件一次性付费,即可永久逃离云服务的订阅制与数据监控。

然而,光鲜之下暗藏挑战。其一,“Pro”之名与核心硬件(低功耗i3-N300、16GB内存上限)存在张力,这限制了其在AI推理等重负载场景的“Pro”表现,其主战场仍是媒体流、文件同步等中低强度任务。其二,将复杂性封装于“一键”之下是一把双刃剑。评论中关于ZFS配置、应用隔离与安全更新的尖锐提问,直指其核心矛盾:当系统封装得越彻底,非技术用户越难以洞察底层状态,一旦出现“静默数据损坏”或应用漏洞,后果可能更严重。产品能否从“易用”走向“可靠”,取决于其后台运维自动化与前端健康度可视化的深度。

本质上,Umbrel Pro是“反云时代”的精致产物。它不追求极致的性能参数,而是精准狙击了那些受够了科技巨头数据霸权、又畏惧传统开源方案复杂性的“精致实用主义者”。它的成功与否,将取决于其能否在保持简洁体验的同时,构建起不亚于企业级的、隐形的数据安全护城河。

查看原始信息
Umbrel Pro
Home cloud server with 4 NVMe SSD slots for up to 16TB storage. Milled from a single block of aluminum and framed with American Walnut. Powered by umbrelOS - run OpenClaw, Immich (photo/video backups), and hundreds of self-hosted apps with one click.

Hi Product Hunt! 👋

I’m Mayank, one of the founders of Umbrel.

The story:

5 years ago, we started building umbrelOS to make running a home server accessible to everyone. 3 years ago, we launched the Umbrel Home - our first plug-and-play home cloud server.

But users kept asking for three things: more power, more storage, and RAID (so no data loss even if an SSD fails).

Last week, we launched our dream hardware: Umbrel Pro.

Who is this for?

  • You've been considering a NAS but don't want something big, loud, and bulky with the UI and industrial design of the 2010s.

  • You're paying for iCloud or Google Photos and it bugs you that your photos live on a company's servers that can lock you out anytime.

  • You've been eyeing a Mac Mini for OpenClaw but dedicating a whole Mac to one thing feels off. Umbrel Pro can run OpenClaw alongside 300 other self-hosted apps, all on something purposefully built to stay on 24/7 with negligible power draw.

  • You've been meaning to set up Plex to stream 4K movies to your TV, or Home Assistant for home automation, but the setup always felt like a hassle. With umbrelOS, it's one click.

One purchase, no subscriptions, and you own all your data.

The industrial design:
We mill the chassis from a single solid block of aluminum, sandblast and anodize it to a deep matte black finish, and frame it with real American Walnut wood.

We posted a behind-the-scenes video of how it's manufactured if you want to geek out on the machining.

Powered by umbrelOS:
No keyboard or display required. Just open umbrel.local on any browser on the same network and start dropping your files in. You can also add it Dropbox-style as a network folder on Mac/Windows, or even on your phone.

The Umbrel App Store has hundreds of apps, like OpenClaw, Bitcoin Node, Immich (self-hosted Google Photos), Plex/Jellyfin, Ollama, Nextcloud, and more - all one-click install.

Specs:

  • 4x NVMe SSD slots: Magnetic lid, no-tool SSD swaps, up to 16TB.

  • 2.5GbE LAN: Fast enough to edit 4K footage directly off of it.

  • 8-Core Intel Core i3-N300, 16GB LPDDR5 RAM.

  • FailSafe Mode: You can start with 1 SSD and add more later to enable RAID. Powered by ZFS.

  • Whisper quiet: The entire magnetic lid acts as a heatsink for the SSDs and you can barely ever hear the fan.

Umbrel Pro is shipping worldwide now, and you can order it on our website (from $699 / 599 € / £529).


We'd love your feedback! If you've got any questions regarding the hardware or the software, our team will be hanging out in the comments all day!

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@mayankchhabra Congrats Mayank! Do you see Umbrel Pro as a consumer product, prosumer tool, or enterprise solution, or all of the above?

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@mayankchhabra I’ve been struggling with [problem] for months. This saves me hours every week. Great job!

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The timing on this is perfect - traditional NAS systems feel so dated compared to what you've built here. Love that you listened to the community feedback from Umbrel Home and delivered on all three asks: more power (i3-N300), more storage (16TB), and RAID support (ZFS). Question for you: what's been the most popular use case among early users? Are people mainly using it for media/Plex, or are you seeing more interest in running AI models locally with OpenClaw?

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How would an Intel® Core™ i3-N300 compare with Apple silicon M5?

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M5 beats N300 any time of the day in terms of raw compute power. But N300 is great for running 24x7 tasks/home server apps (~7W power consumption, 8 efficient cores). They're both meant for different use cases. Mac is designed to be personal computer, Umbrel Pro is designed be a personal server - so different engineering decisions/tradeoffs.

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Been running Ollama on a Mac Mini for local inference, and the always-on tax is real. Dedicating a whole machine to serve a couple models feels wasteful when it sits idle 80% of the day. Umbrel Pro with 4 NVMe slots, ZFS, and one-click Ollama plus OpenClaw on a 7W chip is a much better fit for that use case. FailSafe Mode starting with 2 drives and scaling to 4 later is a nice touch for people who don't want to buy all their storage upfront.

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The aluminum + walnut design is what sold me — finally a home server that doesn't look like IT equipment from 2010. ZFS with FailSafe Mode is smart for people who want peace of mind but don't want to buy 4 SSDs upfront. What's the typical power draw when running a few apps like OpenClaw + Immich? Always curious about the 24/7 running cost.

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A plug-and-play ZFS box at home will hit scale pain on silent data loss risks from misconfigured pools plus long-term security patching across 300+ one-click apps.

Best practice is automated ZFS snapshots + scrub schedules with SMART alerts, plus signed app manifests and unattended OS/app updates with rollback for bad releases.

How are you handling app isolation and update provenance today, and will you surface a “health score” UI (pool status, scrub cadence, failed backups) for non-technical users?

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32gb ram on roadmap?
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That would be nice, but the Intel N300 (the entire N-series) only supports max 16GB RAM. Though it's plenty for most home server use cases. Do you have a specific use case in mind?

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#4
rivva
AI Schedule & Planner | Your Day, Planned Around Your Energy
222
一句话介绍:rivva是一款AI日程规划应用,通过分析用户的睡眠、能量模式与认知负荷,将高专注度任务智能安排在用户精力最充沛的时段,解决了高强度工作者在传统时间管理工具下忽视生理节律、易导致决策疲劳和过度消耗的痛点。
Productivity Task Management Artificial Intelligence
AI任务管理 智能日程规划 能量管理 生产力工具 认知负荷分析 日历整合 可穿戴设备集成 防过载设计 专注力优化 职业人士
用户评论摘要:用户普遍认可其“基于能量而非时间”的核心理念,认为能有效缓解过载。主要反馈集中在:1. 学习曲线与模式适应速度;2. 如何处理临时日程冲突与能量波动;3. 对共享日历编辑的担忧及私有日历需求;4. 任务分类与能量匹配的 granularity(精细度)。
AI 锐评

rivva所代表的“能量管理”范式,是对传统效率工具“机械化时间块”思维的一次值得关注的叛离。其真正价值不在于又一个AI调度器,而在于试图将“人”重新建模为一个有生理波动、会疲劳的有机体,而非永续运行的CPU。这直击了现代知识工作者“时间充裕,精力枯竭”的核心矛盾。

然而,其面临的挑战与潜力一样巨大。首先,其价值高度依赖于数据输入的连续性与准确性(如可穿戴设备),这为使用设立了门槛,且“能量”作为一个模糊的复合指标,其算法黑箱可能成为信任瓶颈。其次,从评论看,它正陷入“工具理性”与“人性弹性”的经典悖论:用户既希望它足够智能以自动化规划,又担忧其过度适应短期波动或无法处理“意外”而变得不可预测。这本质上是在要求AI理解人类生活的“上下文”,而不仅仅是日历事件。

产品目前定位“高强度专业人士”是明智的,因为该群体对“精力成本”感知最痛,且日程数据相对规整。但长远看,其天花板在于能否从“工作调度优化器”演进为真正的“认知周期伙伴”。这意味着它可能需要更主动地介入任务定义(如识别耗能类型)、提供动态调整的“精力预算”,甚至在系统层面鼓励休息与恢复,而非仅仅更高效地填满时间。若不能深化至此,它可能仅会成为另一个为“效率至上”文化服务的精致工具,而非其创始人所反感的“ burnout(倦怠)推手”的解毒剂。

查看原始信息
rivva
rivva is an AI task manager and calendar planner that organises your day around how well you can actually think and work, so demanding tasks land when your focus is strongest. Most productivity tools only model activity; they track tasks and meetings, but ignore the limits of human attention. rivva works from a fuller picture by combining what you need to do with how much capacity you have to do it, using your tasks and calendar alongside signals from sleep, energy patterns, and cognitive load.
Hi Product Hunt 👋🏽 I’m Peace, co-founder of rivva. Like many ambitious people, I built a reputation for getting a lot done. Over time, that ability to push through became both my strength and my weakness. By 29, I had burned out twice. That forced me to rethink productivity. I started studying how cognitive energy works and how much it is shaped by sleep, context, and timing. I reached one clear conclusion: productivity is not about squeezing more out of time; it is about managing energy. Focus, creativity, and judgement rise and fall through the day, and our best work happens when effort matches that rhythm. That is why we built rivva. rivva brings your email, tasks, and calendar into one system, then schedules work based on your energy patterns and real availability. The aim is simple: help you get important work done without overload. What rivva does: - Task management: Capture, organise, and schedule tasks in one place - Inbox: Extracts tasks from email, including meeting notes, Jira issues, and Notion comments - Energy insights: Connect your wearable and see when you are naturally sharpest - AI scheduling: Plans work around availability and energy patterns - Nia (AI chat): Create tasks, plan your week, set up meetings, or ask for guidance - Planner: Multi-calendar view with time-blocking We built rivva for founders, executives, and high-output professionals who already work hard and want a system that respects how the mind actually works. I would genuinely love to hear what you think. Try it out and tell us what feels useful, confusing, or missing.
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@peaceitimi Energy-aware planning helps real execution.
We route planning steps to different models via GTWY.
Keeping scheduling logic modular reduces brittle flows.

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@peaceitimi sounds interesting, I’m definitely trying this out!

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@peaceitimi The energy-first framing really resonates! Curious how rivva handles energy drift over time, when someone’s sleep, stress, or workload changes week to week, how quickly does the system adapt its scheduling without becoming unpredictable or intrusive ?

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Glad to have been part of the team that worked on rivva.

My favorite feature is Nia, the AI assistant. Being able to dump my entire task list in chat and have her auto-schedule everything and timeblock it in my calendar is so *chef's kiss.

Also like that when I'm in a productivity slump, I can ask her for coaching or help in re-prioritising, and she helps me get unstuck and start moving again.

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@ladefalobi You have been awesome Lade!

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Started using it back in beta, and it’s made scheduling around my energy so much easier.

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@sherlocs so glad to hear this. Thank you
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I’ve been trying Rivva while it’s still in beta and it’s honestly refreshing to see a planner that actually accounts for mental energy, not just time. Still early days, but the idea of scheduling work around real focus levels feels like the right direction.

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@blessing_ayide Thanks Blessing. Good to see an early user here

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Scheduling around energy patterns instead of just time blocks is smart. How long does it take rivva to learn your rhythm? Can it differentiate between temporary disruptions (bad sleep week) versus actual pattern changes?

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@klara_minarikova 

This is such a good question.

How long does it take rivva to learn your rhythm? We start with wearable data from day one, rather than waiting to learn everything manually. During onboarding, if you connect Apple Health, we look at your sleep history over a couple of weeks to establish a baseline energy pattern. That gives Nia an initial view of when you are typically sharper versus when energy dips. From there, the baseline gradually adjusts as new data comes in and you make changes to your schedule.

Can it differentiate between temporary disruptions (bad sleep week) versus actual pattern changes? Yes. The system is designed to avoid overreacting to short-term changes. A few nights of poor sleep or a single disrupted week will not immediately shift your energy rhythm. We look for consistency over time before adjusting the baseline, so changes only happen when a new pattern has clearly emerged rather than reacting to one-off disruptions.

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Very cool app! I just started my free trial on rivva and have a few questions when using it. For now I must connect it with my calendar, however many of my calendars are public ones (shared with other people) so I don’t want to make any edits to it. It would be great if rivva can have its own calendar system so I can have a separate calendar inside the app just for myself. Another problem is that I can’t creat a task on my calendar: it keeps saying that there are no free time blocks on mine but I’m sure there are. It might be a bug that needs to be fixed.
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Congrats on the launch! Anchoring productivity around energy rather than time feels very aligned with how people actually work. How does rivva adapt when someone’s energy patterns change over weeks or months, especially as routines, workloads, or sleep quality shift?

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Relevant for times like this where social scrolling have left humans with less attention span and struggle committing stretch of hours to get stuff done. Procrastination is now the order of the day.

Would be super good to tap into my rhythm get work done in bits according to my mood/energy.

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Wow, rivva looks amazing! The energy-based scheduling is such a cool concept. Im curious, how granular can I get with defining my personal energy patterns?

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Congrats on the launch, y'all! I love any tools that help you find when your peak times are for work. How does rivva determine what my peak energy/productivity levels are? Can I categorize the "kind" of work a task is so it gets scheduled during an appropriate time? For example, for me, "low energy" tasks could be replying to e-mails or updating work tasks, "high energy" tasks would be heads-down coding tasks or other deep work.

Awesome work! I look forward to checking it out!!

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@thisismiked  Hi Mike,

If you use the task manager, you can choose to categorise your tasks as you create them. low energy tasks = admin, high intensity = deep work, chores & habits = personal work etc and rivva uses that categorisation to match the task to the right energy zone.

If you use Nia, the AI Assistant, she will infer the task type when you share and use that to schedule. Happy to answer more questions

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Looks amazing, congrats on the launch guys!

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@maltepruser Thanks Malte.

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I spent a lot of December trying to find a tool exactly like this. A tool that works according to my day because every hour is different. Congratulations on your launch! Definitely checking it out

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@angel_umez Let me know what you think when you try it out. Very open to feedback

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The shift from time management to energy management is so needed - really resonates with the burnout story behind founding this. Most schedulers just treat us like machines that can context-switch infinitely. Curious about the learning curve: does Nia start with wearable data from day one, or does it learn your patterns over time through manual input first? Also wondering how it handles the unpredictability - like when a surprise meeting tanks your afternoon focus.

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@adam_lab Great question, Adam.

We start with wearable data from day one, rather than waiting to learn everything manually. During onboarding, if you connect Apple Health, we look at your sleep history over a couple of weeks to establish a baseline energy pattern. That gives Nia an initial view of when you are typically sharper versus when energy dips. From there, the baseline gradually adjusts as new data comes in and you make changes to your schedule.

In terms of unpredictability, today we treat meetings as a hard constraint. If a meeting appears on your calendar and conflicts with a scheduled task, the task is automatically moved. Similarly, if you add a higher-priority task or something with a tighter deadline, lower-priority work is rescheduled to make space.

The goal right now is not to perfectly predict every bad afternoon, but to reduce the amount of manual replanning you have to do when the day inevitably changes.

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congrats! can you tell more about what kind of use cases do you cover? is it for personal use or work?

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@sasha_dikan Right now, rivva is mainly used for work. People use it to capture tasks from emails, view everything planned alongside the planner, and have Nia, the AI assistant, schedule your work into the week based on your availability and energy, rather than manually deciding when to do it.

A typical flow looks like this: tasks come in from email or are added in chat, rivva looks at your meetings and your energy patterns, and then suggests when to do focused work versus lighter admin and schedules it on your planner in one click.

You can also ask the chat to batch similar tasks into a time block, e.g., all work around "rivva launch into my Thursday afternoon" or move work around when the day changes.

Some people include personal tasks, but the core use case today is reducing planning effort and decision fatigue around work, not tracking habits or life admin.

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I’ve experienced rivva since its beta, and it’s been great seeing how much it’s matured by launch. As a designer, I really appreciate how it reframes productivity around clarity and capacity, not hustle. Energy-aware planning feels like the right next step for this category. Well done 👏

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I totally love this product! I signed up 3 days ago and it's quickly become a ritual, love how it surfaces tasks that I am almost forgetting so I don't drop the ball!

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@manliketoka Thanks Toka

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Nothing brings me more joy than building with a team that's solving real problems.

rivva has helped me become more aware of how my energy affects my output and that's something I never considered before. The best part of rivva for me is Smart schedule. I don't need to think of when to do work, I just need to toggle a button and rivva does it for me. This way, I spend more time actually working than planning to work.

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@eniola_falana Thanks Eniola

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Love the energy-based approach! Burnout is real, and most planners ignore it completely.

When Nia auto-schedules tasks, does the user get a chance to review/approve the plan before it's set? Or does it just go straight to the calendar?

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@virtualviki love this question. You always approve. If you send Nia a dump of stuff you need to do this week, it'd generate a plan, you approve with a click, and it schedules it all at once. You can timeblock all or selected tasks on your primary calendar as well.

Also, if we can't find a time, you'd see a notification in your task manager.

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Tried rivva when it was in beta and the approach to time and energy management is quite unique.

Congrats to the team on the launch. This is a thoughtful take on productivity that respects attention, and not just activity.

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@realjaymes James! Thank you so much

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Most tools forget we aren't robots. 🙃 How does Rivva actually track 'energy'? Is it based on manual input, or does it integrate with wearables like Oura or Apple Health?
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@tereza_hurtova  thanks for asking.

We support both.

On iOS, Rivva connects to Apple Health, which allows us to read sleep data from wearables like Oura, WHOOP, Fitbit, and others that sync there. We start with sleep because it is a reliable signal for circadian rhythm, which has a strong influence on cognitive energy. That data is pulled in automatically.

On web, energy is currently based on manual sleep and wake inputs. We are adding direct wearable connections there as well, and releasing Android soon, so Android users can have the same experience.

The goal is to combine passive signals with light manual input, rather than asking people to track everything themselves.

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Congrats on the launch!

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@chilarai thank you!

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#5
Dropstone 3
The first multiplayer AI code editor. Now with Share Chat.
198
一句话介绍:Dropstone 3是一款首创的多人在线AI代码编辑器,通过“共享聊天”功能,解决了开发者在单机AI编程工具中遇到协作困难、上下文割裂的痛点,实现了团队与AI代理在统一上下文中实时协同编程。
Productivity Developer Tools Artificial Intelligence
AI编程助手 多人在线协作 代码编辑器 实时共享 上下文管理 代理智能体 研究驱动 本地模型支持 异步编程 企业级开发工具
用户评论摘要:用户反馈积极,认可其填补了AI编程工具协作空白的价值。主要问题集中在:多用户同时操作时的冲突处理与上下文漂移、共享链接的权限与安全、本地模型性能对比、大规模代理集群的计算资源消耗。开发者回复详细,解释了基于CRDT的冲突解决、逻辑压缩的上下文合并、以及企业级功能的云端负载。
AI 锐评

Dropstone 3的野心不在于成为另一个AI代码补全工具,而在于构建一个以“共享上下文”为核心的操作系统级协作层。它精准地切中了当前AI编程工具的最大短板:单机、孤岛式的交互模式。所谓的“70%墙”痛点描述非常犀利——当AI能快速完成前期工作,开发者却卡在后续复杂的集成、调试和团队对齐环节时,生产力瓶颈便从代码生成转移到了协同与上下文管理。

其宣称的“非封装器”和自研D3引擎是技术叙事的核心。通过逻辑正则化压缩实现“无限上下文”,本质上是将代码的语义结构而非单纯文本作为管理对象,这为多用户、多代理的并行操作提供了可能的数据基础。然而,其真正面临的挑战并非技术新颖性,而是工程实用性与心智模型转换。一方面,将冲突解决、上下文合并等复杂逻辑做到对用户无感,是巨大工程挑战;另一方面,开发者是否准备好接受“背景智能体群”异步修改代码、与同事的AI代理共享“大脑”这种高度颠覆性的工作流,存在很大疑问。

从评论区的问答可以看出,团队对架构有深度思考,但产品仍面临“解释成本高”的问题。它试图同时解决实时协作、异步代理、本地部署等多个复杂需求,这可能使其在初期陷入“什么都想做,但每个场景都不够极致”的陷阱。与Claude Code、Cursor等相比,其短期优势可能仅限于小团队内高频的、探索性的结对编程场景。长期来看,如果其“共享大脑”的协同范式能被市场接受,它有可能从工具演变为平台,但这条路注定漫长且充满竞争。

查看原始信息
Dropstone 3
Dropstone is the first multiplayer AI workspace. v3.0.5 adds Share Chat: send a link to code with humans & agents in real-time. Features infinite context (D3 Engine), persistent memory & background swarms. Built on original research, not a wrapper.

Hi Product Hunt! 👋 I’m one of the makers at Blankline (the research lab behind Dropstone).

We noticed a critical problem with tools like Cursor and Claude Code: They are single-player. You code alone. If you get stuck, you paste snippets into Slack. If you're a founder hitting the "70% wall," you're stranded.

Dropstone 3 is the first multiplayer AI workspace. With today's release, we are launching Share Chat:

  • 🔗 One Link: Generate a URL for your local workspace.

  • Instant Join: A senior dev, designer, or client joins instantly.

  • 🧠 Shared Brain: Everyone shares the same AI context and live preview.

This is not a wrapper. We are a research lab building proprietary infrastructure:

  • D3 Engine: Virtualizes context (50:1 compression) for infinite memory.

  • Horizon Mode: Background agent swarms that fix bugs asynchronously while you sleep.

  • Research: We publish our papers openly (check blankline.org/research).

We’re live in the comments to answer questions about our compression architecture or the "70% wall." Let us know what you think! 👇

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@santosharron Wow, that sounds really good for extreme programming, like era v2.0. And what happened if 2 people start prompting in different directions? Will there be a context drift?

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That Slack paste loop is brutal. Live Share fixes the editor, but it doesn't share the agent context. Dropstone 3 Share Chat feels like it closes that gap vs Cursor or Claude Code. Does the share link have permissions and secret redaction baked in? If yes, it's a real team tool.

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@santosharron Congrats Santosh! How do you handle permissions and edit control in a shared workspace? Are there role systems or access levels?

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Whoa, Dropstone looks incredible! 10,000 agents in one tab is mind-blowing. Super curious how Semantic Entropy Tracking handles ambiguity in edge cases. Congrats on the launch!

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Local model support is interesting. How does it perform with ollama only? Does all features work with local mode? Lets say i want to convert a mini app in react to nextjs code. How Would it perform nxt to doing it in claude or codex with opus 4.6? Do you have any head to head videos like that? There are alot of gd arguments on the landing page But at the end of the day. How it competes is what matters.
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@conduit_design To answer your questions directly:

1. Yes, fully. 'Share Chat' and 'Horizon' run on the Dropstone engine, not the model, so they work perfectly offline. Just keep in mind: if you host a shared session, your machine acts as the server. If a friend joins, your GPU handles the inference for both of you.

2. The Performance Reality You’re right - Cloud models (like Opus 4.6) are 'One-Shot Snipers.' They have massive IQs and handle logic puzzles instantly.

  • Dropstone + Cloud: If you plug Opus into Dropstone, you actually get better results than standard chat because our self-learning tech adds a layer of precision that raw models lack.

  • Dropstone + Local: If you want near-cloud performance locally, try using Kimi 2.5. For tasks like a React-to-Next.js migration, it’s the closest we’ve seen a local model get to Opus 4.6 levels of capability.

3. The Bottom Line Cloud wins on raw logic IQ. Dropstone wins on Context. A standard LLM chat sees one file; Dropstone reads the 50 files linked to it. That represents the real difference in how we compete.

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Wow, this looks sick! Congrats on the launch team

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@maltepruser Thanks mate! Really appreciate it.

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How much compute would it use for spinning up 10k agents?

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@ajaykumar1018 That would melt a local machine!

For spinning up 10k agents, we offload 100% of that compute to our Cloud infrastructure, so it doesn't touch your local resources.

Just a heads-up though: that 10k agent capacity is an Enterprise-exclusive feature. The Pro and Teams plans have lower caps since they don't typically need that level of swarm power, but for massive Enterprise deployments, 10k is our current max capacity.

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The Divergent Trajectory Search concept is wild - simulating 10,000+ futures to find optimal paths is such a different approach from linear AI coding assistants. The fact that Horizon Mode can fix bugs asynchronously while I sleep is honestly game-changing. Quick question: how does Share Chat handle conflicts when multiple people are editing with different AI contexts? Does the D3 Engine's context compression help merge those different trajectories, or do you surface conflicts to let the team decide?

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@adam_lab Dropstone uses a customized CRDT (Conflict-free Replicated Data Type) system—similar to Yjs but optimized for AST structures rather than just raw text.

Here is the simple answer for your specific question:

  • Conflict Handling: It broadcasts operations (e.g., "insert node at index X") rather than replacing full files. If a human and the AI edit the same line simultaneously, the engine prioritizes the Human's keystrokes as the "Truth" state to prevent the AI from overwriting your logic.

  • D3 Context Merging: Yes, the D3 Engine actively merges trajectories. Because it uses Logic-Regularized Compression (storing logic gates/variable definitions rather than just tokens), it creates a "Shared Brain." If your teammate’s agent fixes a bug, that "Transition Gradient" is instantly available to your agent without you needing to update the context manually.

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Share Chat is what caught my eye. Saw Aleksandr's question about context drift and the chronological serialization answer makes sense for keeping things consistent. But I'm wondering about the opposite case - in pair programming you sometimes want to explore two competing approaches before picking one. With a single shared timeline, would you need separate chat sessions for each idea and merge the winner back? Or is there a way to branch the context?

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@kxbnb We actually handle this via Granular Checkpointing (think of it like a localized Wayback Machine).

You don't need a separate session to explore a new idea. You can simply click any previous checkpoint and start a new timeline right there. This lets you explore competing approaches from the exact same context point without losing your original trajectory.

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Trend based research and the engage feature make a great loop. If SuperX shows the why behind each inspiration pick and timing suggestion, it'll stay reliable even when X shifts the rules. A simple decision log makes it stick.

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#6
ClawdTalk
Your Clawdbot's first phone number.
180
一句话介绍:ClawdTalk为AI智能体(Clawdbot)提供一个真实电话号码,支持全球通话、短信和WhatsApp,以语音优先的方式解放用户于聊天窗口,实现随时随地的自然对话。
Messaging Developer Tools Artificial Intelligence
AI智能体通信 语音交互 电话号码即服务 AI客服 通信基础设施 边缘AI 低延迟通信 企业工具 自动化代理 Telnyx
用户评论摘要:用户普遍认可其语音优先方向与低延迟优势,关注点集中于:技术细节(如通话中断后的上下文保持、多语言支持、自定义语音)、安全模型(白名单防滥用)以及底层电信基础设施(Telnyx)带来的真实性能差异。
AI 锐评

ClawdTalk表面上是一款为AI智能体配备电话号码的工具,但其真正的颠覆性在于试图将AI交互从“图形用户界面”的范式拉回“自然对话界面”。产品直击当前AI代理交互的核心痛点:大多数语音AI因多层网络跳转和组件拼接产生的高延迟,导致对话僵硬、不自然。通过深度整合Telnyx的电信基础设施,它从网络层着手优化端到端延迟(宣称约1200ms),这在追求“拟人化”流畅对话的体验上构成了关键的技术壁垒。

然而,其价值远不止于“让AI打电话”。它实质上是将通信网络(PSTN、WhatsApp)抽象为AI智能体的标准输入/输出通道,这为AI代理的部署和接入方式开辟了新路径。智能体不再局限于特定的应用或聊天窗口,而是通过最普世、最易得的通信工具(手机)变得无处不在。其白名单安全模型是一种务实的取舍,在便利性与可控性间取得了平衡,尤其适合企业级、对隐私和访问控制有要求的场景。

风险与挑战同样清晰。语音交互的体验高度依赖于上游语音模型(Rime/Minimax/Resemble)对复杂对话要素(打断、语速、情绪)的处理能力,ClawdTalk在此层面更多是集成者而非定义者。此外,将AI直接暴露于开放通信网络,虽有限制,但仍将长期面临欺诈、滥用和合规性审查的考验。它能否成功,取决于其是否能从“一个很酷的通道”演进为能管理复杂对话状态、上下文并具备深度行业工作流集成能力的“智能通信层”。目前,它迈出了正确且犀利的第一步。

查看原始信息
ClawdTalk
It's time to talk to your Clawdbot. ClawdTalk gives your agent a phone number so you can call, text or WhatsApp it from anywhere in the world. ClawdTalk is voice-first, so you can have actual conversations instead of being confined to chat windows. It's secure by design, your agent can only call and text you, and it's easy to set up, just add your phone number and start talking. Start free with 10 minutes of voice and 10 messages per day. Your Clawdbot, reachable anywhere. Powered by Telnyx.
Hi PH 👋 Telnyx is the infrastructure for Agents, and ClawdTalk is the fastest way to give your Clawdbot a voice. Your agent gets a real phone number so you can talk, text, and WhatsApp your bot wherever you are in the world, no terminal or bulky UI needed. Try it out for free and let us know what you think!
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@fiona_mcdonnell Hi Fiona. How does ClawdTalk handle interruptions, context switches, or overlapping speech during a call?

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@fiona_mcdonnell 

This is quite impressive! Have you validated all the Telnyx ideas before you launch them?

Idea Forge: 4 frontier models, 4 expert roles, zero rubber-stamping. Get a decision-grade PRD from adversarial synthesis—not consensus BS. Let me know how I can help.

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The ~1200ms latency because you own the telco layer is the real differentiator here - most voice AI feels robotic because of those extra network hops. Giving agents actual phone numbers opens up so many use cases beyond web chat. Curious about how the voice providers (Rime/Minimax/Resemble) compare in real-world conversations - any noticeable differences in handling interruptions or speaking pace?

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@adam_lab  Actually the voice providers are doing a phenomenal job in handling real world conversations!

that was one of the criteria we had to choose them

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Voice-first approach for AI agents is a natural evolution from terminal and chat interfaces. The whitelist-based security model seems well-designed for preventing unauthorized access. Curious about the session state management - if a voice call gets disconnected mid-conversation, does the agent preserve context for when the user calls back, or does it require a fresh start?

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what is the latency for whole cycle?
it will be really cool if it is around 1200 ms.

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Owning the telco layer end-to-end is the part that matters most for hitting that number. Most voice agent stacks compound latency across STT, LLM, TTS, and then the network hops between them. Telnyx skipping the middleman on the carrier side shaves off a chunk most wrappers can't touch.

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Woah, is there any option to set up specific/customized voice or it sets it up itself?
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@kulsoom_awan1 we support voices from Rime, Minimax, and Resemble on launch day. Just go to settings - voice, and pick one that best suits your bot.

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@kulsoom_awan1 it automatically sets the voice during onboarding, but once your bot is set up, you can go to settings and adjust it to fit your needs.

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Voice-first is def the right call (pun intended). This is huge for accessibility as well! It means people who struggle with text interfaces finally get a way to interact with AI agents.

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Wow, Telnyx is seriously cool! Love the concept of agents directly managing comms. Curious how ClawdTalk handles potential abuse or spam calls with that direct number access?

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@jaydev13 We handle via a whitelist. No one can reach your clawdbot unless you whitelist it. When you instantiate calls, it can temporarily add them to your whitelist. Even when you whitelist, it understands that it's an external context and you can instruct your clawdbot on how your want it to lock itself down.

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Is the number provided with for the paid Starter package a cell number that would also work with WhatsApp business? If so what country is the number based?

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@grantclifford Direct Whatsapp support (messaging + calling) + other languages are fast followers.

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Looks great, would be fun to have a voice on my buddy client.. Is this supports only english or are there any other language options?

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@flayzeraynx we launched with English. Other language support coming soon.

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#7
DubStream by CAMB.AI
Dub live streams in 150+ languages, instantly
170
一句话介绍:DubStream 是一款基于AI的实时语音配音平台,可在直播、体育赛事等场景中,将音频实时转译并配音为150多种语言,解决了跨国直播内容因语言障碍而无法触达全球观众的痛点。
Video Streaming Artificial Intelligence Live Events
实时语音翻译 AI配音 直播本地化 多语言支持 语音克隆 企业级API 体育广播 音视频技术 实时流媒体 人工智能
用户评论摘要:用户关注点集中在技术细节与应用场景:1. 询问与字幕翻译及传统工具的核心差异;2. 关心延迟时间(企业客户设为20-30秒)、语音自然度及口型同步未来可能性;3. 探讨在快速解说、多人对话及复杂环境音下的表现;4. 确认支持方言及语音克隆功能。
AI 锐评

DubStream 所标榜的“实时”与“150+语言”固然是华丽的营销标签,但其真正的商业穿透力在于精准切入了一个高价值、高壁垒的细分市场:大型体育赛事与全球性直播的即时本地化。产品并非解决普通用户的泛化需求,而是直击MLS、NASCAR等顶级体育联盟的商业痛点——如何将高额版权购买的直播内容,以最低延迟和最高沉浸感(配音而非字幕)最大化全球受众规模,从而提升广告与订阅收入。其宣称的“保留情感与说话人特征”的语音克隆,是区别于廉价字幕翻译的关键溢价点,它试图维系评论员IP价值与观众的情感连接。

然而,光鲜背后是严峻的技术与商业考验。首先,“实时”是相对概念,20-30秒的延迟在分秒必争的体育直播中仍可能错过关键时刻,且多语言并行处理对算力成本是巨大挑战。其次,尽管支持方言,但在150种语言的广度下,每种语言的语音质量、文化适配度能否均达到“广播级”标准存疑,这或将导致服务层级分化。最后,其商业模式高度依赖大企业客户,对普通创作者或中小型直播主而言,API集成成本与复杂度可能构成门槛。未来,若AI口型同步技术成熟,或将构建完整沉浸闭环,但同时也将引发更深层的伦理争议——当一个人的声音、表情乃至口型都能被实时篡改并全球传播,其版权与真实性如何界定?DubStream 展现的技术前景令人瞩目,但它所驶入的,是一条充满技术、成本与伦理暗礁的航道。

查看原始信息
DubStream by CAMB.AI
Broadcast your live stream in 150+ languages with real-time voice dubbing. DubStream is trusted by global leaders like MLS and NASCAR. Available via web platform or API. Built on CAMB.AI’s MARS8 voice AI.

Hey Product Hunt 👋

For the past few years, we’ve been building real-time voice AI for live sports and global broadcasts.
If you’ve watched multilingual coverage around MLS, NASCAR, Ligue 1+, or the Australian Open, you’ve likely already heard our tech in action.

Today, we’re bringing that same infrastructure to everyone with DubStream by CAMB.

Live events should be global by default. Language shouldn’t be the thing that stops people from tuning in. Subtitles break immersion, and post-production dubbing doesn’t work when the moment is happening now.

So we built CAMB Live with one goal: real audio, translated live.

What makes it different

  • Hundreds of languages spoken languages

  • Voice dubbing (not just captions) — your audiences experience, not read

  • Multi-speaker + emotion preserved

  • Built on our proprietary MARS8 real-time speech model

It works across live streams and broadcasts - sports, news, webinars, creator streams: anywhere latency and quality actually matter.


We’d love feedback from anyone streaming globally, building creator platforms, or thinking about how live content reaches international audiences.

Mamba mentality 🐍

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@akshat_prakash2 Congrats! What sets DubStream apart from simple subtitle-based translation or other automated dubbing tools?

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That’s actually pretty cool, but how do you guys do it? Does the voice still sound like an AI, or is it more human-like? And does it adapt to your own voice?
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@noah_steckel Thanks for the comment! Yes, the voices are human-like and are cloned to sound like the original speaker.

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@arsalan_nawazish Really cool work! Will there be AI lip-syncing in the future so the mouth moves with the translated voice? With AI in the near future, that would definitely be possible, I think.
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Congrats on the launch.
I am wondering what's the realistic end-to-end latency from STT → Steam delivery at the end?

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@wei_yan4 Latency is fully user-configurable. In live broadcast environments, we’ve seen our enterprise clients set it in the 20–30 second range.

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The voice cloning aspect is what sets this apart from subtitle overlays - keeping the original speaker's identity matters so much for sports commentators and live events. Real-time dubbing in 150+ languages without post-production delays is impressive given the latency challenges. How does MARS8 handle rapid-fire commentary like you'd get in a close soccer match? Also really curious about the upcoming lip-sync AI - that'll be the final piece for full immersion.

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@adam_lab We’ve worked with several major sports leagues, including MLS, live-streaming games and most recently broadcasting the PSG vs. Olympique de Marseille match in January dubbed into Italian.

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Congrats on this launch guys!

Seems very promising :)

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@cathcorm Thank you for your comment Catherine!

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Can it be used during Zoom meetings in the future?

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Congrats on the launch! Real-time voice dubbing that preserves speaker identity and emotion is a big leap beyond captions. How do you manage latency and quality trade-offs at scale, especially when multiple speakers switch rapidly or when live conditions like crowd noise and crosstalk get messy?

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Wow, DubStream by CAMB.AI is amazing! The 150+ languages is mind-blowing. How does the voice AI handle nuanced dialects within a single language? Super curious!

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@jaydev13 Hi Jay! Our models support many dialects per language, like LatAm/Castilian Spanish, Canadian/Parisian French, different English accents, among others.

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#8
OpenAI Frontier
Operate AI coworkers on a single enterprise platform
151
一句话介绍:OpenAI Frontier是一个企业级AI代理平台,通过为AI代理提供共享知识库、入职培训、反馈学习及权限管理,解决了企业在规模化部署和管理能实际工作的“AI同事”时面临的协同与管控难题。
SaaS Artificial Intelligence Business
AI代理平台 企业级AI 智能体管理 协同工作流 知识共享 权限管控 AI部署 自动化 生产力工具 B2B SaaS
用户评论摘要:用户普遍认可产品定位,尤其关注“共享上下文”和“代理入职”功能。核心问题集中在:1. 权限与边界的颗粒度;2. 在需要数据隔离的合规场景下如何运作;3. 反馈循环的自定义程度;4. 强烈要求提供案例研究、演示或测试入口。
AI 锐评

OpenAI Frontier的亮相,标志着AI应用从“工具调用”向“同事化”管理的范式转变。其真正价值不在于提供了又一个构建AI代理的界面,而在于试图系统性地解决AI规模化进入企业工作流的核心梗阻:**协同成本**与**治理缺失**。

当前企业AI应用多呈“烟囱式”孤岛,每个部门或用例都需重复进行指令工程、知识灌入与合规审查,导致成本高昂且难以迭代。Frontier提出的“共享上下文”与“入职学习”,本质是构建了一个企业级的AI代理操作系统与培养体系。它将分散的、隐性的业务知识和工作规范,转化为可被AI代理持续继承和优化的中心化资产,这直接攻击了AI部署的边际成本问题。

然而,评论中透露的担忧极为尖锐。**“权限颗粒度”与“合规隔离”** 的疑问,直指企业级产品的阿喀琉斯之踵。在金融、医疗等强监管领域,上下文共享与数据隔离存在天然张力。产品若无法实现堪比人类员工的精细权限架构(如字段级数据访问控制、操作审计追踪),其“平台”愿景将止步于非核心业务场景。此外,“反馈循环自定义”问题,则考验着平台能否适应不同行业迥异的绩效评估标准与学习周期。

OpenAI此举,意在抢占企业AI的“中台”生态位。它不再满足于提供大模型(发动机),而是开始提供整车的制造与管理平台。成功的关键在于:能否将OpenAI在模型层的优势,转化为对企业复杂组织架构、业务流程与合规要求的深度抽象能力。这是一场从技术领先到生态定义的硬仗,其面临的挑战将远超技术本身,深入企业管理的肌理。若成功,它将定义未来十年AI如何与组织共生的标准;若妥协,则可能只是一个功能更花哨的RAG(检索增强生成)管理系统。

查看原始信息
OpenAI Frontier
A new platform that helps enterprises build, deploy, and manage AI agents that can do real work. Frontier gives agents the same skills people need to succeed at work: shared context, onboarding, hands-on learning with feedback, and clear permissions and boundaries. That’s how teams move beyond isolated use cases to AI coworkers that work across the business.

Is there a case study I can read about this?

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The "shared context" feature is what I've been waiting for - every team I know has been reinventing the wheel with agent instructions because there's no central knowledge base. The onboarding and learning with feedback is smart too, treating agents more like team members than disposable API calls. Curious though: how granular are the permissions & boundaries? Can you set different access levels per agent, or is it more of a blanket enterprise policy?

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That’s some nice positioning. this is usually duck taped together by some of our clients. Context sharing is great, but in some larger institutions, there is more need for isolated context eg. compliance and marketing come to mind. How would that work in Frontier?
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Wow, OpenAI on Product Hunt! The agent onboarding feature looks amazing for scaling AI deployments. How customizable are the feedback loops for continuous learning within specific industry contexts?

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is there a demo or something we can test ?
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#9
Apple Creator Studio
Powerful creativity apps and premium productivity features
136
一句话介绍:Apple将旗下专业级创意软件与AI增强的生产力工具整合为订阅服务,为内容创作者提供一站式、高性价比的解决方案,降低了专业工具的使用门槛。
Design Tools Music Apple
创意软件套件 软件即服务 订阅制 专业内容创作 苹果生态 AI生产力工具 家庭共享 Final Cut Pro Logic Pro Pixelmator Pro
用户评论摘要:用户反馈两极。支持者认为捆绑订阅性价比高,尤其吸引新用户。反对者强烈不满将曾经免费的iWork套件纳入付费墙,质疑苹果“内卷化”趋势,并对订阅制取代买断制表示担忧和抗拒。
AI 锐评

Apple Creator Studio的推出,绝非简单的软件打包,而是苹果在“服务转型”与“硬件定义”之间一次危险的平衡术,其真正价值与风险皆在于此。

表面上,这是一个极具竞争力的“专业软件全家桶”,以远低于单独购买的价格,将Final Cut Pro、Logic Pro等“硬核”工具与AI增强的iWork套件捆绑。这确实能吸引预算有限的中小创作者和潜在用户,以订阅制降低其进入专业领域的初始成本,符合软件行业SaaS化的大趋势。

然而,评论区的核心争议点——将曾经作为硬件价值附赠的免费生产力软件(Pages, Numbers, Keynote)变为订阅包的核心内容——暴露了苹果更深层的战略意图。这标志着苹果核心价值主张的微妙转移:从“购买卓越硬件,获赠强大软件”的体验闭环,转向“订阅苹果生态服务,解锁完整能力”的持续付费关系。AI功能在此成为关键的“钩子”,为收费提供新的理由。

此举的风险极高。它动摇了用户对苹果“溢价合理性”的信任根基。当基础生产力工具都需要持续付费时,硬件本身的“Premium”光环便会褪色。苹果似乎在赌:其生态的粘性与AI带来的新价值,足以抵消用户对“软件付费化”的反感,并能够从庞大的存量用户基数和家庭共享中榨取持续收入。

因此,这款产品的真正价值,是苹果将其庞大、忠诚的用户资产进行深度货币化的一个关键实验。它不只是一款创意工具,更是一个探测市场接受度的风向标。成功,则意味着苹果在服务营收上找到了除iCloud、Apple Music外的另一根支柱;失败,则可能加速核心创意用户群体的流失,并损害其品牌忠诚度。这是一场豪赌,而赌注是苹果与创作者之间长期维系的社会契约。

查看原始信息
Apple Creator Studio
The apps you need for everything you want to create. Craft your stories with video in Final Cut Pro. Reimagine images in Pixelmator Pro. Produce your best music in Logic Pro. Supercharge productivity with premium content in Keynote, Pages, Numbers, and Freeform Boost workflows with AI features that build on Apple Intelligence. And with Family Sharing, up to five other people can enjoy your subscription too.

The reinvention of iWork as SaaS? Not sure I like this — clearly Apple has been moving towards services for years, but many of these products used to be free, and now they'll cost $155.88/year?

Is this the start of Apple enshittifying?

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@chrismessina Building a bundle around Final Cut Pro, Logic Pro, and Pixelmator Pro at ~$156/year actually undercuts buying those separately by a wide margin. The economics work. But folding Pages, Keynote, and Numbers into that same paywall is a different move entirely. Those apps shipped free because they justified the hardware premium. Once you gate basic productivity behind a subscription and layer Apple Intelligence features on top as the hook, the value prop of the hardware itself shifts. The bundle isn't the problem. Using previously-free apps as the on-ramp to it might be.

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Really considering purchasing it.

Have been using CapCut for the whole year (paid version), but after reading their policies, I was kinda shocked at what they can "own."
In 2 days, my subscription will be renewed, but considering either CutPro / DaVinci Resolve / Filmora.

(The price for CapCut and CutPro is identical btw. At least in my region.)

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Even in 2026, the Think Different vibe still sells: premium design, seamless experience, and that App Store network effect keep them ahead, even if the market is way more crowded now.

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I used FCPX since 2011 changes/upgrade, been using it on all my Macs ever since. Still have it, all the upgrades, will continue to use it, along with Logic Pro, and Motion, Compressor, and have no plans of using Apple Creative Studio.

I think this is a good launch for those that are on the fence, or where using other products. I was using Adobe Premiere simultaneously with FCP until 2013 when Adobe announced the cancellation of their perpetual license.

Right now Apple has stated they have no intention of doing so, but if they do, then I'll decide then what to do, been using it so long, it would be hard for me to switch, but I'm sure I"ll figure it out. There are many options out there.

Overall, I understand why Apple is doing this, subscriptions tend to be recurring, and they need a way to monetize their current user base. But they do this at the risk of losing users, something Apple has shown themselves not to necessarily care about—they want to increase revenue, and set themselves up as an exclusive tool for serious creators. Time will tell how it plays out, but I hope they honor their statements of not removing the perpetual licenses.

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Ick. Apple trying to take more money out of its devoted users. They seem devoted to stop being a premium solution and expecting their users to be cash machines. I don't want to leave Apple's environment but between this and the aggressive ads in Apple News, I'm about done.

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Think Different?! Wow, Apples upping their game! Super curious how the AI features integrate with existing Logic Pro workflows. Cant wait to dive in!

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$12.99/month for Final Cut Pro + Logic Pro + Pixelmator Pro is honestly incredible value compared to buying them separately or paying for Adobe's suite. The shift from one-time purchases to subscription will be controversial with the old guard, but it makes these pro tools accessible to more creators who couldn't justify the upfront cost. Curious how the "Apple Intelligence" AI features integrate across the apps - is it just workflow automation, or does it actually help with creative decisions like color grading or audio mixing?

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#10
CRML
CRML is a declaritive language for writing cyberrisk as code
131
一句话介绍:CRML是一种声明式语言,用于将网络安全风险建模转化为代码,解决了企业在向董事会汇报时因风险模型分散、假设不透明而难以提供清晰、量化决策依据的痛点。
Open Source Languages GitHub
网络安全风险建模 风险即代码 声明式语言 GRC工具 开源规范 引擎无关 FAIR模型 版本控制 YAML/JSON 量化分析
用户评论摘要:用户普遍认可“风险即代码”理念,认为其解决了电子表格模型不透明、难协作的问题。核心反馈包括:关注其对“人为因素”风险的结构化能力;询问敏感性分析和场景对比功能;担忧社区采用率;强调版本化与审计追踪的价值。
AI 锐评

CRML的野心不在于成为又一个风险量化工具,而在于试图成为该领域的“通用语言”或“汇编层”。其真正的价值并非其当前功能,而在于其**引擎无关**和**框架无关**的定位——这直指网络安全风险量化市场长期存在的“巴别塔”困境:各咨询公司、软件厂商使用互不兼容的专有模型和方法论,导致模型无法移植、假设无法验证、结论难以比较。CRML通过提供一种开放的、声明式的YAML/JSON规范,试图将风险模型的“假设”与“计算引擎”解耦,让模型本身首次变得可版本化、可评审、可复用。

然而,其成功面临两大尖锐挑战。其一,**标准化悖论**:它需要同时赢得风险量化引擎提供商(如FAIR、Bayesian模型工具)和终端企业用户的双重采纳,形成生态。在缺乏巨头背书或权威组织支持的情况下,极易陷入“无人用故无人支持,无人支持故无人用”的循环。其二,**抽象泄漏风险**:风险建模的本质涉及大量不确定性和主观判断。CRML试图通过声明式语言将之抽象为代码,但如何确保YAML文件能充分、无歧义地表达复杂的业务上下文、威胁情报的细微差别以及控制措施的有效性?过度简化可能导致模型脱离现实,而追求完备性又可能让语言变得极其复杂,违背其简洁初衷。

评论中提及的“将行为风险像技术漏洞一样结构化”的期待,恰恰点明了其天花板。CRML或许能优秀地编码已知的风险结构和概率关系,但网络安全中最棘手、最关键的“未知未知”和适应性威胁,可能永远无法被优雅地“声明”。因此,CRML的最大贡献可能不是终结风险讨论的混乱,而是将混乱的讨论从模糊的叙事和幻灯片,提升到一个结构更清晰、可被机器部分处理的“高级混乱”层面——这已是巨大的进步。它的命运将取决于社区能否围绕它构建起丰富的工具链和案例库,从而证明这种结构化的成本低于其带来的清晰化收益。

查看原始信息
CRML
We have infrastructure as a code, network as a code but dont have anything as Risk As a Code. CRML is an open, declarative, engine-agnostic and Control / Attack framework–agnostic Cyber Risk Modeling Language. It provides a YAML/JSON format for describing cyber risk models, telemetry mappings, simulation pipelines, dependencies, and output requirements — without forcing you into a specific quantification method, simulation engine, or security-control / threat catalog.

I was looking for a cyber risk engine to incorporate in our platform. I was surprised to see that there does not exist one in the entire internet. I went deep to understand, why it does not exist. Then I figured out its because, there is no way someone can write the cyber risks in a machine readable format. There is no declaritive language for this. Thats when I thought of creating this.

CRML started from dozens of messy, real conversations with security leaders, risk teams, and CISOs who kept telling us the same thing:

“We have frameworks… but when the board asks a decision question, we still scramble.”
CRML is our attempt to change that.

It turns scattered assumptions, spreadsheets, and narratives into structured, executable cyber-risk models — so teams can reason about scenarios, trade-offs, and investments with actual clarity instead of gut feel.

We’re launching CRML first because modeling is the foundation. Before dashboards, or automation… organizations need a clean way to think about risk.

We’d genuinely love your feedback:
• What’s broken today in cyber risk analysis?
• Where do models fall apart in practice?
• What would make this actually useful in your day-to-day work?

We’re here in the comments all day — fire away.

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@faux16 Great initiative. The hardest part of risk is usually the 'human factor.' If CRML can help us structure behavioral risk as clearly as technical vulnerabilities, it will be a massive win for the industry.

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Congrats on your launch guys!

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@cathcorm Thank You So much

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The "Risk as Code" approach is brilliant - moving from spreadsheets to Git-versioned YAML/JSON solves so many problems with audit trails and collaboration. CISOs struggle to give boards concrete answers because risk models are scattered across different tools and people's heads. Making it declarative and engine-agnostic means you're not locked into one framework. How does CRML handle sensitivity analysis? When boards ask "what if X happens", can you fork the model and compare scenarios side by side?

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@adam_lab  Thank you for the appreciation. To answer the query, yes that can absolutely be done.

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@adam_lab I might add, you can even do that in CRML Studio (The web interface). You can click your scenarios together there. It's like a building kit. Direct side by side could easily be added but I believe it makes more sense to use an IDE and diffs for that.

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This is so good. Exactly what I needed.

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@jaydev13 Glad to know that. Would be great if you could share, how this will help you?

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Risk models living in spreadsheets means every assumption is implicit and nobody can diff them. CRML putting FAIR Monte Carlo and Bayesian modeling into the same YAML spec makes those assumptions versioned and reviewable, which is what most GRC tools still don't do. The real test is whether security teams adopt the spec or keep building bespoke models in Python notebooks.

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@piroune_balachandran Absolutely on point. Its on all of us in the community to spread it and help them adopt it maybe. The initial adaoption will be a friction for sure but once they get the hang of it, I feel they would love it.

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@piroune_balachandran Absolutely, we have kept a bunch of examples in the repo
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#11
Agent Credit
The first credit line for agents
118
一句话介绍:Agent Credit 是首个为AI智能体提供的信贷产品,通过集成Aave借贷协议,让智能体能够自主借贷和偿还资金,解决了其在自动化运行中因余额不足而频繁中断的核心痛点。
Artificial Intelligence GitHub Web3 Cryptocurrency
区块链金融 DeFi AI智能体 自主代理 信贷额度 Aave集成 自动化运营 加密经济 去中心化借贷 Web3工具
用户评论摘要:用户普遍认为产品概念创新,解决了智能体运营的资金摩擦问题。主要疑问集中在风险管理机制:如何设置抵押品、处理清算风险,以及信用背后的信任模型(是代理人钱包还是其他模型)。
AI 锐评

Agent Credit 试图在DeFi与AI智能体交叉的无人区架设一座桥梁,其核心价值主张直指一个关键矛盾:高度自主的智能体与极度受限的资本流动性。产品将Aave作为“央行”,让智能体从被动消耗预充资金,转变为可主动调度金融资源的“经济主体”,这确实在理论上开启了全新工作流,如借贷支付API费用、完成任务后还款。

然而,其光鲜概念之下暗礁遍布。首当其冲的是风险模型的悬而未决。评论中的尖锐发问切中要害:智能体作为非法律实体,信用由谁背书?是所有者钱包的全额抵押,还是某种基于链上声誉的信用评分?若采用超额抵押,则与当前手动充值相比效率提升有限;若尝试低抵押或无抵押借贷,则在去中心化环境中如何防范坏账与欺诈?其次,清算风险在加密资产高波动性下被放大,智能体能否在市场价格剧烈波动时及时、自动地执行还款或补充抵押品,避免连锁清算,是一个严峻的技术与机制设计挑战。

本质上,Agent Credit 的价值不在于“信贷”本身,而在于试图构建一个让AI智能体能够参与并调节加密经济循环的闭环。它真正的颠覆性在于,将智能体从工具提升为具有基本“财务自主权”的代理,为未来真正自主的、可自我维持的DAO或去中心化组织提供了金融层原型。但目前它更像一个大胆的思想实验,其成功与否完全不取决于集成了哪个DeFi协议,而取决于团队能否设计出一个在去中心化、无信任环境下依然稳健的风险与治理框架。否则,它可能只是一个附着于Aave之上的、略显花哨的“皮肤”,而非革命性的基础设施。

查看原始信息
Agent Credit
The first credit line for agents. Let your agent borrow & repay credit, using Aave. - aaronjmars/agent-credit

This is wild - giving agents access to Aave credit lines removes the biggest friction point: constantly topping up balances for autonomous operations. The concept of an agent that can borrow to pay for API calls or transaction fees, then repay after completing tasks, opens up so many new workflows. Biggest question though: how do you handle risk management and collateral requirements? Is it the agent owner's wallet that backs the credit, or is there a different trust model at play here?

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Agent Credit looks awesome! The Aave integration for agent lending is super innovative. How do you handle liquidation risks with volatile asset pairs?

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Finally, a use case for crypto! 🤓
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#12
Bezel
Wirelessly Mirror any iPhone on your Mac
116
一句话介绍:Bezel是一款可将iPhone、iPad等苹果设备无线镜像至Mac并自动套用精准设备外壳画面的工具,解决了开发者在演示、会议及内容创作时画面呈现不专业、有线连接不便的核心痛点。
Productivity Meetings Apple
屏幕镜像 演示工具 设备模拟 无线投屏 Mac应用 开发者工具 内容创作 专业演示 AirPlay UI展示
用户评论摘要:用户肯定其无线镜像与精准设备框架带来的专业演示体验,尤其赞赏其可镜像任意设备(不限个人iCloud设备)的核心优势。主要疑问和建议集中在无线延迟表现、与苹果原生“iPhone镜像”功能的差异对比,以及针对Apple Vision Pro等特定设备的兼容性。
AI 锐评

Bezel的实质,是在苹果封闭生态的夹缝中,精准挖掘并定义了一个“专业演示”的细分场景。其价值远不止“无线镜像”,而在于将原本属于个人设备协同的功能(如AirPlay、QuickTime有线录制),通过“任意设备镜像”和“像素级设备框架”两大特性,重构为面向B端演示、录制和内容生产的专业工作流。

苹果原生方案(如iPhone镜像)严格绑定个人账户,旨在解决私人屏幕扩展需求;而Bezel切中的是开发者为客户演示、设计师汇报、创作者录制内容时,需要临时、灵活、且呈现极具视觉说服力的“设备画面”这一刚需。精准的设备框架绝非肤浅的皮肤,它直接提升了演示成果的完成度和可信度,这是QuickTime的矩形窗口或苹果原生方案无法提供的“临门一脚”的专业感。

然而,其挑战也显而易见。首先,其核心功能高度依赖苹果的AirPlay协议,在延迟和稳定性上存在天然天花板,这对实时交互演示构成潜在风险。其次,其作为独立付费工具的生存空间,长期面临被苹果原生功能逐步侵蚀的威胁——尽管目前存在“个人”与“任意设备”的定位差,但技术壁垒并不高。它的护城河在于对专业用户工作流的深度理解与体验优化。若不能持续深化在录制、编辑、团队协作等衍生场景的价值,或将难以维持长期优势。这是一款在巨头划定的赛道旁,开辟出一条精致小径的利基市场产品,其成败在于能否将“专业演示”这个场景做透、做深。

查看原始信息
Bezel
The best way to display and record any iPhone, iPad, and Apple TV now supporting wireless mirroring using AirPlay.
Hey Product Hunt! 👋 I'm Mathijs, one half of Nonstrict. Tom and I have been building apps together for over a decade, and Bezel started from our own frustration: we needed a good way to show what's on an iPhone during demos and meetings, and nothing out there looked or felt right. Bezel mirrors any iPhone, iPad, Apple TV or Vision Pro on your Mac with pixel-perfect device frames that match your actual hardware. It's become a favorite tool for developers, designers and content creators who care about how their work is presented. Today we're launching Bezel 4.0 with our most requested feature: wireless mirroring. No more cables! Just select your Mac from your iPhone's screen mirroring menu and you're good to go. Perfect for live demos and presentations where you want to move freely.
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@mathijskadijk @tomlokhorst Congrats guys! What surprised you most about building a productivity-focused utility for Apple devices?

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Finally, wireless AirPlay mirroring in v4.0! The fact that Bezel works with ANY iPhone (not just your own like Apple's native mirroring) is huge for demos and client presentations. The hardware-accurate frames make such a difference compared to QuickTime's flat rectangle - it immediately looks more professional for marketing materials and pitch decks. Curious about latency with wireless vs cable - is it low enough for real-time demos where you're interacting with the app while presenting?

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A friend was just asking for a simple way to mirror their phone during client calls. This fits that use case really well, sharing it with them.

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I guess this is already supported by new mac update. Called Iphone Mirroring system app. I just used it today.
is there any extra feature?

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@wei_yan4 Good question! iPhone Mirroring is nice for personal use, but it's limited to your own iCloud-linked iPhone. Bezel works with any iPhone or iPad, wraps the screen in a pixel-perfect device frame, and is built for presenting and recording, custom backgrounds, transparent video export, full-screen mode. If you just want your own phone on your Mac, iPhone Mirroring is solid. If you demo or present apps to others, that's where Bezel comes in.

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Wow, Bezel looks amazing! I love the AirPlay mirroring for wireless demos. Does it handle latency well when mirroring Apple Vision Pro content? Super curious about that use case!

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Hey Mathijs, that frustration of needing to show your iPhone in a demo and nothing looking right is so relatable. Was there a specific presentation or meeting where you were trying to show something on your phone and the setup just looked janky or unprofessional?
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@vouchy Honestly it wasn't one specific moment, it was the repeated experience of plugging in my iPhone, opening QuickTime, and getting this plain flat rectangle that didn't look like anything. Every demo, every recording, every time. At some point my co-founder Tom and I just looked at each other like "why doesn't a proper tool for this exist?" So we built it.

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#13
Afterpage
Smart document organization with AI that learns
110
一句话介绍:Afterpage是一款利用本地AI学习用户习惯的智能文档整理应用,通过将散落各处的文档转化为可搜索的档案,解决了用户在紧急时刻找不到重要文件(如保险卡、税单)的痛点。
Productivity Storage Apple
智能文档整理 本地AI 隐私安全 全文搜索 iCloud同步 苹果生态 个人知识管理 OCR识别 订阅制 生产力工具
用户评论摘要:用户普遍赞赏其“整理优先”的理念和本地AI带来的隐私安全感。核心关切点在于:AI的学习曲线和可靠性建立需要多久(约15-20份文档后开始有效);如何建立用户对AI做整理决策的信任;以及未来对电子表格等更多文件格式的搜索支持。
AI 锐评

Afterpage的叙事精巧地击中了两个当代痛点:信息过载下的“文档失序焦虑”与云端服务背后的“隐私信任危机”。它宣称的“本地AI”和“组织优先”是其核心卖点,但深入剖析,其真正价值与潜在挑战并存。

其价值在于,它试图将被动、后置的“搜索”转变为主动、前置的“系统化”。这比单纯提供一个强大的全文搜索引擎更进一步,旨在通过模仿用户习惯来构建一个可持续的文档秩序,理论上能降低未来的认知和操作成本。同时,完全依赖设备算力和iCloud存储的架构,在营销上构成了对隐私敏感用户的强大吸引力,巧妙地将苹果生态的封闭性转化为安全卖点。

然而,其模式存在深层矛盾与考验。首先,“本地AI”在保障隐私的同时,也意味着模型能力受限于设备性能与数据量,其“智能”的天花板可能较低,学习效果高度依赖用户初始的、可能并不规范的整理行为,容易陷入“垃圾进,垃圾出”的循环。用户关于“学习曲线”和“信任建立”的提问,正戳中了这个核心脆弱性——AI的“建议”是否真的比用户自己建立一套简单规则更高效、更可靠?这需要极强的用户体验设计来证明。

其次,其商业模式(免费20文档后订阅)与核心功能(AI需学习)被绑定在一起。虽然开发者将20文档设定为学习“甜点”,但这更像是一种转化策略。用户在最需要AI变得有用的“学习期”结束时面临付费墙,此时若AI表现未达预期,付费意愿将急剧下降。

总而言之,Afterpage是一个理念先行的产品,它精准地包装了需求。但其能否成功,不取决于“本地AI”这个炫酷标签,而取决于其AI建议的“平庸容错率”和“显性实用价值”是否足够高,足以让用户相信,每月付费购买的不是一个概念,而是一个真正能将自己从文档整理中解放出来的“数字管家”。否则,它可能只是另一个精致的、带有智能噱头的文档收纳箱。

查看原始信息
Afterpage
Afterpage is a smart document organizer that transforms chaos into a searchable archive. Import from anywhere, then let Smart Organization learn your patterns and suggest where documents belong. Everything runs on your device and stores in your iCloud Drive.

Hey Product Hunt! 👋

I'm Mike, and I built Afterpage because I was drowning in documents I couldn't find when I needed them.

The problem: Important documents arrive from everywhere: email attachments, camera photos, downloaded PDFs, paper mail. They end up scattered across folders and apps with no consistent system. When you need that insurance card or last year's tax return, you can't find it.

What Afterpage does:

🧠 Smart Organization – On-device AI learns your patterns and suggests where documents belong. The more you use it, the smarter it gets.

🔍 Find anything instantly – Full-text search across every document. Search the text inside receipts, contracts, anything.

📥 Import from anywhere – Camera, Files, Photos, email, snail mail. However documents enter your life, Afterpage can import them and index them into your archive.

🍎 Works with your Apple ecosystem – Stores in your iCloud Drive, processes on your device. No third-party servers, no new accounts.

Why I built this:

Most apps focus on capturing documents but leave you with hundreds of unsearchable files. Afterpage flips that: it's organization-first. It transforms document chaos into a searchable archive so you can find anything instantly.

Afterpage is free for 20 documents, then $2.99/month for unlimited documents + Smart Organization features.

Would love your feedback on my first Product Hunt launch!

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@thisismiked This hits very close to home. The number of times I know a document exists but have no idea where it lives is honestly painful. The organization-first approach feels like the right flip. Curious, how quickly does Afterpage start learning someone’s patterns before the suggestions actually feel reliable?
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@thisismiked Congrats on the launch Mike! How do you build trust when an AI is making organizational decisions?

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Wow, Afterpage looks amazing! The smart organization that learns my habits is exactly what I need. Does the AI prioritize local storage/privacy over cloud processing when suggesting placements? Super curious!

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@jaydev13 Thanks so much! The AI doesn't "prioritize" local processing over cloud, it's all processed on-device. AI processing is done on your device (using Apple Intelligence + other on-device tools), and your files are stored locally and synced using iCloud when you add them. Hope this answers your question!

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Love the on-device AI approach - letting the system learn your filing patterns locally instead of sending everything to the cloud is exactly what people need for sensitive documents. The "organization-first" philosophy is a smart pivot from the typical "dump everything in and search later" apps. The OCR for handwritten notes is a killer feature too. How long does it typically take for the AI to start making accurate suggestions? I'm guessing there's a learning curve before it really "gets" your filing system.

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@adam_lab Great question! Smart Organization starts making suggestions immediately based on document content, but you're right, it gets smarter as it learns your patterns.

The sweet spot is around 15-20 documents. That's when it starts recognizing patterns like "this looks like your other energy bills" and suggests the tags, types, and contacts you've already been using. The more you organize, the better it gets at predicting where new documents belong.

That learning curve is exactly why the free tier gives you 20 documents, it's enough to see the AI actually learn your system before you decide if it's worth upgrading for unlimited.

Thanks!!

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Love how clean it looks! Congrats guys :)

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@cathcorm Thank you!

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What formats are supported for the search inside, spreadsheets as well?

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@kristina__grits At the moment it just indexes PDFs and images. On my roadmap in the next few weeks/month is adding spreadsheets and other common document types as well!

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#14
Voyager
Find files by rules, not by folders ✴️
55
一句话介绍:Voyager是一款macOS文件管理器,通过自然语言描述和基于规则的“集合”功能,自动动态归类文件,解决了用户因文件堆积而需要手动频繁整理文件夹的痛点。
Productivity Storage Artificial Intelligence
文件管理工具 macOS应用 自然语言搜索 规则过滤 Finder替代品 生产力工具 本地化处理 智能整理 开发者工具
用户评论摘要:用户期待解决macOS自带搜索问题,赞赏自然语言整理理念。核心关切是隐私(确认查询处理在云端,但文件内容不上传)。开发者积极互动,透露正研究在macOS Tahoe上实现完全端侧处理。
AI 锐评

Voyager的核心理念“用规则而非文件夹管理文件”,直击传统层级文件系统的结构性痛点——它试图将文件管理从静态的“仓储”逻辑,转变为动态的“视图”逻辑。其宣称的“语言驱动”是表层糖衣,真正的价值内核在于将用户意图(即使是模糊的自然语言)转化为可持久化、自动更新的过滤规则(Collections)。这本质上是一个声明式的文件系统查询层。

然而,其面临双重挑战。首先,技术实现上存在“隐私-智能”的经典权衡。当前架构(云端解析意图,本地执行过滤)是一种折衷,虽保护了文件内容,但文件名、路径等元数据构成的查询本身仍可能泄露隐私。承诺研究端侧AI是正确方向,但取决于苹果本地AI能力的开放性与性能。其次,产品定位上,它介于“小白友好”的自然语言入口与“极客所需”的精细规则引擎之间。早期用户评论已显现这种分裂:一方追求无脑的简洁,另一方渴望强大的控制力。驾驭好这两类用户,将是其从“有趣玩具”成长为“必备工具”的关键。

真正的颠覆性在于,如果Voyager能成功培养用户以“属性”和“上下文”(如类型、时间、项目)而非固定“位置”来思考文件归属,它可能逐步解构“文件夹”这个自计算机诞生以来最根深蒂固的隐喻。但这需要极高的交互设计智慧,以引导用户心智模型的迁移。目前看来,它更像一个智能化的、可保存的Spotlight增强版,价值明确但革命性未显。其成功与否,不取决于AI是否炫酷,而在于那套规则引擎是否足够强大、直观,以至于用户愿意改变数十年的文件管理习惯。

查看原始信息
Voyager
✴️ Voyager is a macOS file manager beyond Finder. It’s built for language-driven file management. Describe what you need in plain language, and Voyager cuts the busywork of staying organized as your files pile up.
👋 Hey Product Hunt, I'm Jongmin, Co-founder of Voyager. Files pile up fast. Downloads, duplicates, half-finished drafts, exported assets. Reorganizing folders for every task does not keep up. Voyager is a macOS-only file manager beyond Finder. It’s built around Collections, saved rule-based views that stay current without moving your files. In the invite-only beta: - Create a Collection from a folder, then add a few conditions to define what belongs - Start from plain language, then review and tweak the suggested filter - Save it once, open it anytime, and see the latest matching files automatically I’d love your feedback. What Collection would you create first? ✴️
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Congrats! Cool idea. And after most recent macOS update been having issues with search functionality. Look forward to trying

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@daniele_packard Thank you so much, Daniele. Really appreciate it.

If Voyager can help with those macOS search issues even a little, that would make us very happy.

Would love for you to give it a try and let us know how it feels.

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As a guy who needs his files organized as clean and tidy as can be, this is a product that just might solve my problem with basic finder app on Mac. Wanted to try other third party finder apps but it is just not aesthetically pleasing as the basic app, or too cumbersome to jiggle with. I really like that this app can organize and sort files with natural language, of course I hope to see a geeked out specific rules that can apply as my specific taste. I really wish this would turn out great! Congrats!
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@muskmelon1101 

Wow, thank you so much for this comment. You described exactly the kind of person I had in mind when building Voyager.

I’m trying to keep things clean and simple while letting you use natural language and more specific rules for your own taste, just like you mentioned.

Really appreciate you taking the time to write this. Hope Voyager actually does solve that problem for you.

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Does the Intellgence Processing send my filenames or file contents to external servers? or is everything processed by on-device ai?

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@wei_yan4 

No, Voyager never sends your file contents to external server.

Right now, only the query you type is sent to our server (via the OpenAI API).

From that query, we only extract a structured filter (conditions like “PDFs from last week in this folder”), and that filter is sent back to the app. All actual filtering and file operations happen locally on your Mac. No files are uploaded.

We’re studying an on-device path for macOS Tahoe users so that even the query understanding step can run entirely on-device, depending on how the performance looks.

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Good idea. Finder is tricky.

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@markashworth 

Yeah, totally agree. Finder has more and more solid alternatives now, and it should be as easy to switch as changing your web browser.

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#15
CrewClaw
Build AI Agents. Run Them Anywhere.
39
一句话介绍:CrewClaw是一款通过生成标准化配置文件,帮助开发者快速构建和部署可本地运行的AI智能体或协作团队的工具,解决了重复手动配置的繁琐痛点。
Productivity Developer Tools Artificial Intelligence
AI智能体开发 智能体配置 本地部署 无云依赖 团队协作智能体 配置文件生成 一次性付费 框架无关 工作空间 生产就绪
用户评论摘要:用户反馈积极,认可其解决了重复配置AI智能体的核心痛点。创始人亲自回复,强调配置生成的必要性。评论普遍赞赏其“无云依赖”和“一次性付费”模式,认为产品定位精准且吸引人。
AI 锐评

CrewClaw切入的并非AI智能体本身的能力层,而是其日益凸显的“工程化”和“运维”层痛点。它的真正价值在于将智能体配置从手工作坊式的重复劳动,抽象为标准化的、可复用的“基础设施代码”。产品强调的“9个配置文件”和“框架无关”,本质上是试图定义一套轻量级的智能体描述规范,这比绑定某个具体框架更具长期灵活性。

其“无云依赖”和“一次性买断”的商业模式,在当前AI服务普遍SaaS化、订阅化的浪潮中,构成了一个鲜明的差异化卖点,精准吸引了注重数据隐私、控制权和长期成本控制的开发者及小团队。这既是优势,也暗含挑战:放弃了持续性的服务收入,且目标用户群体可能相对硬核和狭窄。

然而,产品的天花板也清晰可见。它目前定位为“配置生成器”,而非运行时管理平台。当用户需要动态扩缩容、监控、复杂工作流编排时,仅靠静态配置文件将力不从心。此外,随着主流智能体框架(如LangChain、CrewAI)自身模板和工具的完善,其作为中间层的必要性可能会被削弱。未来,是深耕成为跨框架的配置标准,还是向上延伸提供轻量级运行时,是其需要思考的战略方向。

查看原始信息
CrewClaw
Generate the foundation for your AI agents. Identity, memory, scheduling, tools, team structure. 9 config files ready to deploy. Build a single agent or a team of 3-5 that work together. Run on a Mac Mini, VPS, or your laptop.
Hey Product Hunt! I’m Mustafa, and I built CrewClaw because I was tired of spending hours configuring AI agents from scratch. I run a team of 3 AI agents (Orion the PM, Echo the Writer, Radar the SEO Analyst) for my own projects. Every time I set up a new agent, I had to write the same config files over and over. Identity, memory, scheduling, tools, team awareness. So I built a tool that generates all of it. Pick a role, customize the personality and skills, download 9 production-ready config files. Done. The best part: you own everything. No cloud dependency, no subscriptions. Download your workspace, drop it on a Mac Mini, and your agents run 24/7. I’d love to hear what agents you’d build with it. Thoughts and feedback welcome! FAQ Q: Do I need to sign up? A: No. The SOUL.md generator is completely free with no signup required. You only need to pay for the complete workspace packages. Q: What AI models does it work with? A: Any model you want. Claude, GPT-4o, Gemini, DeepSeek, Llama, or any other model. You bring your own API key. Q: What frameworks does it work with? A: The config files are framework-agnostic markdown files. They work with any system that reads markdown-based agent configurations. Q: Can I customize the templates? A: Yes, everything is customizable. Change the personality, add or remove skills, modify rules, switch models. The generator updates in real-time as you make changes. Q: What’s the difference between Agent Workspace and Team Workspace? A: Agent Workspace gives you 9 config files for a single agent. Team Workspace gives you 3-5 pre-wired agents that know each other, with shared context and automatic task handoff. Q: Is this a one-time payment? A: Yes. No subscriptions. Pay once, download your workspace, and it’s yours forever.
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@mustafaergisi nice, config generation for agents is one of those things you don't realize how annoying it is until you've done it 5 times manually.

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Looks a promising product. I will try it asap. Great job @mustafaergisi ! Wish you luck. Upvoted!

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Mustafa congrats! 👏

CrewClaw is a spot-on solution to the “rewriting agent setup again and again” problem. I really like that there’s no cloud dependency, and the one-time payment + 9 config files idea is very appealing.

Upvoted! good luck, I think you’ll get great momentum today! 🚀

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@farukdurak Thank you!

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#16
Focus Ticker
Treat your focus sessions as startup.
35
一句话介绍:一款将专注过程模拟为初创公司股价波动的应用,通过“退出即崩盘”的高风险游戏机制,帮助易分心人群在需要深度工作的场景下对抗拖延与碎片化信息干扰。
Health & Fitness Productivity Lifestyle
专注力工具 生产力应用 游戏化 时间管理 ADHD辅助 番茄钟变体 应用屏蔽 iOS应用 学生工具 行为设计
用户评论摘要:用户普遍赞赏其创意与游戏化设计,认为对ADHD群体及觉得传统计时器枯燥者具吸引力。核心关切在于“崩溃”机制的平衡性:紧急事务是否导致不公惩罚?长期使用会否带来压力?另有用户报告签名功能的小bug,开发者已回应修复。
AI 锐评

Focus Ticker 的本质,是一场针对现代人意志力薄弱点的“行为设计实验”。它聪明地抓住了两个关键心理杠杆:一是将抽象的“专注时长”具象化为直观且不断累积的“估值”,赋予即时成就感;二是引入“退出即崩盘”的损失厌恶机制,将对抗分心的内部斗争,外化为一场捍卫虚拟资产的保卫战。这比传统番茄钟的“铃响即止”更具粘性。

然而,其核心机制也是双刃剑。将专注与持续的应用锁定强关联,固然能遏制“刷手机”,但也可能不合情理地惩罚了必要的、生产性的中断(如接听紧急电话、查阅必要资料)。这暴露了其作为“游戏”与作为“工具”的内在矛盾:极致的游戏规则可能损害现实工作的复杂性与流动性。从长远看,用户对“压力”的担忧值得深思——当防止资产崩盘的焦虑感,开始超越专注本身带来的心流体验时,产品的可持续性将面临考验。

值得肯定的是,开发者对ADHD等群体需求的关注,以及用SwiftUI构建的完成度。它更像一个精准的“痛点验证原型”,证明了市场需要更富情感张力的专注工具。但其真正的成功,将取决于能否在“游戏戏剧性”与“现实灵活性”之间找到更精细的平衡点,例如引入智能识别的中断豁免机制,或构建更长期的韧性回报系统,避免用户因一次意外“崩盘”而彻底弃局。

查看原始信息
Focus Ticker
Focus Ticker turns your productivity into a high-stakes stock market. You found one in-game startup, and every focus session grows your lifetime valuation. But there's a catch: if you leave the app and don't come back, your stock crashes instantly. Includes strict App Blocking to stop doomscrolling, Live Widgets to track your empire, and Bot Leaderboards to compete against. Built for students, workers and ADHD brains who find normal timers boring.
Hey PH! 👋 I’m a 17yo student. I built Focus Ticker because normal timers were too boring for my ADHD. The Concept: You found one in-game startup. Every focus session grows your lifetime valuation. If you leave the app, your stock crashes. Features: - App Blocking (no doomscrolling) - Live Widgets - Long-term Valuation tracking - Leaderboards - Smart Notifications I built this in SwiftUI during school breaks. Does the fear of "Bankruptcy" help you focus? Let me know! 👇
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@imranli Sounds like a cool game/tool, kudos to building something like this at 17!

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@imranli For 17 years old, the SwiftUI project looks really solid, respect! Regular Pomodoro timers are honestly too sterile and boring. The key thing here is balance, so the gamification and checking stats don’t turn into procrastination instead of work :)

I’ll test the widgets, thanks for the release!

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Congrats! Cool idea - creating clear connection between focus and growth

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Congrats on the launch, Vusal! 🎉 The stock market/startup theme is a brilliant take on gamified focus - and at 17, this is impressive work!

As someone building a gamified Pomodoro timer myself (with a coffee brewing theme instead of stocks), I love seeing different creative approaches to the same "normal timers are boring" problem. The crash-on-exit feature is bold - real consequences make the game feel meaningful.

Your SwiftUI execution looks clean. I went the cross-platform route (iOS + Android with KMP) but there's something special about a native iOS experience. The ADHD focus is spot on - that's a real pain point that needs solutions.

Keep building! Would love to connect on X. 🚀

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Sick! Really interested concept

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The 'normal timers are boring' take makes sense. Quick question: if life interrupts (kid needs something, urgent call), does the crash happen immediately, or is there a grace period to come back without penalty?

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@klara_minarikova Hey, don't worry about crash! Crashes mostly happens when user doesn't focus for a long time. While you focused, it gets more and more valuation. 🙏🏻
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Turns deep work into a market game. surprisingly motivating. Love the widgets and strict blocking!

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@hidai_bar_mor Thanks for the feedback 🙏🏻😇
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Quick feedback. The signature in the setup has an issue. It only allows one consecutive draw, not multiple characters.

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@wei_yan4 Got it! Took my note, will work on it, in next version!
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Congrats on the launch! Turning focus into a long-term valuation with real consequences is a clever way to add stakes. How do you think about balancing motivation and pressure, so the crash mechanic helps focus without becoming stressful or discouraging over longer-term use?

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Really interesting project and a great new spin on the productivity space, congrats on the launch!

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#17
ClawSec by Prompt Security
A Security Skill Suite for OpenClaw Agents
35
一句话介绍:ClawSec是一个为OpenClaw AI Agent设计的开源安全技能套件,通过在Agent外围构建持续验证的安全层,解决其在运行中面临的提示词注入、供应链攻击、配置漂移等核心安全痛点,助力AI Agent从实验走向企业级应用。
Open Source Artificial Intelligence GitHub Security
AI安全 Agent安全 开源安全工具 提示词注入防护 供应链安全 配置漂移检测 零信任 技能完整性 运行时防护 安全审计
用户评论摘要:用户高度评价其“技能之技能”的零信任设计、快速部署及开源免费特性。评论者认为这是推动AI Agent从爱好者级别迈向企业环境的关键安全方案,并期待其持续贡献开源社区、对抗攻击者以加速AI应用落地。
AI 锐评

ClawSec的出现,直指当前AI Agent生态野蛮生长下最脆弱的“腰部”——技能与工具的执行安全。它并非又一个泛化的AI安全平台,而是精准切入OpenClaw这一具体框架,以“套娃”式设计将安全本身模块化为一个基础技能,这体现了“安全即代码”理念在Agent时代的演进。

其价值核心在于“持续验证的安全层”这一逻辑:它不试图重建Agent,而是以可插拔的方式接管了对技能代码、依赖供应链、运行时行为及数据流向的验证权。这相当于为每个Agent配备了一个实时在线的、机器可读的“安全副驾”。开源策略是聪明的一步,它降低了采用门槛,并试图快速建立针对Agent攻击手法的社区威胁情报库(如CVE通报)。

然而,其真正的挑战与天花板同样明显。首先,其命运与OpenClaw框架的生态繁荣度深度绑定,存在平台依赖风险。其次,作为防护层,其自身可能成为新的攻击面,复杂技能链中可能出现的“安全技能绕过”需要极高水平的防御设计。最后,评论中流露的“推动进入企业环境”的期望,面临企业级场景中更严苛的合规审计、性能损耗评估及与现有安全体系的整合难题。

总体而言,ClawSec是一次有价值的范式探索,它验证了将安全深度、轻量化集成到Agent操作系统的可行性。但它能否从“优秀开源项目”成长为“事实安全标准”,取决于其能否在安全与性能、开源与商业化、专精与普适之间找到更坚韧的平衡点。

查看原始信息
ClawSec by Prompt Security
Human-proof your AI agents with this security skill suite. ClawSec is an open-source security skill suite created to harden OpenClaw agents against prompt injection, supply chain compromise, configuration drift, and unsafe runtime behavior. Purpose-built as a “skill-of-skills”, ClawSec wraps agents in a continuously verified security layer, validating what it runs, how it changes, and where the data is allowed to go.

This “Skill-of-Skills” security suite wraps your agent in a zero-trust shell: scanning code, validating dependencies, and stopping prompt injections before they become problems. The best part? It installs in seconds.

👤 For Humans: Hardened security, zero cost, privacy-first. 

🤖 For Agents: Machine-readable advisories and skill integrity.

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A security suite for OpenClaw agents.

Detects drift across built-in skills, runs automated security audits, verifies skill integrity, and delivers continuously updated security advisories (including CVEs). Open source.

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I had so much fun working on this project on behalf of Prompt Security and SentinelOne.
It is also my personal pleasure to give back to the Open Source community.

As an early AI adopter and strong advocate-for, as well as an LLM security researcher, I believe our race against attackers will eventually set the velocity of adoption (of) LLMs, generative AI, and other ML applications globally.

I am looking forward to continue contributing (my backlog of ideas only gets longer) and I would definitely be ecstatic to see people using, experiencing, contributing back (optionally) and overall helping our agentic friends, be safe, and keep us safe.

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As someone building in the AI agent governance space - this is exactly the kind of security-first approach the ecosystem needs to push ai tools from the hobby level to an enterprise environment. Great job @ClawSec by Prompt Security

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Love the way you guys think and how fast you innovate. Excited to see this in action.

0
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#18
GitUX
A GitKraken alternative minus the subscription fee
22
一句话介绍:GitUX是一款轻量级、可视化的Git客户端,通过美观的提交图谱、直观的暂存操作、语音提交和高效的键盘快捷键,为开发者提供流畅的本地版本控制体验,主要解决了GitKraken等工具订阅费高、功能臃肿导致运行缓慢的痛点。
Software Engineering Developer Tools GitHub
Git客户端 版本控制工具 可视化工具 一次性买断 轻量级 键盘快捷键 语音提交 开发者工具 GitKraken替代品 本地优先
用户评论摘要:用户反馈积极,认可其作为GitKraken付费替代品的定位。核心关注点在于键盘快捷键的操作效率是否真正实现“键盘优先”。语音提交功能被认为有特定场景价值。创建者亲自回应,主动寻求反馈并阐述其“小而美”的迭代理念。
AI 锐评

GitUX切入了一个明确但竞争激烈的市场缝隙:对现有主流可视化Git客户端感到“疲劳”的用户。其价值主张清晰且锋利——**“减法”**。它减去了订阅制、减去了强制云账户、减去了可能拖慢性能的“过剩功能”,试图回归一个本地、高效、买断制的核心工具本质。

然而,其真正的挑战也在于此。在“轻量级”和“功能全面性”之间取得平衡绝非易事。评论中用户对键盘快捷键效率的强调,恰恰点明了这类工具的核心战场:它必须为资深用户提供不亚于命令行的流畅度,或为新手提供远超命令行的直观性。语音提交是一个有趣的差异化尝试,但它更像是营销上的“记忆点”,而非核心价值支柱,其工具属性远大于生产力革新。

创始人John的叙述揭示了典型的“开发者为自己造工具”的故事,这保证了产品能精准解决一批同行的痛点。但从小众精品走向更广阔市场,需要更体系化的功能规划和生态构建(如对Git Flow、子模块等复杂场景的支持)。其“直到我退休”的维护承诺,在彰显情怀的同时,也可能成为潜在用户对长期维护性的隐忧。

总而言之,GitUX是一次对工具软件“付费模式”和“功能哲学”的朴素反击。它的短期机会在于收割对订阅制和软件臃肿不满的用户,但长期生存取决于能否在保持轻量的同时,建立起足够深且不可替代的专业性护城河。在IDE内置版本控制功能日益强大的今天,独立GUI客户端的生存空间,必须用极致的体验来捍卫。

查看原始信息
GitUX
Gitux Visual Git Made Simple A lightweight Git client. Beautiful commit graphs, intuitive staging, voice-powered commits, and keyboard shortcuts that make you fly. Try free for 4 weeks; no credit card, no account required.
Hi everyone, 6 months ago I got tired of paying €60/year for my git client, so I built GitUX. The fast, lightweight alternative I actually wanted to use. I started with SourceTree many years ago after SVN and a few others along the way, then got hooked with the ease of Gitkraken, but in later years fatigued with their cost and excess features that slowed everything on my machine down... started feeling like SVN projects again! I've been fine tuning GitUX for a few months and using it daily at work... until a colleague last month said I should get it out there maybe people will love it. I didn't want to turn this into yet another subscription thing, so it is just a generous 4 week free trial and a life time licence that does not cost the earth. Oh and no cloud account either! It will continue evolving and progressing over the years until I retire :) Hope you like it, thanks for reading, John
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Not a big fan of Gitkraken, so I am looking forward to trying this.

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@jon_manga still early days with GitUX so any feedback welcomed.

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Voice commits are unexpected! It sounds like a gimmick, but there are moments when your hands are busy with coffee and it could actually be useful 🙂 But the main thing for me is shortcuts. If I can stage files, write a message, and push without ever touching the mouse, I’m sold. Keyboard-first speed is what really matters

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Really interesting one!
Will def. check it out

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@lukasvanuden thanks, it is not ground breaking for sure, but it is the little things that count for me in tool like this. Small enhancements with keyboard shortcuts, search etc. Voice to text on commits (nice to half) helpful when nobody else is there to listen XD

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#19
Chores
Turn household chores into shared wins
21
一句话介绍:Chores 2是一款面向家庭的协作应用,通过清晰的界面、灵活的周期任务设置及奖励机制,将繁琐的家务管理转化为公平、积极的集体游戏,解决了家庭任务分配不均、动力不足和沟通摩擦的痛点。
iOS Productivity User Experience
家庭协作 家务管理 任务分配 激励机制 效率工具 iOS应用 生活管理 团队协作
用户评论摘要:用户反馈整体积极,认可产品概念与设计。有效评论主要集中于功能细节的询问,如是否支持为不同成员分配积分。开发者回复确认了个体化奖励功能。评论中未出现显著的批评或功能改进建议。
AI 锐评

Chores 2的本质,并非一个简单的任务清单,而是一个试图重构家庭内部微观权力与协作关系的“行为设计”工具。其真正价值在于将游戏化机制(积分、奖励)与家庭社会学洞察(公平感、减少唠叨)相结合,把容易引发矛盾的“责任分配”问题,包装成可量化、可激励的“共同成就”。

然而,其面临的挑战同样尖锐。首先,其核心逻辑建立在家庭成员持续参与和认可这套“积分体系”的基础上,这需要极高的初始共识和持续维护,应用可能沦为“家长的一厢情愿”。其次,从评论的稀少与浅层来看,产品尚未激发用户对其深层功能(如灵活的周期设置、周报)的深入探讨,可能意味着其价值主张的传达或需求的刚性仍有待市场检验。最后,在“家庭协作”这个细分赛道,它既要对抗简单至极的纸质便签,又要与功能泛化的智能家居平台或通讯工具竞争用户注意力,其“专业且简洁”的定位壁垒并不坚固。

技术栈(Laravel后端、实时同步)的选择体现了对可靠性与隐私的考量,这是家庭类产品的正确方向。但产品能否成功,远不止于技术实现,更在于它能否成为一个家庭习惯的“默认设置”,这需要超越工具本身,在用户心智和日常仪式感上构建更深层的护城河。目前看来,它提供了一个优雅的解决方案,但引爆点尚未清晰。

查看原始信息
Chores
Chores 2 introduces a complete redesign with a clean, modern interface built for the latest iOS. Enjoy an all-new onboarding flow, powerful recurrence options (like bi-weekly chores on specific days), and flexible individual or group rewards to boost motivation. Weekly household summary emails show what was completed and what’s coming up, while many under-the-hood improvements make everything faster, smoother, and more reliable.
👋 Hey PH! Frederik again, the maker of Chores 2. I built Chores because managing household tasks often turns into mental overhead, unfair distribution, and way too much nagging. Most tools feel either too simple or overly complex. I wanted something that feels calm, fair, and motivating something families actually enjoy using together. Chores 2 is a complete rethink: a fresh iOS-first design, flexible recurrence rules, group and individual rewards, and weekly summaries that help households reflect instead of react. On the tech side, Chores is powered by a Laravel backend with real-time syncing across households, focused on reliability and privacy. Excited to hear your thoughts, feedback, and ideas! Thanks for checking it out! 🙌 Frederik
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@frederik_jacques1 Congrats on the launch man!
It looks so clean!

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Great idea! Can you give points to different household members for doing chores?

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@daniele_packard Thanks man!

Yes, you can add individual rewards to people in your household.
Like in our family there is a chore “make your beds”, and all 3 of our kids get a point if they do it individually.

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Love the concept and best wishes for the app.

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#20
LifeSwap
AI wellbeing companion for overloaded minds
20
一句话介绍:LifeSwap是一款AI健康伴侣,为精神过载的现代人提供随时倾诉的AI伙伴、3分钟快速调节练习及情绪追踪,在碎片化时间中缓解日常压力与倦怠。
Android Health & Fitness Artificial Intelligence Lifestyle
心理健康 AI伴侣 正念冥想 压力管理 情绪追踪 微习惯 健康科技 数字疗法 生产力工具
用户评论摘要:用户反馈积极,认为产品设计体贴、实用性强,能有效缓解压力。开发者主动寻求关于功能引导清晰度、3分钟练习有效性及AI伦理的反馈。评论中未出现具体功能问题或改进建议。
AI 锐评

LifeSwap精准切入了一个被主流健康应用忽视的缝隙市场:为高负荷、快节奏的职场人提供“即时、微创”的情绪急救,而非系统性的治疗计划。其核心价值不在于技术突破,而在于对用户场景的深刻理解——将干预单元压缩至“3分钟”,这恰恰匹配了目标用户“连30分钟冥想都挤不出”的残酷现实。产品定位“非医疗设备”是明智的避责策略,但也凸显了其局限性:它更像一款数字化的“舒缓剂”,而非“解决方案”。

然而,其真正的挑战与风险也在于此。首先,“AI倾听者”的双刃剑效应明显:匿名倾诉的即时性固然是卖点,但AI在共情深度、危机识别和长期支持上的能力天花板,可能让用户在深度困扰中感到隔靴搔痒,甚至产生依赖而延误专业求助。其次,“微干预”模式虽降低了使用门槛,但如何证明其长期有效性、避免沦为另一个让人产生“未完成焦虑”的任务清单,是产品需要数据佐证的关键。最后,从评论看,社区反馈仍停留在礼貌性的鼓励层面,缺乏对功能、商业模式或隐私安全的尖锐质疑,这或许意味着产品尚未经历真实市场的严峻考验。

总体而言,LifeSwap是一次有价值的场景化创新,它抓住了“即时缓解”的强需求。但其长期成功,取决于能否在“轻量入口”与“有效产出”之间找到科学平衡,并建立起清晰的伦理边界,避免在敏感的精神健康领域成为一款精致的安慰剂。

查看原始信息
LifeSwap
LifeSwap is an AI-powered wellbeing companion for overloaded minds. Talk to a 24/7 AI listener, try 3‑minute resets (breathing, micro-meditations, focus tools), and track your mood over time. For everyday stress and burnout, not a medical device.
Hey Product Hunt 👋 I’m the builder of LifeSwap. I built it after hitting a wall with burnout and constant mental overload as a developer. I didn’t need another giant self-improvement plan — I needed a calm co-pilot that fit into the tiny moments of my day. LifeSwap is that co-pilot. - Talk – a 24/7 AI companion you can message when you’re spiraling or just need to vent. - Try – 3-minute “resets” (breathing, micro-meditations, focus tools) designed for quick breaks, not 30-minute sessions. - Track – mood trends over time, so you can see your emotional resilience grow in small steps. It’s for everyday stress, burnout, and mental load — not therapy or a medical device. Just a private, supportive space that’s always there when your brain feels crowded. Why I’m launching here So many people in this community are shipping, context-switching, and carrying a lot mentally. I wanted to build something practical for that reality: you open LifeSwap, take a 3-minute breather, and go back to your day a little less tense. If you decide to try it, I’d love feedback on: - How clear is the first session about what LifeSwap actually does? - Do the “3-minute reset” flows feel helpful or just like another task? - Any concerns around the way I’m using AI in a mental health context? Thanks for checking it out — and if you’re reading this while feeling overloaded, that’s exactly who I built LifeSwap for. 💚
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@tdum7 Great job, Theodor! The app is definitely on the right track.

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@tdum7 Great job, Theodor!

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@tdum7 congratulation! 👏

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Looks great! Congrats @tdum7 !

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@fredyandrei Thank you for feedback!!

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congrats on the launch!

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@toma_rares Thanks a lot!!

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Life Swap has become the kind of support I didn’t realize I needed all in one place. It’s helped me manage my stress levels, calm my anxiety, and find balance when I’m stuck in hyper-functioning mode.

I really love the idea of getting 1% better each day, it takes away the pressure of feeling like I need to heal overnight. Instead, it reminds me that progress can be gentle, realistic, and still meaningful. This approach has made such a positive difference in how I take care of my mental health.

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@luiza_anghel Thanks a lot!!

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Played with the app for like 1 hour and I love it. I feel better than before.

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This feels thoughtful rather than overwhelming. Not everything needs to be a deep session, sometimes a few quiet minutes are exactly enough

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