Product Hunt 每日热榜 2026-02-18

PH热榜 | 2026-02-18

#1
Sonnet 4.6
The most capable Sonnet model yet
480
一句话介绍:Claude Sonnet 4.6是一款高性能AI模型,在编程、知识工作及长文档处理等场景下,以接近顶级模型的智能水平但更经济的成本,解决了用户对高效、可靠AI助手的核心需求。
Artificial Intelligence
大型语言模型 AI助手 编程辅助 长上下文推理 智能体规划 知识工作 性价比升级 生产力工具 计算机使用 模型迭代
用户评论摘要:用户普遍认可其性能飞跃,特别是百万token上下文和接近Opus的智能水平。主要反馈集中在:肯定其编码和任务执行能力;认为价格虽值但仍偏高;期待更大幅度的降价;认为其正从对话工具转向生产力执行工具。
AI 锐评

Sonnet 4.6的发布,与其说是一次技术升级,不如说是Anthropic一次精准的市场卡位。其核心叙事“Opus级智能,Sonnet级价格”,直击当前企业及重度用户的最大痛点:在预算与性能间寻找平衡点。产品介绍中强调的“计算机使用技能”重大改进,以及评论中提及的“任务执行”焦点,清晰地揭示了Claude的战略转向——从“思考的伙伴”变为“干活的员工”,正式杀入个人与企业生产力核心腹地。

然而,光环之下亦有隐忧。用户对“价格差异很小”的抱怨,暴露出在激烈竞争中,单纯“性价比”故事的边际效应正在递减。当竞争对手可能以更激进的定价或更垂直的优化袭来时,Sonnet 4.6的全能升级路线能否持续赢得市场,需要打上一个问号。此外,其将部分工作流导向如n8n等外部工具以控制成本的用户实践,也微妙地揭示了当前大模型服务在复杂、长周期任务中仍面临token消耗不可控的固有挑战。

总体而言,Sonnet 4.6是一次强有力的迭代,它巩固了Anthropic在第二梯队的领先地位,并对领头羊形成了切实的压力。但它也标志着,大模型竞争已从炫技式的基准竞赛,进入了刺刀见红的实用化、成本与效率精细平衡的新阶段。真正的赢家,将是能真正将“智能”无缝转化为稳定、可预测“产出”的平台。

查看原始信息
Sonnet 4.6
Claude Sonnet 4.6 is a full upgrade across coding, computer use, long-context reasoning, agent planning, knowledge work, and design. It also features a 1M token context window in beta. Sonnet 4.6 has improved on benchmarks across the board. It approaches Opus-level intelligence at a price point that makes it practical for far more tasks. It also shows a major improvement in computer use skills.

Pro tip: @v0 by Vercel Pro is now powered by @Sonnet 4.6 - "The power of Opus 4.5 at lower cost."

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Claude Sonnet 4.6 is a massive step forward — the 1M token context window alone is a game changer for long-document workflows. What really stands out is that Anthropic is closing the gap with Opus-level intelligence at a much more practical price point. Coding, reasoning, and computer use all feel noticeably sharper. Congrats to the Anthropic team on another strong launch 🚀

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The price difference feels very small. I wish they cut down costs a bit for Sonnet.

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@peter_albert2 Same, but it does what they say it does. Haven't had any errors in months. The price is worth it, doesn't mean its not expensive because it is haha. Offloading some code tasks to n8n to stabilize token hemorrhaging.

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Obvious winner!

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I was hopping a lot between AI models the past couple years, but after I found Sonnet a few months ago, I really have never looked back. Personally it is by far the best model for me, makes working on code a breeze.

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Super interesting to see the focus on task execution in the launch materials for this one — definitely moving Claude into the personal productivity space (i.e. to be used to "execute work") rather than just a conversational sidekick...!

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It's a strong model and Anthropic is really winning right now after their recent Opus release. I am wondering what OpenAI is up to. Do they still exist?

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Big congrats on the launch! 🎉

Sonnet 4.6 looks like a huge step forward - love the focus on real task execution. Excited to try it out!

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Claude has been a game changer when it comes to development with Stellify. A year ago I wouldn't have been able to imagine the progress that we've made.

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Always quality from Anthropic. Great model!

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#2
Moda
Finally, AI designs you can edit
417
一句话介绍:Moda是一款AI驱动的品牌化设计工具,通过提供分层可编辑的画布,解决了用户在快速产出营销材料、演示文稿等内容时难以保持品牌一致性和进行精细调整的痛点。
Productivity Design Graphic Design
AI设计工具 品牌视觉管理 可编辑画布 演示文稿制作 营销素材 图形设计AI 企业级设计 内容创作 设计协作 智能排版
用户评论摘要:用户高度认可其“分层可编辑”的核心差异点,认为解决了AI生成设计只能“重头再来”的痛点。主要问题与建议集中在:需加强数据/上下文理解能力;需完善与PPT、Figma等工具的导入导出兼容性;并期待其向UI/UX设计和代码生成领域拓展。
AI 锐评

Moda的亮相,与其说是又一个AI设计工具,不如说是一次对当前AI内容生成“黑箱”与“不可控”现状的精准反击。其真正的价值不在于“生成”,而在于“生成后的主权归还”。市面上多数AI工具止步于输出一张精美的“图片”,用户若想调整,只能重新祈祷提示词的有效性,陷入低效循环。Moda自研WebGPU画布并构建“有品味”的设计智能体,本质是构建了一个人机协同的“设计沙盒”——AI负责提供符合品牌规范与美学的基础方案,人类则保留最终、最细微的编辑控制权。

这直击了企业内容生产中最隐秘的成本:品牌资产的稀释与管理损耗。它试图解决的,并非“从无到有”,而是“从有到优且一致”。早期用户反馈的“取代承包商”、“迁移Canva”已初步验证其价值主张。然而,其挑战同样清晰:首先,技术层面,“品味”作为约束条件如何持续标准化并适应多样品牌?这或是其护城河,也是易碎点。其次,生态层面,能否无缝嵌入以Figma、Office套件为主导的现有工作流,将决定其是成为独立生产力平台,还是仅为补充工具。最后,其“设计智能体”的定位,若不能向理解业务数据与逻辑的“内容协同者”进化,则可能被更垂直、更懂业务的AI应用所分流。Moda的赛道正确,但长跑才刚刚开始。

查看原始信息
Moda
Moda helps you design beautiful, brand-aligned content - slides, posters, ads, and more - with an AI trained in graphic design. Unlike other AI tools, everything is fully editable on a powerful layered canvas.

Hi 👋

I'm Anvisha, and this is my third time launching on PH: I built @Slab (#1 Product of the Week) and @Dover (#2 Product of the Day). This one's the most personal.

I've always been obsessive about design. At my previous startup, even at 100+ people, I was still in design files, tweaking spacing and fixing colors.

Brand is the first thing people notice, and the fastest thing to get diluted when you're churning out content. Especially without an in-house designer.

AI was supposed to fix this. Instead, it made it worse. ChatGPT and Nano Banana can make pretty images, but the outputs aren't brand-aligned, and you can't directly tweak it.

So we did something that most teams wouldn't attempt.

We built a powerful WebGPU canvas from scratch, engineered from the ground up for people and agents to work together. Then we taught an agent layout, typography, and color. We taught it taste.

Moda is a brand-aligned design agent that produced fully editable designs with layers on a canvas that you control.

⚡ What people are making:

  • Pitch decks, QBR and sales slides

  • LinkedIn and Instagram posts with animations

  • Sales collateral and one-pagers

  • Ads, UI mockups, even printed large-format designs for booths and live events

💬 Early users say Moda already beats Canva, Gamma, and dedicated contractors:

"Moda has democratized branded asset creation for our entire go-to-market org. It's saving us time and money compared to agencies." - Chief of Staff, Series B startup

"I have Canva, I've tried Gamma and other AI tools. Moda is just easier. I made an Instagram carousel in minutes and it was beautiful." - Mortgage broker

"We moved off Canva and haven't looked back." - CEO, seed startup

🎁 Free to start. Every account gets 1000 AI credits - enough to create dozens of assets. Use code PRODUCTHUNT for an extra 500 on us.

Over the past few months, we've onboarded hundreds of people from our waitlist and we're just getting started. Our vision is a world where anyone can produce work that looks and feels like it came from a world-class design team, in minutes, not days.

We'd love for you to try Moda and tell us what you think 🙏

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@anvisha_pai  will definitely check this out! Have been looking for something like this!

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@anvisha_pai Flattened outputs are where design gen falls apart. Moda building a WebGPU canvas you can actually edit, plus an agent that understands layout, typography, and color, feels like a better path than prompt-only generators or template libraries. If the brand kit is treated as hard constraints, you get fast iteration without the export and rebuild loop. That's what keeps brand from drifting.

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@anvisha_pai I'm curious how the "taste" layer works. Is it a custom fine tuned LLM or more of a rules based engine for the layout?

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@anvisha_pai Congratulations. And happy product launch.

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@huisong_li thanks!

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Finally, an AI design tool that doesn't just give me a flat image! As an HR professional, I love the ability to tweak every layer. However, the next frontier for Moda should be better data-grounding.. We need the AI to be as smart with our provided info as it is with the layout. Great launch, team—this is a huge step forward for editable AI!

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@soubangi_rajkhowa thank you! a lot of early users have been using Moda for personalized HR letters, all hands decks, etc so I totally agree.

The next frontier is gathering more context and helping you with more than just design. Stay tuned!

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A lot of teams live and die by compatibility: how are you approaching exports/imports (PPTX, PDF, images, maybe Figma/Canva workflows), and what quality bar do you need to hit before you’d call Moda viable for customer-facing decks and collateral?
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@curiouskitty this question really gets at core questions we’re asking ourselves as well. First-off, we’ve already had early partners that are currently using Moda for client-facing decks! But anyone who has ever built an editor knows there are always more bugs, feature requests, and file types to be compatible with.

The team has put a lot of

time into testing and developing PPTX, GSlides, and Keynote both for import and export and our compatibility continues to get better. We also export PDF and import SVG, which hits some Figma use cases. Try it out yourself and tell us which features you need before it’s ready for your needs!

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@curiouskitty what @steven_frieson said! Hundreds of users tried Moda during our closed beta

  • One Series B's startups entire GTM team replaced contractors w Moda

  • Multiple companies printed 6 ft+ posters for recruiting events

  • Someone ran their first account-based marketing campaign

  • A company already migrated off Canva

You can see more stories in the testimonials section on our website :)

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Great! Can I edit both ways: with prompts and manually? Are design elements also editable or text only?

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@alina_petrova3 Yes you can! We were so tired of image gen getting so close but not close enough , and a new prompt being inefficient and cumbersome, so we made an agent that makes 100% editable designs. If you want to make a small copy tweak go for it! if you want to move around layers you can. Added bonus: the agent’s edits can be just as fine-grained as yours. No more starting over from zero with every prompt.

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@alina_petrova3 As Steven said everything is editable in the canvas. You can resize shapes, edit text, change colors, drag images into the canvas from your desktop, etc. Everything you'd expect from a full-featured editor!

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As a marketer, I’ve been using AI for landing pages visual and social media content for a while, and Nano Banana has always been my go-to for quality, but I was always wishing I could just 'tweak one little thing' without a total reroll or reprompt. Seeing direct canvas editing here is a game-changer for me. Huge congrats on the launch—going to put this to the test right now!

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@pidsinee_einarsdottir the total reroll is so painful! That was one of the first problems we wanted to solve. Excited to hear what you think.

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@pidsinee_einarsdottir yes, that's 100% the pain point we wanted to solve. Nano Banana and other image models are great but they give you a raster output that's not editable unless you re-prompt, and then you rarely get exactly what you want when you do that!

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so excited to see this out in the world - my all hands decks won’t know what hit ‘em ✨💃
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@b_nick can't wait for you to try it!

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@b_nick thanks! very much looking for feedback on the slide import/export flows, so keep us posted!

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Moda is amazing! I've been a beta tester for the past two months and it's honestly helped so much with my customer-facing presentations. Moda is a life saver!

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@carissajansen thank you!! 🙌 So happy Moda’s been helping with customer-facing decks — what kind of presentations are you making most often?

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@carissajansen Thank you Carissa!

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@Moda Classic example of understanding a problem and building a product to resolve it. Fantastic work by the entire team. Will definitely take it out for a spin

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@tanoy27 we've lived the pain 🫡

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@tanoy27 Let us know what you think once you've had a chance to use it!

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Congrats on the launch! So exciting to see it live, the experience feels really intuitive.

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@alanka Thank you! Glad to hear you like it!

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@alanka Greatly appreciated!

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Congrats on the launch, Team! 🎉

Love the focus on brand-aligned, fully editable designs - this feels like the AI design tool teams actually need.

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@rohithreddy Yes exactly - we built this for ourselves, the pain point we've faced so many times.

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deck city

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@maxkolysh Yes, exactly!

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Congrats on the launch! I just tested it out, and the interface is really smooth. The video demonstration was super helpful for seeing how the layers actually work in real time. Great job! 🙌

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@alina_anitei Glad the demo video helped out. There are plenty more to come as we keep shipping new features.

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@alina_anitei thanks so much! 🙌 if anything in the video or UI felt confusing / could be clearer, we’d love to hear it — even small notes help a ton.

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@anvisha_pai Congrats! There's a strong need for this in the market. I wonder if I can do UI/UX work with Moda and use the output with agentic coders like Claude Code or Codex so I can transform the design into code?

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@anvisha_pai  @ahmetardal Yes, absolutely. We use Moda for this ourselves internally - mock up UI in there, and then right now we export to PNG and just share the image with Claude Code. That is obviously not perfect, so we're working on an MCP that would let Claude (or any agent) just observe the design directly so it can make pixel-perfect designs. This is something WE want to use ourselves so it's definitely high on the feature priority list!

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@ahmetardal a LOT of people have been asking us for this

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Fire y'all...congrats.

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@thekidsprinkles Thank you so much!

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Editable canvas is great. Do you support .odp?

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@ben_frank3 We haven't gotten to .odp yet, but we do have .pptx. Are you looking for import, export, or both?

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A great tool! I will definitely use it. Right now, I need to create some advertising materials based on existing ones, and it looks like moda.app will do the trick! ;-)

Is it beginner-friendly? What documentation or tutorials do you have?

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@christo_tsvetanov That sounds like a great use case. It's definitely made to be beginner-friendly. There's a tutorial video on the homepage after you sign up before you create any projects.

You have two main options for your case though. You can create a brand kit by uploading your existing materials if you're going to keep going back to the same set for inspiration or you can easily drop your files into the chat as references for the agent.

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curious to test it. just wonder - does it have integration with Figma?

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@tonya_snezh No integration with Figma yet, but we've definitely imagined some use cases where it'd be helpful. What did you have in mind?

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@tonya_snezh A couple other folks have requested a Figma integration so we'll likely prioritize it soon! Let us know what you're looking for (import, export, something else?)

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Congrats @anvisha @jhh3 and team! This is awesome. Product is super impressive and easy to use, already running low on credits : )

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#3
Omnia
Become the brand AI recommends
250
一句话介绍:Omnia是一款AI可见性工具,通过分析AI如何认知品牌、提供实时提示词洞察和内容优化建议,帮助企业在AI搜索时代提升品牌曝光,解决品牌在AI推荐中“失声”的核心痛点。
Marketing Growth Hacking SEO
AI可见性工具 GEO优化 品牌监控 竞品基准分析 AI搜索优化 内容策略 B2B SaaS 营销科技 智能推荐分析
用户评论摘要:用户反馈积极,认可AI可见性新赛道。主要问题集中在:GEO策略如何应对LLM快速迭代的挑战、数据来源是否涉及用户隐私、定价与试用策略、以及工具与内容生成工作流的整合。创始人回应将推出代理平台与更深度集成。
AI 锐评

Omnia切入的“GEO”(生成引擎优化)赛道,本质是试图在AI原生搜索时代,成为新一代的“SEO”工具。其价值主张犀利地戳中了品牌方的集体焦虑:当消费决策入口从搜索引擎转向ChatGPT等对话式AI时,传统的SEO策略近乎失效。产品试图通过逆向工程AI的推荐模式,为品牌提供一套新的“游戏规则”。

然而,其面临的挑战远比当年的SEO更为严峻。核心在于LLM的不透明性与快速迭代性。正如用户质疑的,谷歌的排名算法相对稳定,而大模型的输出逻辑、知识库和偏好可能随一次更新而剧变,这使得任何基于当前模型分析的“优化策略”都可能迅速过时。Omnia试图用“统计性真实”的提示词模拟来构建洞察,这虽能缓解数据来源问题,但本质上仍是一种间接推测,与直接获取用户真实提问数据相比,存在精度鸿沟。

其真正的护城河可能不在于监测,而在于其宣称的“行动优先”与“代理平台”方向。若能深度集成到企业内容生产与分发工作流中,实现基于AI洞察的自动内容优化与部署,将工具从“仪表盘”升级为“智能体”,则可能创造不可替代的粘性。目前来看,它成功定义了一个紧迫且真实的需求,但技术壁垒与策略的长期有效性,将是其从早期概念验证走向规模化必须跨越的两座大山。市场需要的不只是一个监测工具,而是一个能持续适应AI进化节奏的动态优化系统。

查看原始信息
Omnia
Omnia is an AI visibility tool that shows how AI sees your brand and helps you take action. Discover real AI prompts, monitor brand presence, benchmark competitors, and create content that boosts visibility and citations in AI search.
Hey Product Hunt! 👋 I'm Dani, Founder of Omnia. A little over a year ago I was running Klarna in Spain as General Manager. I loved what I was building there, but somewhere along the way, I had a moment of clarity: if I'm researching most of the products I buy with AI, my customers must be doing the same. That was it. The insight I couldn't unsee. Every brand in the world has the same problem now: *how do you show up when your customer asks an AI?* SEO took decades to figure out. GEO is being written right now — and most brands don't even know the game has changed. So I left Klarna and started Omnia. Omnia lets you monitor the prompts and topics that matter most to your customers, understand the patterns AI engines use to recommend brands, and create content so that *your brand* is what people see when they ask AI. We're still building (plenty features more in the oven), but we wanted to share where we are today so brands can start improving their GEO position right now. Happy to answer anything. What's your biggest challenge with AI visibility? 👇
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@danimirror Hey Dani, quick thought .. SEO worked because Google had stable ranking mechanics. LLMs change rapidly and are less transparent. How does GEO avoid becoming a moving target that resets every model update?

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@danimirror The way the tool is more customer-focused makes it stand out. Congrats on the launch!

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@danimirror congrats on the launch! 🚀 Are you prioritizing B2C or B2B? Have you seen success on both?
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That's a really new trouble for business owners. Do you have access to OpenAI users' requests? Can you track what users ask in chatgpt, for example?

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Hey @olya_vasilevskaya !
thanks for the comment :D


We don't have access to OpenAI user's request (nobody does except them). We replicate the users' questions by asking daily and with different prompts to the AI engines (in this case to ChatGPT), so we reach a statistically true.

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Congrats on the launch @danimirror!

What’s been the biggest “aha moment” so far when working with customers?

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@gulipad Thank you! We're excited!

We’ve had a couple of really cool ones, but the one that caught our attention the most is the case of INDYA, a SaaS for nutritionists that grew from position 11 to position 2 across several prompts in less than a week by implementing the insights provided by Omnia.

In fact, you can find the full case study here

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This is such a great product, congrats on the launch!

I think having a connector to automated article generation could be a game changer for this.

Is it in scope?

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Hey @rogarmu8 !
Yes, it is! It will be here soon!

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Many teams worry AI answers won’t drive clicks the way SEO did—how do you recommend customers define success (KPIs) for GEO, and what’s a realistic timeframe to see meaningful business impact?
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Hey kitty! @curiouskitty 

The best KPI's a team can define are:

  • Share of Voice

  • Visibility

  • Mentions

The timeframe to see impact depends of the industry and the company, but we are seeing high impact in days, like with this case

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Congrats Omnia team! Obsessed with playing with the new string in your marketing site hero haha!

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Thanks! @rebeccahpearson 


We love it too :)

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@danimirror Really interesting space – AI visibility is becoming the new SEO conversation. 🙂 The framing around "the game has changed" feels very true right now.

I’ve been seeing quite a few tools emerging around "how AI sees your brand", so I’m genuinely curious: how do you think about differentiation in this category? Is Omnia’s edge more in the prompt discovery layer, the monitoring depth, or in the content recommendations side?

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hi @tereza_hurtova !

Very good one :)

Omnia is a action-first tool, we are focusing on recommendations by insights and content (in the next release) to be very accurate to the content we offer to the customers.

Also, we're an agentic platform, we will launch soon the MCP too, so you'll be able to apply all the intelligence residing within Omnia to your day a day workflow.

Thanks for asking!

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What does the product look like today vs what you thought you were building on day one?

Congrats on the launch! @danimirror

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Hey@miguel_beltran_sanchez !

It has changed a lot!

We're redesigning a lot of features, and releasing others almost every week!

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Awesome Daniel! It sounds great man. Researching through AI is saving a lot of time and energy. It’s so smart and I feel most of the founders here are gonna take the most of it

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Amazing team and product - congrats on the launch @danimirror and @miguelff !

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thanks Jorge!!

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Interesting direction — AI visibility will only get more important. Congrats on shipping!

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Thanks for the comment@andrzej_pacholik !

Yes, we think so, all in with Omnia :D !

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Congrats Omnia team!

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Thank you a lot! @benln 

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It's quite expensive, and you have to link your card right away without knowing whether you'll use the service or not. In my opinion, a 1-2 day trial is enough to understand whether you need such a service or not.

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Congrats on the launch, Team! 🚀

GEO is such a timely space - love the focus on helping brands show up in AI answers.

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Great product - congratulations on the launch.

Any particular target user you are focused on?

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Hey @danimirror Congrats on the launch! AI visibility is definitely something brands should be focusing on. I have a few questions, hope you can help me understanding it.

  • In the video, the suggestion is to add a VEGAN attribute to the SKU. If I run my ecommerce website on Shopify, for example, would the tool update my product's data and add those attributes for me if I click on "Use Created Content"?

  • Curious to understand more about the Search Trend feature: is it calculated using real conversation data searched by actual users, or other traditional search intent data?

Thank you and congrats again!

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Regarding the content creation feature, does Omnia generate fully written articles optimized for LLM training data, or does it provide briefs for our copywriters to execute manually?

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@valeriia_kuna 

Eventually, we will give the user both options :) . At the end o the day, there will be always a human in the loop.

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We currently use AI visibility reports in Amplitude. How do you compare it to your product?

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Hey @vasilbo !

Our platform is built around what brands can actually do to improve their presence, and we provide specific, actionable recommendations tailored to their brand based on what they’re monitoring. Also you have a 14 day trial, so you can check it out :)

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Hey @danimirror . Congratulations on your launch. Your product is very intriguing. I just tried it and I have one question:

Where are the information about the user prompts coming from? I see some weird prompts that don't sound like real user questions. For example: In the screenshot (sorry, it's german) you see a question "What microphone is the best for newbies in the year 2026?" I really can't imagine someone would ask for a specific year.

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hey @kay_siegert ! Thanks a lot for trying it out and for the great question 🙌

The prompts in Omnia Trends are trend estimations, not exact copies of a single user query. They reflect what’s most searched/asked across AI tools.

Since only platforms like OpenAI, Perplexity or Google have full access to raw data, our Trends data are estimated using:

  • A dataset of real customer prompts (via a Chrome extension)

  • SEO data

  • Social listening across platforms

So something like “best microphone for beginners in 2026” reflects how users often phrase timely, future-oriented queries.

While volumes and difficulty scores aren’t perfect, they’re highly accurate and very useful for deciding what to optimize for.

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How often do you monitor?

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Hey@juan_ros , thanks for asking!

We monitor at least daily. Sometimes if the monitoring data doesn’t converge (because LLMs are non deterministic by nature) we start monitoring more frequently until the data converges (basically until we find the statistical truth).

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#4
Flixier Generate AI Video in Timeline
Extend shots, connect clips, generate from any frame
172
一句话介绍:Flixier 将AI视频生成直接集成到编辑时间轴中,解决了创作者在多个工具间反复导出、拼接AI生成片段,难以高效完成视频成品的核心痛点。
Artificial Intelligence Video
AI视频生成 视频编辑 一体化工作流 时间轴编辑 AI视频剪辑 内容创作工具 生产力工具 云端视频制作
用户评论摘要:用户普遍认可“AI融入时间轴”的理念,认为其解决了“AI片段坟场”问题,让实验和成片流程无缝衔接。核心建议/问题包括:重生成片段如何影响已编辑时间轴、AI能否理解并保持多片段间的叙事连贯性、以及希望增加版本对比功能以安全迭代。
AI 锐评

Flixier 的发布,与其说是一次功能更新,不如说是对当前喧嚣的AI视频生成赛道一次冷静的“工作流纠偏”。它敏锐地刺破了一个行业泡沫:许多工具沉迷于生成单段“惊艳”片段,却将最耗时、最决定成果的剪辑、衔接与润色工作粗暴地抛回给传统工作流,本质上只是制造了更多的数字废料。

其真正价值不在于生成质量可能超越顶尖模型,而在于“空间锁定”——它将生成、扩展、连接等AI动作全部禁锢在唯一的生产环境“时间轴”内。这强行改变了用户与AI的协作心智:从“生成-评判-导出”的离散消费模式,转变为“生成-调整-延伸-整合”的连续构建模式。用户评论中“更愿意实验”的反馈,恰恰印证了其降低了创作的心理成本与操作断层,将AI从“魔术盒”工具还原为“编辑助手”角色。

然而,其面临的挑战同样深刻。首先,技术层面,如何确保在时间轴上对AI片段进行“修剪后重新生成”等操作时,能保持上下文一致性而非引入逻辑混乱,是工程难题。其次,产品逻辑上,“在时间轴内生成”固然流畅,但AI对跨片段叙事逻辑的理解是否跟得上,决定了它能否从“片段缝合器”升级为“故事辅助者”。当前它解决的仍是效率与流程问题,并未触及创作智能的核心。Flixier 的成功,将取决于它能否在“流畅工作流”的基础上,真正深化时间轴内AI的上下文感知与协同编辑能力,否则可能仅成为优秀的工作流整合者,而非颠覆性的创作范式定义者。

查看原始信息
Flixier Generate AI Video in Timeline
Most AI video tools stop at generation. Flixier brings AI into the editing timeline, so you can generate, extend, and connect clips, trim, polish and finish videos in one place, without exporting or rebuilding elsewhere.

Hello Product Hunt 👋


AI video generation is everywhere right now: New models, better outputs, faster generation cycles.


But most of these tools are built around a single moment: the clip.


You generate something impressive… and that’s where the product ends.


There’s no real place to keep building. No continuity. No timeline where the video actually comes together.

If you want to turn that output into something publishable, you have to export it and start assembling the rest elsewhere.


We think that’s backwards.


Videos aren’t one-shot results. They’re built through iteration, extension, and connection between clips. That only works if AI lives inside the timeline


So we moved generation into the editor itself.


In Flixier, you can generate, extend, and connect clips directly inside a real timeline, then shape, add context, and finish the video without restarting the workflow.


AI clips are easy. Finishing videos is the hard part.


Give it a try and let me know if building inside the timeline feels different from the usual generate–export–rebuild loop.


Paul
Co-founder, Flixier

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@pruscior congrats!

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@pruscior What happens to downstream edits if you regenerate an extended or connected clip in Flixier after you've already trimmed the timeline? Generate from any frame is powerful, but it only stays usable if the prompt, reference frame, and model version stay attached to each clip. A quick compare between takes would make iteration feel safe.

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@pruscior Love the “AI inside the timeline” framing. Curious how Flixier handles narrative continuity across multiple generated clips, does the model retain story context between timeline segments, or is each generation still somewhat independent?

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Good luck on your launch Flixier team!

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@levent_askan Thank you, and we are excited to get this in front of the PH community. Bringing AI video generation directly into the timeline felt like the right next step.

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Love it!

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@osman_kocs that’s great to hear!

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proud to be a part of this launch! it's the only AI video generation tool that allows its users to generate, extend and connect AI clips without leaving their timeline.

big kudos to the dev team!

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As someone who actually posts regularly, the “AI clip graveyard” is real.

You generate 10 things. Maybe 2 are good. But stitching them into something coherent usually means switching tools, exporting everything, and basically starting again. That break in flow almost always crushes my momentum.

What’s genuinely changed for me with the new timeline-based generation setup is that I don’t have to leave. I can test ideas across different models, pull the best clips straight into a real editing timeline, trim, re-sequence, add voice or text, and actually shape something into a finished piece. All without having a hundred tabs open.

It sounds small, but it makes me far more willing to experiment! Because I know the outputs won’t just sit in a folder. They can actually become a video.

That’s been the practical shift for me.

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That fear of ending up with a folder full of almost-useful clips is exactly what we were trying to remove. We really wanted experimentation to feel safe, knowing you can actually turn it into a finished video.

Thank you @cam_strive , for putting this into words so clearly.

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Loving the new AI generation updates directly into the timeline! 🚀

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@cretueusebiu really glad to hear that!

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Congrats on the launch Paul

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@otodidakt_20 thanks, really appreciate the support.

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Improve, improve, improve ... Nice

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@razvan_girmacea1 Thanks a lot for supporting us since the early days!!!

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Congrats on the launch, Team! 🚀

Putting AI directly in the timeline just makes sense. Love the focus on actually finishing videos, not just generating clips.

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Without restarting the workflow? This has got to be THE tool, then. Congrats on the launch, @pruscior !

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@neilverma Exactly, no restarts, no jumping between tools. Everything stays in the timeline where you're already working. Thanks, glad it landed!

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#5
ClawMetry for OpenClaw
Real-time observability dashboard for OpenClaw AI agents
143
一句话介绍:一款为OpenClaw AI智能体打造的开源实时观测仪表盘,解决了开发者在复杂多智能体工作流中“黑盒”操作、难以调试和成本不透明的核心痛点。
Open Source Developer Tools Artificial Intelligence
AI可观测性 智能体监控 开源仪表盘 实时可视化 成本分析 运维调试 开发工具 OpenClaw生态
用户评论摘要:用户普遍认可其解决AI智能体“黑盒”问题的价值,认为对开发者至关重要。主要建议与问题集中在如何更精细地追踪智能体链式调用与后续动作的决策过程,开发者已回应具备相关追踪功能并邀请反馈。
AI 锐评

ClawMetry瞄准了一个正在爆发的刚需市场:AI智能体,尤其是多智能体系统的可观测性。它并非简单的日志聚合器,其真正价值在于将“Grafana”的理念引入AI工作流,试图将智能体内部离散的“思考”、工具调用、子智能体派遣等动作,转化为可实时监控、可追溯因果的数据流。

当前AI应用开发,尤其是基于OpenClaw这类框架,正陷入一个矛盾:智能体能力越强、工作流越复杂,其内部决策过程就越像一座迷宫。开发者如同“盲人摸象”,仅能通过最终输出结果反向猜测问题所在,调试效率极低。ClawMetry直击这一痛点,提供从成本、系统健康到会话历史的全局视角,其“实时流程可视化”是区别于传统日志的核心利器,旨在将不可见的推理过程变为可见的交互图表。

然而,其挑战与机遇并存。首先,其生态绑定性强,深度依赖OpenClaw,这既是精准切入,也是增长天花板。其次,评论中关于“链式调用追踪”的提问切中要害,这恰恰是AI智能体调试最复杂的部分——问题可能不在单步执行,而在逻辑链的传递偏差。产品虽已回应,但证明其追踪的“上下文”是否足够直观、能否定位到语义层面的错误,将是衡量其专业深度的关键。最后,“零配置”降低了使用门槛,但面对千差万别的智能体任务与自定义工具,如何保持足够的扩展性和灵活性,避免沦为“玩具仪表盘”,是后续发展的考验。

总体而言,ClawMetry在正确的时间点,提出了一个正确的解决方案原型。它能否从一款优秀的开源工具,演进为AI智能体时代不可或缺的调试标准,取决于其在对复杂工作流的深度洞察、跨平台适配以及构建开放生态上的进展。

查看原始信息
ClawMetry for OpenClaw
ClawMetry is a free, open-source observability dashboard for OpenClaw AI agents. Think Grafana, but purpose-built for AI. One command install (pip install clawmetry), zero config. Monitor token costs, sub-agent activity, cron jobs, memory changes, and session history. All in real-time with a beautiful live flow visualization. Works on macOS, Linux, Windows, even Raspberry Pi
Introducing ClawMetry for OpenClaw 🚀 I built an real-time observability dashboard for OpenClaw AI agents. Here's why. You send a message in your Telegram / WhatsApp to do some work & the agent says "spawning sub-agent" and you just... hope it works? You shouldn't have to. So I built ClawMetry. See what every sub-agent is doing. Right now. What files it's reading, what commands it's running, what tools it's calling, what it's thinking. Summary, narrative, full logs. No more guessing. System health at a glance. Cron jobs, service uptime, disk usage, active sub-agents. All in one view. Session history. Every session logged with a timeline, tool calls, and cost. Go back and see exactly what happened. Cost breakdown. Per-session, per-model, per-tool. Know what you're spending before the invoice shows up. It's open source, installs in 30 seconds: pip install clawmetry One line in your OpenClaw config, and you get a full dashboard. If you're building with AI agents, you need visibility. Not more logs, actual observability. clawmetry.com
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Congrats on the launch 🚀

Finally, real visibility into what agents are actually doing. Super useful for anyone building with OpenClaw.

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@rohithreddy Thank you Rohith! That means a lot. Visibility into what the agent is doing was the #1 thing I was missing when I started building with OpenClaw, so I built it. Glad it resonates. Would love to hear how you use it with your setup!

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Observability for AI agents is something most builders overlook until things break in production. Love that you're tackling this early. How do you handle tracing when agents make multiple chained calls? In my experience building database agents, the hardest part to debug is when the agent interprets a query correctly but chains the wrong follow-up action. Clean dashboards for that would be a game changer.

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@saezbaldo Great question, Damian. Tracing chained agent calls is exactly where most logging tools fall short.

ClawMetry tracks every tool call, sub-agent spawn, and session handoff with full context. So when agent A calls agent B which queries a database and picks the wrong follow-up, you can trace the entire chain: what each agent saw, what it decided, and where it went wrong.

The cron management dashboard also helps here. You can see scheduled tasks, their run history, and drill into individual executions. No more guessing which step broke.

We're actively building deeper tracing for multi-agent workflows. Would love your feedback if you try it out: pip install clawmetry and you're up in 30 seconds.

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#6
Travel Animator
Name every stop your way with Place Labels
129
一句话介绍:Travel Animator 通过创新的“地点标签”功能,在用户制作旅行轨迹动画视频时,解决了路线展示不清、缺乏个人化叙事的痛点,让旅程回顾更清晰、更有故事性。
Travel Maps Video
旅行视频制作 地图动画 个性化标签 社交媒体内容 旅程可视化 用户生成内容 创意工具 移动应用
用户评论摘要:用户反馈积极,认可其核心动画效果并认为应用直接易用。主要建议集中在希望集成到CapCut等主流剪辑软件,以及确认了多种视频导出比例的支持。有评论深入探讨了标签模式的设计逻辑与取舍。
AI 锐评

Travel Animator 捕捉到了一个精妙的用户需求缝隙:将冰冷的GPS轨迹转化为有温度、可阅读的视觉叙事。其“地点标签”功能看似是简单的标注,实则是将“数据可视化”与“情感表达”进行了一次轻量级融合,旨在解决社交媒体上旅行视频“观众看不懂路线”的核心传播障碍。

然而,产品目前呈现出一种“功能驱动”而非“体验或生态驱动”的典型工具思维。从开发者在评论中“没多想约束与取舍”的坦诚回答可见,其设计哲学更偏向快速响应用户表面需求(如提供多种颜色和模式),而非构建一个深思熟虑的视觉叙事体系。这导致其价值天花板清晰可见——它是一个优秀的、功能具体的特效插件,但难以成为一个独立的创作平台。

用户的评论也印证了这一点:人们因其标志性的“移动小车”动画而来,并希望将其效果导出到更专业的视频流中。这暗示了其最终归宿可能并非独立App,而是作为效果插件或模板集成到CapCut、Instagram Reels等现有内容生态里,才能最大化其效用。它的真正挑战不在于添加更多标签样式,而在于如何深度绑定社交视频的生产与传播链条,从“一个有趣的工具”进化成“一种流行的视觉语言”。

查看原始信息
Travel Animator
Place Labels are here ✨ Now you can highlight the places you’ve visited right on your animated map, helping every route feel clearer, more personal, and easier to follow. With the new Place Label Customiser, you can choose from 6 thoughtfully designed styles, explore 7 colors to match your mood, and decide how labels appear with Current, Visited, or Always-on modes. Edit or remove them anytime. Tell your journey your way 🚀

I sometimes saw reels in the past with this car riding around and I always wondered what app that would be. Finally found it out lol it's TravelAnimator. Cool project

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Wow and it's also straightforward to use. I really like it

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I would wish to have this in some apps like CapCut or so. Or the option to export it for videos in landscape or portrait. Do you have it like that?

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@busmark_w_nika Yes you could export videos in 1:1, 9:16 or 16:9 aspect ratios.

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This looks awesome! 😍 Can’t wait to try it for my trips.

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@rohithreddy Thanks

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Place Labels seem aimed at solving the ‘viewers get lost’ problem—how did you decide on the label modes (Current/Visited/Always) and style constraints, and what tradeoffs did you make between full design freedom and keeping results consistently legible?
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@curiouskitty This was a user-demanded feature that was just waiting to be executed.

As for the constraints and trade-offs, to be honest, we didn't think much about them.

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Finally found this app that does those effects. Congrats on the launch@angell019!

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@angell019  @neilverma Thank you.

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#7
Empirical Health for web
Comprehensive preventive heart health solution scaled w/ AI
119
一句话介绍:Empirical Health 提供基于AI的综合性预防性心脏健康解决方案,通过网页版让用户能在更大屏幕上便捷查看超过100项生物标志物的血液检测报告、评估心脏病发作风险、与医疗团队沟通,解决了用户在桌面端深度分析复杂健康数据、进行长期健康管理的痛点。
Web App Health & Fitness
数字健康 预防性医疗 心脏健康管理 健康数据分析 AI健康助手 远程医疗 生物标志物检测 个性化健康计划
用户评论摘要:用户反馈积极,关注产品核心价值。有效评论集中于技术实现细节(如构建难点、风险预测模型)、用户体验流程(从结果到行动计划的转化),以及市场扩张计划(如进入欧盟)。开发者回应展示了AI报告生成、营养推荐、医疗团队支持等具体功能。
AI 锐评

Empirical Health 的网页版发布,看似是一次简单的平台延伸,实则暴露并试图解决数字健康领域的一个深层矛盾:移动端的便捷性与专业健康数据分析所需的大屏、深度交互场景之间的割裂。其真正的价值不在于“从移动端到网页端”的功能搬运,而在于它正试图成为个人健康数据的“中枢神经系统”。

产品逻辑清晰,遵循“测量-预测-预防”的链条,但其核心竞争力并非那100+生物标志物的检测(这属于第三方实验室),而在于其宣称的AI驱动的数据整合与30年风险预测模型。这里埋下了最大的价值点与质疑点:风险预测模型是基于公认的医学研究框架(如汇集队列方程)进行本地化优化,还是完全自研的“黑箱”?前者具备医学可信度但创新有限,后者若未经大规模长期临床验证,则存在过度营销的风险。

从评论和回复看,团队聪明地将AI定位在“生成报告”、“营养推荐”等辅助环节,而将关键的医疗决策(如开处方)交给了人类医生团队。这是一种务实的风险规避策略,也符合当前监管要求。其“年费会员制”结合医生问诊的模式,试图构建一个可持续的商业模式闭环,但挑战在于如何证明其AI驱动的长期管理方案,能产生优于传统定期体检和医患沟通的、可量化的健康结果改善。

本质上,它是一款“健康数据增值服务”产品。其成功不取决于技术多么炫酷,而取决于能否建立坚实的医学公信力,以及能否将复杂的健康数据,转化为用户能理解、易执行、有正反馈的日常行动。网页版的上线,是向更严肃、更深入的健康管理场景迈出的关键一步,但真正的战役在于临床有效性的证明与用户长期依从性的维持。

查看原始信息
Empirical Health for web
When Empirical Health first launched, it was centered around iOS and Android apps to help you optimize your heart health in your daily life. But sometimes you need a larger screen, especially when viewing blood test reports (there are 100+ biomarkers per test). Now, you can view all of your blood test results, check heart attack risk scores, message your doctor, and schedule lab reviews from your desktop or phone without downloading an app.
Hey everyone, Today we're announcing a new way to interact with Empirical Health through our web app. We took all the features we loved from our mobile app including viewing your test results, chatting with your medical team, predicting your heart attack risk, and more and brought it to our new web app. Our core value prop remains the same: Heart disease kills one in five people in the U.S.—but 80% of heart attacks can be avoided, and your risk is predictable using statistical models up to 30 years in advance. Measure We're offering a $190 test measuring 100+ biomarkers—available at 2,200+ locations nationwide. This includes key biomarkers like: * ApoB: every 10 mg/dL drop cuts heart disease risk by 9% * Lp(a): up to 6x more atherogenic than regular LDL * hs-CRP: an inflammation biomarker that predicts heart disease better than cholesterol Predict Next, we show how your heart attack risk could change by age 70— * If you do nothing * If you follow a tailored plan with medication, diet, and exercise Many people cut their risk by 50% or more with the right changes. Prevent Then, we help you build a personalized action plan with the help of our doctors. Make lifestyle changes to your diet and exercise routine, or start taking a new medication to help prevent heart disease. Check is out here: https://app.empirical.health/app...
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@wyattchang11 what was the hardest part of building Empirical for web?

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@wyattchang11  In your opinion, which statistical models you’re using for 30-year risk forecasting, are these based on established frameworks like pooled cohort equations or something proprietary? The predictive angle is very compelling !

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After a user gets results back, what does the end-to-end workflow look like from “numbers on a screen” to a concrete plan—how do you decide what to prioritize first, and how do you coordinate with (or complement) the user’s existing primary care/cardiologist?
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@curiouskitty we have a few features that take the results from just "numbers on a screen" to actionable change. When results are back people receive an AI generated report for each biomarker. We also have an in-app tool that uses your biomakers to create nutrition recommendations. This can even prompt you when you enter a restaurant on nutrition choices that would be best for you. Our medical team is also available to answer any questions and our year-long members can access doctor check-ins to review the results, get their questions answered, obtain prescriptions if necessary, and ensure we support each individual roadmap toward a long and healthy life!

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Great idea to combine medical care with long-term tracking. Since health data regulations are different here, do you have a roadmap for expanding to the EU market? We are definitely waiting for something like this in Europe!

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@valeriia_kuna our platform can be used across many countries - people can upload their lab results, pair their wearable devices, and take steps toward improving their health outcomes. In the US we are also able to provide medical care and our year-long program includes doctor check-ins to ensure our members get a deep dive into their results and a customized action plan. We would definitely want to expand this component at some point so that it is available to people worldwide!

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#8
Design Rails
Get an agent-ready brand in minutes
118
一句话介绍:一款通过与AI创意总监对话,在几分钟内生成包含logo、色彩、字体等完整品牌标识系统,并打包为“智能体就绪”文件,旨在解决初创团队在验证产品市场匹配前快速获得专业、一致品牌设计方案的痛点。
Design Tools Developer Tools Vibe coding
AI品牌设计 智能体就绪 设计系统生成 品牌标识自动化 初创企业工具 设计令牌 UI风格指南 快速原型 设计交付 AI设计助手
用户评论摘要:用户普遍肯定其解决品牌快速启动痛点的理念和流畅流程,但生成Logo被多次批评为“缺乏创意”、“通用”。另有用户询问对现有品牌的整合路径,以及设计令牌到代码(如CSS、Tailwind)的转换能力,这是确保品牌一致性的关键。
AI 锐评

Design Rails的野心不在于成为另一个Logo工厂,而在于试图成为连接品牌定义与AI智能体执行层的“编译层”。其核心价值并非替代人类设计师的创造力,而是将模糊的品牌方向“编译”成机器可精确理解与严格执行的结构化设计系统(如W3C设计令牌)。这直接瞄准了当前AI辅助开发的核心痛点:智能体在生成UI时因缺乏严格约束而导致品牌表现飘忽不定。

产品将品牌资产封装为“智能体就绪”文件,本质是提供了一套AI原生时代的设计交付标准。它解决的真正问题,是从“人类可读的设计稿”到“机器可循的设计规则”的最后一公里转化。评论中关于Logo“通用”的批评,恰恰点中了当前AI生成视觉的普遍短板,但这或许并非其最致命的弱点。更关键的考验在于,其生成的设计系统在复杂项目中的深度、灵活性以及与技术栈(如Tailwind)的集成度,能否支撑起一个真实、持续演进的品牌。若其设计令牌体系足够健壮,即使初始Logo稍弱,品牌的核心体验(色彩、间距、字体层次)也能得到保障,这比一个孤立的精美图标更有长期价值。

该产品是典型的“为AI而生”的工具,其成功与否,取决于它能否在AI智能体驱动的开发流程中,成为不可或缺的基础设施,而不仅仅是一个一次性的品牌速成方案。

查看原始信息
Design Rails
Chat with an AI creative director. Get a complete brand identity in minutes—logo, colors, typography, voice & tone, UI styles—all packaged as agent-ready files. No more generic UI. Drop the files into your project, and tools like Claude and Lovable generate on-brand UI from day one.

Big thanks for the launch lift, YC & @garrytan!

Hey Product Hunt 👋,

Here's the backstory - last year, we needed a new brand for a product we had built quickly and were going to ship within days. We couldn't justify paying thousands of $'s on a brand before PMF, nor could we afford waiting weeks for the full design cycle.

Plus, we wanted more than a visual reference in Figma, or a homepage template. We needed a design system that we could handoff to agents to carry the brand consistently across app workflows, and marketing channels. It needed to include UI styles, voice & tone guidelines, a logo and logo derivatives that'll work well for a favicon, and light and dark themes.

We talked with other builders who were in the same boat and realized this was a common problem. So, we built Design Rails.

Looking forward to hearing how it works for you, and happy to answer any questions!

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@garrytan  @ehudhal When I'm in a tight MVP sprint, the agent starts freelancing, new spacing, new radii, slightly different blues. Design Rails shipping a design-context folder with agent-instructions.md and W3C design-tokens.json is the kind of handoff that actually works. Do you also generate CSS variables or a Tailwind theme from the tokens so the app and landing page don't drift apart? That last mile is where brand kits usually fall apart.

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Just tried it. Hoped to have a good alternative to fiverr when it comes to logo design. The flow is very intuitive and also the color selection was a good fit for my test company. I really like that I get the files to throw them directly into Claude. Still a big BUT: the generated logos do not look professional. Sorry to say but it’s like using any out of the box AI to get a logo. Very generic - 0 creative.
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@t1m0slav Thanks for giving it a try, and for the feedback!

The logos are a fun problem :) If you gave a thumbs down to those that weren't helpful that'll help us look into the specifics and tune it up further. Or, if you're open to sending over the thread ID (URL) over to hello@designrails.com that would be much appreciated.

In many of the runs, we've been blown away by the creativity the AI achieves (looking at you, nano banana) in capturing concepts, and reflecting the desired style. It fails at times, and there's more work to do! What often works well is going beyond the single-shot, asking for (free) variations and steering it with revision guidance to hone-in on the concept you have in mind.

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Why are you lying about being backed by YC?

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Hi @sam_alexander1 Design Rails is the name of the product. Company is Chordio. https://www.ycombinator.com/companies/chordio

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Congrats on the launch, Team! 🚀

Love the idea - getting a full, agent-ready brand in minutes is super practical.

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@rohithreddy Thanks, Rohith!

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If someone already has a partial brand or an existing product UI, what’s the recommended adoption path—do you recreate from scratch, extract and normalize into tokens, or incrementally refactor—and how long does it typically take to get to a stable system?
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@curiouskitty- that's pretty much the process. You provide the partial brand (e.g. hex values, typography, visual concepts) as an input to give an initial direction, and you get a more complete brand system. If we define "stable system" as "the UI I'm building doesn't look generic and the AI consistently follows the brand guidelines" - once you're happy with the brand and add the exported package as design context, the LLM picks it up immediately and does a really good job following it.

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I liked onboarding and user flow, but logos are very generic. Hope improve it soon

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@vasilbo thanks for checking it out and for the feedback. 🙌

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#9
SPECTRE
An agentic coding workflow for product builders
108
一句话介绍:SPECTRE是一个为产品构建者设计的、遵循“规划-执行-测试”等明确步骤的智能体编码工作流,旨在通过消除需求模糊性,帮助开发者利用AI编码助手(如Claude Code)高效、稳定地产出高质量代码。
Software Engineering Developer Tools GitHub Maker Tools
AI编程助手 智能体工作流 代码生成 软件开发流程 人机协作 项目管理 工程化 生产力工具 上下文管理 质量保证
用户评论摘要:创始人强调其能实现可重复的高质量结果,并用于自家产品开发。用户认可AI编程对生产力的变革,并深入探讨了长会话上下文管理的技术方案。产品核心原则“模糊性是致命的”引发共鸣,证实清晰的输入对输出质量至关重要。
AI 锐评

SPECTRE的野心不在于替代另一个代码补全工具,而在于试图为“智能体编程”这场混乱的早期实验,强行注入软件工程的纪律性。其宣称的“一个工作流,应对所有功能、任何规模、任何代码库”,更像是一剂对抗AI幻觉与项目熵增的理想化处方。

产品真正的价值,或许不在于其“/Scope, /Plan...”这套看似线性的步骤本身——任何资深开发者对此都耳熟能详——而在于它试图将人类项目经理的架构思维与AI的执行能力进行标准化耦合。它戳中了当前AI编码的核心痛点:AI并非能力不足,而是其输出质量极度依赖于输入的精确度与上下文的一致性。SPECTRE通过“手动交接”状态报告和自动加载“技能文档”来维持上下文连续性,这是一种务实的“胶水策略”,本质上是将人类开发者提升为架构师与审核者,而将重复性、易出错的代码实现与上下文维护工作交由流程和AI管理。

然而,其挑战也同样明显。该工作流高度依赖使用者自身具备清晰的架构和拆解能力(“伟大的输入”),这无形中设立了不低的用户门槛。它能否真正适配“任何规模”的项目,尤其是在庞大、混乱的遗留代码库中,其“技能文档”的维护成本可能成为新的瓶颈。当前的热捧更多源于早期采用者(如创始人自身)在绿地项目上的成功,其方法论在更广泛、更复杂的现实开发环境中能否经受住考验,仍需观察。它是一盏在AI编码迷雾中指明方向的灯,但脚下的路,依然需要开发者自己一步步去夯实。

查看原始信息
SPECTRE
SPECTRE is an agentic Coding Workflow - /Scope, /Plan, /Execute, /Clean, /Test, /Rebase, /Evaluate - that uses simply step by step product development workflow to generate high quality results from your AI Coding Agents. - Codename-Inc/spectre
Hey everyone! I’ve been iterating on the SPECTRE workflow almost daily for the last year with the goal of getting repeatable and consistent high quality results from Claude Code. SPECTRE has made it possible to do more, faster, and with higher quality and I really don’t see an end to this workflow continuing to improve and find/eliminate each bottleneck in agentic coding process. 🎯 Core SPECTRE Principles * Great Inputs → Great Outputs * Ambiguity is Death * One Workflow, Every Feature, Any Size, Any Codebase * Obvious > Clever We use SPECTRE at our startup Codename to build Subspace (open beta) and New June (closed alpha). Neither of those products would exist without it. I hope this works as well for you all as it does for us.
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Congrats on the launch, @joenandez !

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@neilverma thanks Neil!

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Agentic coding has completely changed how I ship. Built a 118k-line SwiftUI Mac app solo using Claude Code — the key insight was that it's not just autocomplete, it's having something that actually understands the full codebase. What's your approach to context management across longer sessions? That's where I've found the biggest gains.

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@matthias_stralman 100%. Our app Subspace has a Rust backend. I’ve never written a single line of Rust before we started building it. LLM’s are a universal translater and the language is system architecture!

SPECTRE uses a manual /handoff that auto inserts a status report into the next session - complete continuity until you run /forget. And the learning Skill documents features that get auto loaded when relevant. It’s really simple but it works really well.

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Hey Joe, that principle of ambiguity is death says a lot. Was there a specific feature or task where Claude Code went completely off the rails because the input wasn’t clear enough?
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@vouchy oh man all the time. I actually experimented with the first version of our app Subspace and built two versions - one with Spectre (an early version) and one without. The without version looked better, but once you got down one layer it was a complete untangle-able mess. The Spectre version is what exists now.

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I like the objective Joe, best of luck with the launch!

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@stellify_software I appreciate it Matt!

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#10
Calendarly
Turn your calendar into a live Lock Screen wallpaper
107
一句话介绍:Calendarly将手机日历实时同步至锁屏壁纸,在频繁解锁手机查看日程的场景下,让用户一目了然、避免分心,解决了碎片化时间管理中注意力易被转移的痛点。
iOS Calendar Wallpaper
锁屏工具 日历可视化 效率应用 个性化壁纸 隐私安全 本地化处理 日程管理 实时更新 iOS自动化 无干扰设计
用户评论摘要:用户普遍赞赏其UI设计及定制化能力。主要问题集中在自动更新机制上,开发者解释其通过iOS快捷指令自动化实现,需用户手动设置一次。创始人自述开发动机引发共鸣。
AI 锐评

Calendarly的本质,是将“查看日程”这一高频低复杂度行为从“主动打开应用”简化为“被动视觉接收”,其核心价值在于对注意力的保护而非信息呈现本身。产品聪明地利用了系统级壁纸作为信息载体,避免了 widget 仍需在锁屏界面“主动注视”的交互成本,实现了真正的零点击信息获取。

然而,其技术实现依赖快捷指令自动化,实则是苹果系统权限限制下的妥协方案。这种“伪实时”更新存在延迟风险,且设置门槛虽低但仍需用户进行自动化配置,与产品宣称的“无配置”理念存在微妙矛盾。隐私安全虽是亮点,但纯本地处理在跨设备同步和多日历账户管理上将面临天然瓶颈。

产品目前精准切入了一个细分场景,但长期价值取决于其能否从“美观的日历显示器”升级为“情境化信息中枢”。若仅停留在视觉优化层,易被系统原生功能迭代所覆盖。其真正护城河在于对用户日程数据的智能解析能力——例如根据日程紧急程度自动调整视觉权重、整合交通天气等情境信息。目前看来,产品在“减少分心”的定位上值得肯定,但在“增强认知”维度尚未展现更深层的思考。

查看原始信息
Calendarly
Calendarly turns your calendar into a live Lock Screen wallpaper that updates automatically throughout the day. See your schedule the moment you pick up your phone - no widgets to configure, no apps to open, no distractions pulling you away. Choose from beautifully designed templates and fully customize them to match your style, layout, and priorities. Fully private. Everything runs on-device.
Hey Product Hunt 👋 I built Calendarly because I noticed something stupid about myself — I unlock my phone dozens of times a day just to check what’s next. And almost every time, I end up distracted by something else. So I started wondering: what if my calendar was just… always there? Not as a widget. Not inside an app. But directly on the Lock Screen. Calendarly turns your schedule into a live wallpaper that updates automatically throughout the day. You can choose a layout and fully customize it to match your style and priorities. Everything runs fully on-device. No accounts, no tracking, no cloud processing. It’s been live for 2 days now and 2,300+ people are already using it daily, which honestly still feels surreal. Would love your feedback — what would you add or improve?
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Looking cool. Congratulations! Really like the UI design on the widgets.

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@alpsu_dilbilir Thanks a lot, really appreciate it!!

Yeah, I spent quite some time on the UI. You can actually customize pretty much everything and create completely different presets and styles.

The only real limit is your imagination :)

Glad you like it!

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Thank you for this! Really nice made, congrats!
How does it update automatically with my up-to-date calendar?

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@kkyshko Thank you, really appreciate it !!

It updates using a Shortcuts automation. You basically set it once, and it regenerates the wallpaper automatically at whatever time/frequency you choose.

There’s a simple step-by-step tutorial inside the app that walks you through it, takes less than a minute to set up.

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#11
Your AI Clone
Your clone remembers people you've never met
105
一句话介绍:一款允许用户基于自身内容、声音和个性训练AI克隆的产品,该克隆拥有独立页面,可24/7与受众互动并记忆对话历史,解决了创作者无法实时、个性化与所有粉丝深度交流的痛点。
Social Network Artificial Intelligence E-Commerce
AI克隆 数字分身 个性化AI 创作者工具 粉丝互动 记忆会话 内容变现 虚拟形象 人工智能代理
用户评论摘要:用户反馈呈现两极。积极方惊叹于其记忆和拟人能力,分享了克隆在深夜与陌生粉丝进行有连续性深度对话的震撼案例。消极方则尖锐质疑未明确标价,并担忧“AI冒充真人”可能引发的欺骗感和信任危机。
AI 锐评

“Your AI Clone”所描绘的,并非一个简单的聊天机器人,而是一个企图将“人”进行异步化、可扩展化运营的数字替身。其宣称的核心价值——“记忆”,是它区别于早期静态知识库型AI的关键,试图通过构建连续性对话关系来模拟真实人际互动,从而提升粉丝粘性与体验。

然而,其光鲜表皮之下蛰伏着巨大的伦理暗礁。产品介绍中“talks to your audience as you”的表述,已游走在欺骗的灰色地带。当用户知晓自己倾注情感的对话对象并非真人,产生的被背叛感和信任崩塌,将直接反噬创作者本人的品牌信誉。评论区的质疑恰恰击中了这一命门。这不仅是“技术透明”的问题,更是对人际交往本质的粗暴简化。

从产品逻辑看,它瞄准了创作者日益增长的“分身乏术”与“流量变现”焦虑,提供了一种看似高效的解决方案。但其真正的挑战在于:第一,如何确保克隆的言行不偏离本体核心价值,避免“失控”?第二,当记忆成为卖点,用户数据的隐私与安全如何保障?第三,这种“伪亲密关系”的批量制造,长期是否会导致受众对真实互动的感知钝化?

该产品是技术可能性的一次大胆试探,但更像是一把未装刀柄的利刃。它为创作者提供了前所未有的互动扩展能力,却未同时提供与之匹配的伦理操作指南与风险管控机制。在监管与社会共识尚未跟上的当下,过早地将此推向市场,收获的或许不仅是105个点赞,更可能开启一场关于身份、真实性与信任的潘多拉魔盒。它的成功与否,将不取决于技术是否炫酷,而取决于团队能否以最大的审慎,在效率诱惑与人性底线之间找到那个危险的平衡点。

查看原始信息
Your AI Clone
Build an AI clone trained on your real content, voice, and personality. It gets its own page, talks to your audience 24/7, and remembers every person it speaks to across sessions. Monetize it or keep it free.
Hey PH! Last week someone thanked me for a conversation I never had. They'd been talking to my clone at 2am about something I covered in a blog months ago. My clone remembered them from a previous conversation, referenced it, and built on it. I was asleep. I didn't know this person existed. That's Brussle. Feed it your content. It learns how you think, how you talk, your humor, your edges. It gets a public page and talks to your audience as you. It remembers everyone it speaks to.
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@shaunscdmx why haven’t you mentioned the price on your site?
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@shaunscdmx What happens when the person learns it was an AI they were talking to and not you? I think some people would be very annoyed that they were lied to.

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This is wild! 🤯 Loving the idea of an AI that actually remembers and talks like you.

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@rohithreddy Thank you

0
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#12
OpenFlowKit
100% Free and Open Source Diagram Creator with Total Control
100
一句话介绍:一款完全免费、开源的现代化图表引擎,通过代码编写、拖拽和AI对话三种方式,为厌倦了陈旧界面和高昂订阅费的工程师与产品团队,提供兼具美感与掌控力的图表绘制解决方案。
Design Tools Open Source Developer Tools GitHub
开源图表工具 图表即代码 AI绘图 流程图引擎 设计工具 本地优先 免费生产力工具 Mermaid Figma导出 开发者工具
用户评论摘要:用户赞赏其美观界面、开源免费及灵活操作。核心反馈集中在:1. 寻求与Excalidraw等工具的差异化优势;2. 建议营销话术应更侧重投资回报率以提升转化;3. 询问AI供应商扩展(如支持OpenAI)、暗黑模式及P2P协作功能。开发者回应积极,相关功能已在规划。
AI 锐评

OpenFlowKit的亮相,精准刺中了当前图表工具市场的两大痼疾:审美滞后与订阅制泛滥。它并非又一个“功能缝合怪”,其真正价值在于试图重构图表创作的工作流范式——将“图表即代码”的精确可控、拖拽操作的直观与AI的自然语言意图理解,整合进一个本地优先的浏览器环境中。这直指专业用户的核心诉求:在追求效率与表达自由的同时,拒绝数据上云与持续付费。

然而,其面临的挑战同样清晰。评论中关于“差异化优势”的追问一针见血。在Excalidraw(手绘风协作)和Mermaid(纯代码)已占据心智的赛道,OpenFlowKit的“三合一”模式能否形成足够陡峭的学习曲线与体验壁垒?其引以为傲的“美学默认值”和Figma矢量导出,是锦上添花还是关键破局点?仍需市场检验。另一条关于“营销应聚焦ROI”的评论则揭示了更深层的产品-市场匹配问题:对于厌倦了月费的个体用户,“免费”是利器;但对于试图切入团队场景,“本地优先”、“数据安全”和“可定制化”的工程价值,或许才是更锋利的钩子。

开发者的回复展现了敏捷与开放,快速迭代AI模型并规划P2P协作。这印证了开源模式在反馈循环上的优势。但长远看,其成功与否将取决于能否在“优雅的玩具”与“可靠的生产力工具”之间找到平衡,并围绕其开源生态构建起可持续的开发者社区与扩展能力。否则,它可能仅会是一小部分技术美学爱好者的精致选择。

查看原始信息
OpenFlowKit
OpenFlowKit is a 100% free, open-source diagram engine for engineers, architects, and product teams who care about craft.
Hey Product Hunt! 👋 I'm V, and I built OpenFlowKit because I was tired of two things: 1. Diagram tools that look like they're from 2005, locked colors, rigid templates, enterprise beige everywhere. 2. Paying $20/month for something that should be a text file. OpenFlowKit is my answer: a diagram engine where you can write code (Mermaid or DSL), drag-and-drop, or just tell the AI what you want. It runs 100% in your browser — no signup, no cloud, no data leaving your machine. Some things I'm proud of: * Flowpilot AI — BYOK with Gemini. It actually understands diagram context. * Figma export — Copy-paste gives you editable vectors, not flat images. * The aesthetics — I spent way too long making sure diagrams look beautiful by default. It's MIT licensed and completely free. I'd love your feedback, what would make this your go-to diagram tool?
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@vrun Love the “diagram as code + AI” combo! Where do you see OpenFlowKit’s biggest edge versus tools like Excalidraw or Mermaid Live, aesthetics, AI context awareness, or workflow flexibility? Also, when you say Flowpilot understands diagram context, does it reason about structure (nodes, dependencies, hierarchy), or mostly operate at a visual/layout level?

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@vrun Congrats on the launch! Since you asked for feedback: the product itself looks solid, but I think you’re leaving some money on the table with the current positioning. Right now, it’s very 'feature-heavy.' If you pivot the copy to focus more on [ROI / User Growth / Time saved], your conversion rate from this PH traffic would likely double. I do this for a living at franvimktg, happy to drop some specific copy tweaks if you want to bounce some ideas around!
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Varun Congratulations on the launch. The clean interface looks great and the ease of dragging and dropping nodes offers a very pleasant experience. I'm sure it will be a guaranteed success since it has the necessary options to create robust flows. What you have created is wonderful, congratulations! Also, the attention to detail in the design really makes a difference and demonstrates a very professional approach.

And the best part is that it is open source and completely free. Wow!

Moreover, being open source means any developer can adapt and customize the tool according to their specific needs, enhancing its flexibility and reach. This also fosters a collaborative ecosystem where improvements and updates can come from multiple sources, ensuring the software’s constant evolution. Without a doubt, this feature opens many doors for future innovations and greater accessibility in using the tool.


I have a question: is BYOK only with Gemini? I ask because, for now, I only have OpenAI. I would like to know if there is any compatibility or planned support for other platforms or cloud service providers. It would also be helpful to understand if there are significant differences in the implementation or management of BYOK between Gemini and OpenAI, so I can properly prepare the integration depending on the environment used.

Do you have any plans for a dark mode option?

It would be great to know if you are considering adding more integrations in the future to expand its reach and functionality.

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@martin_hernandez4 

Thank you so much for the incredibly kind words! Really glad you’re enjoying the UI and the open-source aspect, it’s the core of why we built this.

Regarding your questions:

  1. AI Providers: Currently it’s BYOK for Gemini only, but we built the service layer to be modular. OpenAI and Claude support are the top priorities for our next update. The experience will be identical, just pop in your key and go.

  2. Dark Mode: 100% on the roadmap! We're planning to ship 'Dark mode' soon. You can expect this and more model support by early next week.

  3. P2P Collaboration: One big thing we're planning is P2P Multiplayer via WebRTC. This will allow two people on the same Wi-Fi to brainstorm on one canvas with zero database or cloud infra required, just browser-to-browser sync.

  4. UX & Core: We're also working on a more persistent Flowpilot AI sidebar for better back-and-forth refinement, along with improved node components, auto-layouts, and higher export fidelity.

Thanks again for the support! 🚀

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Looks beautiful! What are your plans for the AI mode? I just entered an API key and prompted something relatively simple and got a less-than-optimal result. Would be cool if I could back-and-forth with the AI to refine my result.

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@wilco_kruijer1 

Thanks so much for the kind words on the design! We just pushed a few updates specifically to address your experience with Flowpilot (AI mode).

  1. Model Selector is LIVE: We just added a model selector in Settings > Brand Kit > Flowpilot. You can now choose between 2.5 Flash, 2.5 Pro, and even the new Gemini 3 Pro/Flash (Preview) for much better reasoning on designs. We’re also working on adding OpenAI and Claude models to give users more flexibility across top AI providers.

  2. Optimized Layouts: We’ve switched our auto-layout engine to a dedicated Tree algorithm (mrtree) for AI results. This produces significantly cleaner, more professional hierarchies than before.

  3. Refinement is supported: You can actually keep chatting with the AI to tweak the result (e.g., 'add a retry loop' or 'change the theme to blue'). However, we realized the current UI (closing the modal after generation) makes this feature feel hidden. We're working on a persistent sidebar chat so you can refine side-by-side with the canvas.

If you’re open to sharing the prompt that gave you a less-than-optimal result, I’d love to test it against our new layout and model updates!
Please use this form: CLICK HERE

Really appreciate the candid input, it helps us move way faster. 🚀

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#13
Baseline Core
Open-source skills system that wires your business into AI
97
一句话介绍:Baseline Core是一款开源AI技能系统,通过一键配置将企业业务上下文注入各类AI工具,解决AI输出内容与业务脱节、产品工作流程缺乏结构化支持的痛点。
Productivity Open Source Artificial Intelligence GitHub
开源AI工具 技能系统 业务上下文集成 AI代理 产品开发框架 多平台兼容 提示工程 团队协作 工作流自动化 无供应商锁定
用户评论摘要:用户反馈系统显著提升工作效率,实现“一人团队”效果。主要问题聚焦于技能配置灵活性、上下文文件加载机制(是否全量加载)、与OpenClaw等工具的集成可能性,以及长会话中的上下文管理优化。
AI 锐评

Baseline Core的本质,是一个试图将“提示工程”体系化、产品化的野心之作。它不提供新模型,而是提供一套让现有模型(Claude、GPT等)更深度嵌入企业工作流的“中间件”。其真正价值在于两点:一是通过标准化的技能、框架和上下文文件,将零散的AI提示词提升为可版本控制、可组合的业务能力模块,对抗AI输出的随机性与通用性;二是其工具无关的开放设计,直指当前AI工具生态碎片化的痛点,为用户构建了一层可迁移的“业务逻辑层”。

然而,其挑战同样明显。首先,其核心价值高度依赖于“业务上下文”的质量与更新维护,这本质上将知识管理的负担转移给了用户,而非真正解决。其次,评论中透露的上下文管理、长会话质量衰减问题,是底层模型固有限制,仅靠工作流编排难以根治。最后,其“一人团队”的愿景虽诱人,但将产品、设计、市场等非结构化决策过度流程化,可能抑制创新,产出“正确但平庸”的结果。它是否真能成为AI时代的“业务操作系统”,还是沦为另一套需要精心维护的复杂脚本,取决于其能否在灵活性与规范性、自动化与人类把控之间找到更精妙的平衡。

查看原始信息
Baseline Core
Baseline Core is an open-source skills system for AI agents. Run one command and your AI tools can research markets, write PRDs, plan sprints, and design user flows -- all grounded in your business context. 12 skills, 14 frameworks, 34 reference files. Works with Claude Code, Cursor, Codex, ChatGPT, Gemini, Windsurf, and GitHub Copilot. Free forever.

Hey everyone! I'm Trent, founder of Baseline Studio. I research how product teams can work better with AI.

Baseline Core is a free, open-source skills system that wires your business context into any AI tool. You run one command, answer a few questions about your business, and your AI agents can start doing real product work -- research, PRDs, sprint planning, user flows, design, prototyping, positioning, and more.

It works with Claude Code, Cursor, Codex, ChatGPT, Gemini, Windsurf, and GitHub Copilot. Tool-agnostic by design.

I built this because I kept seeing founders and small teams either skip product work entirely or get generic AI output that didn't sound like their business. Baseline fixes that.

Would love to hear what you think. Happy to answer any questions!

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@baseline_studio On the skills side, what does a Baseline Core skill look like under the hood, is ux-design just markdown in skills/, or can a skill run code too? The npx @baseline-studio/cli init scaffold that drops skills/, context/, frameworks/, and AGENTS.md feels like the right path for tool-agnostic use across Claude Code, Cursor, Codex, and Copilot. The trust builder for teams is drift control, version skills plus core/voice.md, stamp outputs with the versions used, and ship a tiny eval set so a tweak doesn't silently change PRDs or sprint plans.

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@baseline_studio Trent, how flexible is the configuration regarding what exactly gets fed into the context? For example, if I'm making a skill for DB refactoring, can I feed it only the database schema and migrations, ignoring the marketing docs? I want to keep the focus narrow so the model doesn't get distracted or start hallucinating

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Trent showed me this system about a month ago and I've been experimenting with it since then; and my honest take is, this is a great unlock! With this system I have been able to supercharge my claude-code usage (tbh I also got into claude-code because of this system) to the extent where I am effectively only reviewing PRs now! Another thing this has really done for me is unblock me on all the non-technical tasks (like voice and communication or customer profile and positioning) and concretely articulated my ideas and documented them! I am now adapting the @Baseline Core system to fit my exact workflow and exploring how I can build without any employees but with the impact of a team of ten.. That is what this system truly unlocks!!

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@isthispalash This is incredible feedback. The fact that you've gone from experimenting with it to adapting it to your own workflow is exactly what the system is designed for. The context layer is what makes that possible. Once it knows your business, every skill gets more specific to how you work. The "impact of a team of ten" framing is something I think about constantly, that's the real unlock here. Not replacing people, but giving a solo founder or small team the structured output that used to require dedicated roles across product, design, marketing, and strategy. Really appreciate you sharing this!

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The markdown-as-skill pattern is underrated — keeping everything as plain files means it stays portable and version-controllable without any lock-in. What I'm curious about: when you say the skill loads supporting context files together, does the agent get all 34 reference files at once or does it selectively pull based on the specific skill being run? Managing context window size feels like the main tradeoff here vs. just dumping everything in.

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@cogotemartinez Each skill has a manifest.yaml that declares exactly which context, frameworks, and reference files it needs. Reference files are nested inside each skill's folder, so the UX design skill has its own set of 6 references while research synthesis has a different set. The agent reads the manifest first and only loads what that specific skill requires. Not all 34 at once. Agents[dot]md is what connects everything. It routes tasks to the right skill, tells the agent where to find the manifest, and defines the execution protocol. The workflow orchestration framework also handles context management across sessions. For larger tasks it scopes work into multiple sessions and generates a plan so context stays clean and output quality doesn't degrade. That said, managing context within longer sessions isn't always consistent yet and it's something I'm actively looking for better solutions to.

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This is awesome! Does it integrate with OpenClaw? How did you curate the skills?

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@dan__cleary Thank you! I haven't used OpenClaw yet, but Baseline is modular by design. The skills, frameworks, and context files are all standalone markdown, so in theory they should be portable into other systems but I'd love to explore that more!

As for how I curated the skills, they come from my experience across the full product development spectrum. Each one maps to a phase of pre-engineering product work that I've done hands-on and refined across client engagements.

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#14
Reflex Rooster
Can You React in Under 300ms!?
96
一句话介绍:一款通过“鸡叫”测试反应速度的网页游戏,在碎片化娱乐场景下,为用户提供了从静态枯燥的传统反应测试转向动态、可竞争、易上瘾的轻量化游戏解决方案。
Productivity Developer Tools Games
反应速度测试 轻量网页游戏 休闲竞技 排名系统 成就徽章 多人竞速 全球排行榜 成瘾性设计 碎片时间杀手
用户评论摘要:用户普遍认可其趣味性和成瘾性,但指出核心机制(以鼠标释放而非按下作为触发)可能不公平且易被“取巧”,影响了与标准反应测试的可比性。开发者积极互动,并已根据反馈更新了排行榜等功能。
AI 锐评

Reflex Rooster 的本质并非严谨的反应速度测量工具,而是一款成功将“反应测试”这一单一行为游戏化的产品。其真正价值在于,通过一套成熟的游戏化框架(XP、段位、徽章、排行榜)包裹一个极简交互,精准狙击了用户对“即时反馈”和“攀比心理”的需求,将枯燥的点击变成了有目标的“刷分”和社交竞争。

然而,产品面临的核心矛盾在于其“科学性”与“游戏性”的冲突。高赞评论犀利地指出,其采用“鼠标释放”作为触发判定的机制,实际上引入了一个非反应时间的变量——预判和长按策略。这使其数据无法与《人类基准》等标准测试对标,削弱了其作为“反应力基准工具”的严肃性,但或许反而增强了作为“游戏”的策略深度和可钻研性。开发者面临的抉择是:坚持现有机制,明确其游戏娱乐定位;或修改机制以追求硬核公平,但可能失去部分“可操作性”带来的趣味。

从产品迭代看,开发者显然选择了前者,并快速加入了排行榜等强化竞争的功能。其成功关键在于极低的入门门槛和丰富的进度系统形成的“反差感”,让用户在“简单到愚蠢”的交互中,为虚拟荣誉投入远超预期的时间。长期挑战在于,单点玩法的深度有限,需依靠持续的内容更新(如每日挑战、新徽章)和社交功能来维持用户活跃,否则极易像许多爆款小游戏一样,经历快速的热度衰减。它是一款设计精良的“时间熔炉”,完美诠释了如何用最小成本撬动用户的好胜心。

查看原始信息
Reflex Rooster
Test your reaction speed in Reflex Rooster – the ultimate chicken scream reaction game. Compete in solo mode, endless streak mode, or multiplayer race. Track XP, ranks, badges, and beat your fastest reaction time.

Hey everyone 👋

I built Reflex Rooster because I’ve always loved simple browser games that are easy to start but hard to master. Most reaction time tests online feel static and boring — just click when the screen changes color.

I wanted to turn that into something competitive and addictive.

So I added:

Rank progression (Sleeping Egg → Legend 🏆)
Endless streak mode with auto-restart
Multiplayer CPU reaction races
XP system, combos and badge unlocks
Daily challenges that reward extra XP
Deep stats dashboard (accuracy, best time, streaks, history)
Global online leaderboard .
Profile system with one-time name + country (locked for fairness)
Country filters to see top players from your region
Offline-friendly sync (your best runs sync when you’re back online)


The hardest part was balancing randomness and fairness — the scream timing had to feel unpredictable but not frustrating, while still rewarding real reflexes and consistency.

I’d love feedback on:

Does it feel addictive enough to keep grinding ranks and badges?
Is multiplayer (racing the CPUs) competitive and satisfying?
Does the global leaderboard + country filter make you want to climb higher?
What else would make you replay it daily?

Appreciate any thoughts 🙏

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Haha, I can't believe how fun this was. So silly but well done. @lokeshchoudharyprogrammer what was your high score? I got 225 before I went back to work 😅

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@gabe Haha you’re way too quick 😆 225 was insane! I just barely hit 279ms 😂 That Reflex Rooster is turning me into a chicken ninja 🐔💥

You should def share it with your friends and see who’s the real cluck-master 😂✨ Try it again at

https://www.reflexrooster.com/ — upcoming updates are gonna be even better (leaderboard + more things 😎🔥). Come beat me again!

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@gabe just added a leaderboard and some cool new features at https://www.reflexrooster.com/ 😎🔥 Come try again and climb the ranks!

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This is great man, super polished, I was hooked for more time than I'm proud to admit.
But I was wondering why my scores where so much worse than the human benchmark ones. Then I've found out it only counts the click on mouse up. That knowledge changed everything, the strat is to click and hold, then just release when it's time.
With that I've set up the record for Brazil with 200ms (which is still slower than my consistent times on human benchmark for some reason).
Might be worth considering tweaking the trigger to onMouseDown, but that might also require some re-balancing

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@guibassa oh wild, I didn't know that but that does feel like it could be gamed! That's a good find.

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Absolutely loved this.

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@otodidakt_20 Thanks so much! Really happy you loved it 🎉😊 Means a lot! If you have any feature ideas or feedback, I’d love to hear them 💬✨

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Lmao what a fun way to kill a few minutes and turn of my brain. Reminds me of the google dinosaur game

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I started playing this 15 mins before and turns out I am already World#2. Good Game though bro 😄🤍.

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I guess I'm kinda slow - 405 was my best. Lots of fun though - nice work!

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#15
Open blivz
Customizable Open-source alternative to Clay
95
一句话介绍:Open blivz是一款可本地运行、开源的GTM(市场进入策略)工作流工具,为使用Claude Code等AI工具的工程师和运营团队,解决了依赖高价SaaS(如Clay)进行数据丰富和线索生成时成本不可控、工作流不灵活的痛点。
Sales Open Source Marketing GitHub
开源GTM工具 数据丰富 线索生成 工作流自动化 可本地部署 市场进入策略 成本控制 Claude Code集成 RevOps 可定制化
用户评论摘要:创始人解释转向开源是为适应“可编程GTM”趋势。用户反馈强烈认同,以自身使用Clay成本高昂为例,指出自托管开源模式能彻底改变成本结构,并建议提供对标Clay的预置工作流模板以降低迁移门槛。
AI 锐评

Open blivz的亮相,远不止是又一个“开源替代品”。它精准刺中了当前GTM工具市场的一个隐秘痛点:在AI编码助手普及的背景下,专业团队的定制化需求与封闭SaaS的僵化模型及成本黑箱之间的矛盾。

其真正价值在于“主权移交”。它将数据丰富、工作流编排的核心逻辑从Clay这样的专有“画布”中解放出来,变成团队代码库的一部分。这不仅意味着用户自带API密钥,直接控制每次调用的成本(彻底解决“积分暴增”问题),更关键的是,它将GTM工作流从“配置”层面提升到了“编程”层面。这正呼应了其创始人洞察的“GTM正在变得可编程”的趋势——现代GTM工程师和RevOps团队,需要的是可以像基础设施一样被版本控制、持续集成和深度定制的工具链。

然而,其挑战也同样明显。开源模式放弃了SaaS的便捷性,将安装、维护、安全的责任转移给了用户,其目标客群因此被严格限定在具备较强技术能力的“构建者”范围内。这固然是一个精准的利基市场,但也可能成为增长的天花板。此外,从评论中用户的迫切建议可以看出,生态建设是关键。提供与主流SaaS工具兼容的“迁移模板”,降低采用初期的认知负荷和切换成本,将是其能否从技术爱好者的玩具,转变为真正生产力工具的第一道考验。

总而言之,Open blivz代表了一种清醒的行业趋势:在AI赋能开发的时代,工具的价值正从提供封闭的全套解决方案,转向提供高度模块化、可被编程和集成的核心能力。它不是在功能上挑战Clay,而是在范式上颠覆Clay。

查看原始信息
Open blivz
blivz is an open-source, customizable tool for data enrichment, lead generation, and GTM workflows. Designed for modern GTM engineers, RevOps teams, and builders already using AI tools like Claude Code for GTM. blivz enables you to Run it locally and use Claude Code to fully customize your stack and GTM motion.

Hey Product Hunt 🎉 I’m Houssam, founder of blivz.

I originally planned to launch this as a paid SaaS.

But I changed direction.

Why ?

GTM is becoming programmable.

More teams are using AI tools like Claude Code to build custom workflows, automate enrichment, and orchestrate outreach.

So we built something customizable.

blivz can run locally, be self-hosted, extended, and shaped to your exact GTM motion.

Would love your feedback.

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回复

@mhoussam9 Last quarter I wired up a Clay table to enrich about 2k contacts and blew through credits in two days. The markup on enrichment calls versus hitting the APIs directly was painful. Self-hosted and open source changes that math completely... you bring your own keys, you control per-call cost, and the workflow logic lives in your repo instead of a proprietary canvas. A library of pre-built enrichment recipes mapping to common Clay table setups would make migration dead simple.

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@mhoussam9 but first, congrats on the launch!

2
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#16
STUD
Cursor for Roblox Studio
84
一句话介绍:STUD是一款深度集成于Roblox Studio的开源AI编程助手,可在Roblox开发环境中直接编辑Luau脚本、操作实例、查询数据存储和搜索工具箱,显著提升Roblox开发者的工作效率。
Developer Tools Artificial Intelligence Games
AI编程助手 Roblox开发 开源工具 Luau脚本 游戏开发 生产力工具 Roblox Studio插件 代码辅助 开发者工具
用户评论摘要:用户反馈极少,仅有一条评论询问Logo为何选用榴莲,开发者回复称是临时选择并沿用。目前无关于产品功能、体验或问题的有效讨论与建议。
AI 锐评

STUD瞄准了一个高度垂直且潜力巨大的细分市场——Roblox创作生态。其核心价值并非泛化的AI代码补全,而是深度绑定Roblox Studio工作流,实现对Luau语言、DataStore、Instance等平台特有元素的精准理解和操作。这解决了Roblox开发者需在通用AI工具与专属开发环境间频繁切换、上下文割裂的痛点,将AI辅助直接“嵌入”生产环节。

然而,其面临的挑战同样尖锐。首先,Roblox开发者社区年龄层跨度大,专业开发者占比有限,AI编程工具的付费意愿与需求强度有待验证。其次,“开源”是一把双刃剑,虽有利于建立信任和生态贡献,但也可能削弱其短期商业化潜力,并依赖社区持续维护。当前近乎空白的评论区的确反映了产品初期的冷启动困境,或说明其曝光度与社区互动严重不足。

真正的考验在于其AI模型对Roblox庞大、独特且文档可能不完善的API的理解深度。能否真正理解Roblox的客户端-服务器模型、安全过滤机制等复杂概念,而不仅仅是简单的语法提示,将决定它是“玩具”还是“利器”。在Roblox平台自身也在探索AI工具的背景下,STUD需快速迭代,建立足够深的技术壁垒与开发者口碑,否则极易被内置方案或更大规模的AI工具集成所淹没。其路径应是成为Roblox开发领域的“Cursor”,但征途才刚刚开始。

查看原始信息
STUD
Open-source AI coding assistant with deep Roblox Studio integration. Edit Luau scripts, manipulate instances, query DataStores, and search the Toolbox.
Why a durian? Lol
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@andresolarte Why not :)

Tbh, I don't know why we picked it, just needed a logo for the moment and it stuck 😅

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#17
Deckary
The AI consulting toolkit for PowerPoint
79
一句话介绍:一款集成在PowerPoint内的AI咨询工具包,通过AI快速生成专业咨询幻灯片,并内置高级图表和图标库,解决了咨询、金融等专业人士在制作高质量演示文稿时耗时耗力的核心痛点。
Productivity Analytics Consulting
PowerPoint插件 AI幻灯片生成 咨询工具 图表工具 效率工具 MBB背景 办公生产力 演示文稿 Excel集成 设计美化
用户评论摘要:目前有效评论较少。主要有一条评论肯定了产品的美观与实用性,但同时提出了一个关键竞争性问题:与微软Copilot相比,其核心价值主张是什么?这反映了用户对产品在AI办公生态中的独特定位存在疑问。
AI 锐评

Deckary与其说是一个单纯的AI幻灯片生成器,不如说是一个带有浓厚“咨询血统”的PowerPoint效率武器库。其真正的价值,并非泛化的“AI做PPT”,而是精准地封装了顶级咨询公司(MBB)的方法论与审美范式。

产品最犀利的切入点在于“咨询质量”(consulting-quality)这一承诺。这意味着它生成的并非普通幻灯片,而是符合麦肯锡、贝恩等机构苛刻标准的分析框架、数据叙事逻辑和视觉呈现。这直接击中了广大咨询从业者、投行分析师以及企业战略部门员工的痛点:如何将复杂的分析快速转化为董事会认可的专业演示。其内置的瀑布图、梅科图等高级图表,并强调与Excel的动态链接,正是咨询分析核心工具的数字化平替,这比简单的图文生成门槛更高、价值更专。

然而,其面临的挑战同样尖锐。正如用户评论所问,在微软Copilot全面嵌入Office的背景下,Deckary的独立插件价值何在?其护城河可能正在于其“垂直专业性”。通用AI助手(如Copilot)擅长广度,但未必深度理解“咨询幻灯片”的特定语汇与结构。Deckary由前MBB顾问构建,其AI模型很可能针对该领域进行了深度训练和优化,这是通用工具难以短期复制的。它的风险在于,如果微软未来将类似功能深度集成,其生存空间将被挤压。

因此,Deckary的成败关键在于能否将“咨询工具包”的定位做到极致,并快速建立行业内的口碑和生态。它需要证明,自己不仅是PowerPoint的一个功能补充,而是提升专业服务工作者核心竞争力的“必备软件”,从而在巨头的阴影下找到不可替代的利基市场。

查看原始信息
Deckary
Deckary is a PowerPoint add-in that gives you a complete consulting toolkit — right inside PowerPoint. Describe what you need, and the AI Slide Builder generates consulting-quality slides in seconds. Add Waterfall, Mekko, and Gantt charts linked to Excel. Drop in icons from a library of 2,000+. Speed up your workflow with keyboard shortcuts for alignment and formatting. Built by ex-MBB consultants. One-click install, Mac and Windows.

It looks useful and aesthetically pleasing, what is the main value proposition in a comparison to Microsoft Co-Pilot?
Good luck!

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#18
yottoCode
Claude Code, meet Telegram.
79
一句话介绍:一款原生macOS应用,将Claude Code智能体与Telegram无缝桥接,让开发者能通过手机远程管理开发工作流,解决了开发者被束缚在电脑前等待AI响应的核心痛点。
Productivity Software Engineering Artificial Intelligence
AI编程助手 远程开发 macOS应用 Telegram集成 语音交互 工作流管理 开发者工具 Anthropic生态 人机交互创新 效率工具
用户评论摘要:用户反馈积极,认可其解放开发者的核心价值,对表情反应提升效率的设计表示赞赏。主要关注点集中在安全性(如路径和密钥泄露风险)以及对Anthropic平台条款的合规性。开发者回应称基于官方SDK构建,且免费使用。
AI 锐评

yottoCode表面上是一个连接工具,实质上是对AI辅助开发范式的一次小型革命。它敏锐地抓住了当前AI编程代理工作流中的一个关键断层:高智能的Claude Code被禁锢在CLI中,而人类开发者是移动的。产品通过Telegram这个最高频的移动接口,将“监控-反馈-授权”这个原本需要守在电脑前的环节彻底移动化,其价值远不止于“远程控制”。

其真正犀利之处在于对交互密度的重构。引入“表情反应作为低摩擦确认”和语音消息,这并非花哨功能,而是针对大模型token成本和响应速度的精妙优化。它用极低的交互成本维持了人机协作的“连接感”,使开发者可以真正心无挂碍地离开工作站,这或许会催生一种新的、更松弛的“后台式”开发心态。

然而,其光环之下暗藏隐忧。最大的命门在于安全性与隐私。将开发环境(即便是经过筛选的提示)推向Telegram此类第三方平台,无异于打开了潜在的攻击面。评论中关于路径与秘密泄露的担忧极为关键。尽管团队声称使用官方SDK,但这仅解决了合规问题,而非数据链路的安全问题。产品的成败,将取决于其权限控制与信息过滤机制的严格程度,这需要极度透明和坚固的设计。

此外,其模式高度依赖于Telegram的生态与Anthropic的政策稳定性,存在明显的平台依赖风险。它目前更像一个精巧的“功能插件”,而非一个独立产品。长远来看,其理念——即移动端轻量级交互层与桌面端重型AI智能体的协同——极具前瞻性。若能抽象出一套安全协议与跨平台标准,其想象空间将远超一个单一的桥接工具。

查看原始信息
yottoCode
A native macOS app that bridges Claude Code and Telegram — built on the official Anthropic Agent SDK. Full agent controls from Telegram. Voice in, voice out, permission keyboards, session resume — all built in.
Makers here! 👋 We built yottoCode because we got tired of being chained to our laptops while Claude Code was doing its thing. The idea started simple: what if Claude Code could talk to you through Telegram? But it evolved into something more interesting — Claude doesn't just send you text updates, it can react to your messages with emoji reactions when a full reply isn't needed. It's a surprisingly token-efficient way to communicate, and it genuinely feels like a new channel of expression. Some things you can do with it: - Ask Claude to screenshot your simulator or website remotely (via MCPs) - Send voice messages to Claude and get voice messages back - Manage your entire dev workflow from your phone, anywhere The only thing keeping you at your desk was Claude Code CLI. yottoCode breaks that constraint — and it works on your existing Claude Code subscription, no extra cost. Would love to hear how others are using it! 🚀
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@muhamad_jawdat_akoum Stepping away mid-run is when the permission prompt hits and Claude Code just waits. yottoCode moving the loop into Telegram, plus emoji reactions as low-friction acks and voice notes for intent, feels like the right direction. If reactions can map to approve, pause, cancel, does it also keep a tight allowlist plus redaction so paths and secrets don't leak? That combo would make phone-first runs feel safe.

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@muhamad_jawdat_akoum Love the remote dev workflow idea! The emoji reactions for token efficiency is clever.

Question: How do you handle security with Telegram integration? Curious about the architecture since I'm new to this space.

Also just launched my first app today (FireBlazer) - fellow first-time maker! 🚀

Upvoted yottoCode!

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Congrats on the launch, @muhamad_jawdat_akoum !

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Congratulations @muhamad_jawdat_akoum Its awesome!! Definitely helps covering the bridge in between. I’m making something similar, could you tell me if YottoCode is compliant with Anthropic’s terms?
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@_anasansari we use the official Anthropic Claude Agent SDK. no workarounds.

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@_anasansari you can use yottoCode for free!

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Use Native telegram UI for Claude Code

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#19
Konta
GitOps for Docker Compose on low‑resource VPS
78
一句话介绍:Konta是一款在低资源VPS上,通过GitOps理念管理Docker Compose应用状态的工具,为管理中小型基础设施的开发者解决了手动部署繁琐、缺乏版本控制和一致性的痛点。
Open Source Developer Tools GitHub
GitOps Docker Compose VPS管理 轻量级部署 容器同步 基础设施即代码 开发运维 自动化 版本控制
用户评论摘要:开发者阐述创作初衷,满足小项目管理需求。用户主要关注故障处理机制,如部分服务更新失败时的回滚策略。开发者回应目前部署失败会整体回滚,并计划未来增加健康检查功能以实现更精准的状态判断。
AI 锐评

Konta瞄准了一个精确定位的缝隙市场:那些用着低配VPS、跑着几个Docker Compose服务,既用不起也配不动K8s,却又受够了手动SSH和复制粘贴的独立开发者或小团队。它的核心价值在于“极简的GitOps实践”,将复杂的集群管理概念降维到单机与Git仓库的直连同步,这既是其最大的优势,也是其潜在的天花板。

产品逻辑清晰且克制:以Git为单一事实来源,用Docker Compose这一已被广泛接受的格式作为配置界面,实现了“推送即部署”。它巧妙地避开了构建镜像、服务发现等复杂环节,只做状态同步这一件事。这种克制使其资源消耗极低,契合目标场景。从评论中的开发者互动可以看出,团队对产品边界有清醒认识,当前专注于可靠部署,而对健康检查、灰度发布等高级功能持谨慎态度。

然而,其“无控制平面”的设计在简化架构的同时,也意味着在管理多台VPS时,每台服务器都需要独立安装并配置Konta,无法进行集中观测和统一策略管理。此外,其回滚机制目前仍停留在“全有或全无”的堆栈级别,面对评论中提到的多服务独立更新失败场景,缺乏更精细的管控能力,这可能会阻碍其在稍复杂场景下的应用。

总体而言,Konta并非一个颠覆性的新框架,而是一个高度优化的自动化脚本的优雅产品化封装。它证明了在云原生工具链的“重型装甲”之外,市场依然需要一把“瑞士军刀”。它的成功与否,取决于有多少开发者正深陷于它所针对的那种“轻量级混乱”之中,并愿意为这种极简的秩序买单。对于追求极致简单、项目结构清晰的小型部署,Konta是一个优雅的解决方案;但对于需要跨服务器协调或具备复杂发布流程的场景,它可能很快会显得力不从心。

查看原始信息
Konta
Store the state of your VPS containers in a repo. Konta helps you use Git as a single source of truth, automatically sync changes with server containers using docker-compose files — no cluster, no control plane. Simply push changes to Git, and your containers will be updated automatically.
Hi everyone. I created Konta because I manage several small VPS servers with projects for which using Kubernetes or similar tools is simply not an option. I needed: - Git as a source of truth - Simple application configuration via Docker Compose - Automatic update deployment - No unwanted migration of a bunch of new config files So I created Konta. It's designed for developers who manage small and medium-sized infrastructure and want reproducibility without the hassle. It's a tool for servers with few resources and simpler tasks where powerful cluster utilities are overkill. You install it on your VPS, connect your Git repository, and it syncs all applications to your server according to the repository's instructions. It also keeps the list of containers up-to-date. I'd really appreciate your feedback: How interested are you in the GitOps approach for small projects? What would prevent you from using it for your needs? How often do you install, configure, and update applications on servers from scratch and what tools do you use? Thank you for your attention 🙌
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How does Konta handle a partial failure mid-sync, say one service in the compose file fails its health check while the others come up fine? ConOps and Composed do the git-pull-and-redeploy loop well, but rollback on a per-service basis without tearing down the whole stack is still manual. If Konta tracks which services changed between commits and rolls back just those, that'd set it apart for multi-app VPS setups. The no-config-migration constraint is smart... every Portainer or Coolify install ends up with more yaml managing the manager than the actual apps.

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@piroune_balachandran Thanks for the question and minds!

At this moment Konta used only for deployments to automate manual steps. If a deployment fails, the stack update is considered unsuccessful. So you don’t end up with a half-switched infrastructure state. Konta tracks which services changed between commits and redeploys only changed.

I want to implement health-check feature after deployment. Because now it only verifies that containers are in a running state. With this feature Konta could decide that new vps state is broken and deployment was failed.

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#20
Cencurity
Security gateway for LLM agents
77
一句话介绍:Cencurity是一个安全网关,为生产环境中的LLM智能体流量提供实时敏感数据检测与掩码、风险代码模式拦截及全量审计日志,解决了AI智能体行为不可控、无审计追踪的安全痛点。
Open Source Developer Tools Artificial Intelligence GitHub
AI安全 LLM智能体 安全网关 数据防泄漏 审计日志 实时监控 本地部署 代理服务 生产环境防护 提示词注入防护
用户评论摘要:开发者关注智能体调用生产API带来的真实风险,建议网关应支持不安全调用的熔断、关键操作的监督模式,并询问是否支持细粒度的权限控制与数据脱敏。同时建议集成OpenTelemetry以对接现有安全监控体系。
AI 锐评

Cencurity切入了一个精准且迫切的细分市场——LLM智能体生产安全。传统应用安全方案确实难以覆盖智能体的动态行为风险,如提示词注入导致的越权工具调用、敏感数据在交互中泄露、以及缺乏可追溯性等“不可见”操作。产品将安全网关范式迁移至AI智能体层,试图在流量通道上实现实时检测与阻断,本质上是为混乱的智能体行为建立“交通规则”与“黑匣子”。

其核心价值并非技术创新,而是工程化整合与场景化应用。通过代理架构、本地化部署和审计日志,它直接回应了企业级客户对数据主权、合规审计和风险可控的核心诉求。然而,其成功高度依赖于策略引擎的精准度与覆盖度:能否准确识别多变的敏感数据模式和“危险代码”?能否在低误报率下实现有效阻断?评论中提及的“每工具每动作的权限范围”和“OpenTelemetry导出”恰恰点中了要害——企业需要的是能无缝嵌入现有运维与安全体系的可观测方案,而非又一个孤立的安全孤岛。

长远看,此类产品可能面临两重挑战:一是上游LLM服务商或智能体框架可能逐步内化基础安全能力,削弱独立网关的中间层价值;二是安全策略的维护成本会随智能体复杂度的提升而剧增。Cencurity若想构筑壁垒,需在策略智能性、行业特定规则库及与开发生态(如LangChain、LlamaIndex)的深度集成上建立优势。它当前是应对AI智能体“野蛮生长”阶段的一剂及时药,但未来必须进化成智能体原生安全架构的神经系统。

查看原始信息
Cencurity
Cencurity is a security gateway that proxies LLM/agent traffic and detects / masks / blocks sensitive data and risky code patterns in requests and responses, while recording everything as Audit Logs.
Hi Product Hunt! I’m one of the makers of Cencurity.\n\nAs we started shipping LLM agents, we realized traditional app security doesn’t cover agent behaviors: prompt injection, unsafe tool calls, data leakage, and “invisible” actions with no auditability.\n\nCencurity helps teams add guardrails + audit trails for agent actions in production.\n\nWould love feedback—what’s the scariest failure mode you’ve seen with agents, and what integrations would you want next?
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@vlad1323 Letting an agent touch prod APIs is where it gets scary, a prompt injection can turn into real side effects. Cencurity as a security gateway makes sense if it can fail closed on unsafe tool calls, force supervised mode for state changes, and keep an audit trail tied to user identity. Does it support per-tool, per-action scopes plus redaction at the gateway? An OpenTelemetry export to your SIEM would make adoption way smoother.

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Small technical note for builders interested:

Cencurity runs as a proxy in front of OpenAI-compatible APIs and inspects both inbound tool calls and outbound responses in real-time.

It can block dangerous code patterns before execution and keeps full audit logs for every policy match.

Everything runs locally via Docker, so teams can self-host without sending data to external services.

Happy to answer any technical questions.

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