Product Hunt 每日热榜 2025-12-04

PH热榜 | 2025-12-04

#1
Pylar
Securely connect your entire data stack to any agent
485
一句话介绍:Pylar是一个在AI代理与结构化数据栈之间提供安全治理层的平台,解决了企业在将AI代理接入敏感生产数据时面临的安全泄露和成本失控两大核心痛点。
Developer Tools Artificial Intelligence Security
AI代理安全 数据访问治理 MCP工具 数据沙箱 查询管控 审计日志 数据栈集成 AI安全 企业级AI 访问控制层
用户评论摘要:用户普遍认可其解决“代理访问数据库混乱”的痛点,尤其关注成本控制(查询限流、费用封顶)和权限动态管理。创始人详细回应了技术实现,并引用真实安全事件佐证产品紧迫性。
AI 锐评

Pylar切入的并非一个痒点,而是企业规模化部署AI代理时必然遭遇的“阿喀琉斯之踵”:安全与效用的根本矛盾。当前方案,无论是使用来路不明的开源MCP服务器,还是自建脆弱的API包装层,都是在“裸奔”与“锁死”两个极端间摇摆。Pylar的价值在于提出了一个范式性的中间层——将数据访问从“权限点”管理升级为“视图沙箱”治理。

其真正的犀利之处在于三点:首先,它用“沙箱视图”替代原始数据访问,从根本上划定了代理的行为边界,将安全防线大幅前移。其次,它巧妙利用了MCP(模型上下文协议)这一新兴但日益重要的标准,将自己定位为标准化、可观测的工具生成器,而非又一个封闭平台,这极大地提升了其兼容性和采用潜力。最后,其“控制平面”的设计理念意味着策略可集中定义、动态生效,这符合现代基础设施的治理要求。

然而,其挑战同样明显。它本质上销售的是“控制”与“信任”,这需要极深的产品成熟度与安全背书才能让大型企业买单。此外,其商业模式可能面临上游(云数据平台)和下游(AI代理平台)的挤压。如果Snowflake或Databricks等数据平台决定内建类似功能,Pylar的独立价值将受考验。总体而言,这是一个在正确时机切入关键缝隙的产品,但其长期成功取决于能否将技术方案转化为不可替代的合规与运营标准。

查看原始信息
Pylar
Pylar connects agents to your data stack, safely. Connect to any datasource, define exactly what an agent can see, turn those views into custom MCP tools, and publish them to any agent builder - with full observability across every AI deployment.

👋 Hey everyone, I'm Hoshang, Co-founder of Pylar.

Super excited to finally share what we’ve been building.

Agents today are great at reading docs, invoices, websites, transcripts -
but the moment you want them touching structured systems where sensitive customer data is stored e.g Snowflake, Postgres, CRMs… things get tricky.

We kept hearing the same two blockers over and over:

  • Agents may over-query and silently spike warehouse bills

  • Agents are at a risk of leaking sensitive data (PII, financials, customer history) because access isn’t properly scoped

And right now, teams have two options:

- Off-the-shelf MCP servers : 18,000 exist, ~10% are malicious, and most are exploitable or too generic for production.
- Custom API wrappers : months of engineering bandwidth used up in building endpoints, policies, and governance… all brittle, fragmented, and hard to audit.

This forces companies into a painful choice: lock agents down so much they become useless, or open things up and risk a security incident.

Traditional database ACLs weren’t designed for autonomous systems. Custom APIs are hard to build, govern and control for agent level interactions.

Pylar exists to fix this. It’s a governed access layer between your agents and your entire data stack.

You connect your datasources → define sandboxed SQL views → turn them into MCP tools → ship them to any agent builder… all from one control plane, with full observability.

What you get out of the box:

  • Agent-specific sandboxed views (never raw DB access)

  • Enforced permissions & guardrails

  • Automatic breach containment + audit logs

  • Publish to any agent builder (n8n, Cursor, Claude, LangGraph, etc.) via a single secure link

We’re already working with some fantastic data, platform, and security teams - everything from internal analytics copilots to customer-facing AI features wired directly into production data.

If you’re exploring structured-data access for agents, I’d love to hear your thoughts, help you build your use case or just share best practices on what we've been seeing with our customers. You can book a call with me here if you'd like.

Thanks for checking us out — means a lot. 🚀

- Hoshang
Co-founder, Pylar

17
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@hoshang_m Love that you’re tackling agent over‑querying, feels like a pain everyone’s quietly dealing with right now.

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@hoshang_m Congrats on the launch! The UI looks super clean. I'm launching my own app today too, so I know how much work goes into this.

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Congrats on the launch @hoshang_m and team! Seems like you're threading the needle between agentic adoption and security risk. Great work 👏

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Hey Hoshang, congrats on the launch! That stat about 10% of MCP servers being malicious is wild. I’m curious was there a specific moment that made this feel urgent for you? Like did you witness (or hear about) an agent accidentally exposing customer data, or maybe a team get hit with a surprise warehouse bill they didn’t see coming?
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@vouchy Thanks for the question, Van! Instances of agents leaking sensitive data is on the rise, recently Salesforce had a security incident where their ai agents accidentally leaked sensitive crm data through through their agentforce powered web-to-lead form. attackers injected a malicious prompt on website forms to make the AI share internal data with outside domains.

basically, hiding malicious instructions inside normal text. the ai read it… and pulled private data it had permission to see. I did a deep dive here, you might find this interesting - https://www.pylar.ai/blog/forcedleak-salesforce-agentforce-vulnerability-deep-dive

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Finally, someone tackling the agent-to-DB mess. I’ve nursed a painful Snowflake bill from a runaway agent. Sandboxed views + audit logs feels sane. How do you cap query spend per agent? Might wire this into Cursor first, then LangGraph if it holds up.

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@alexcloudstar Thanks Alex! Right now, we cap spend in two ways:

1. Every agent only sees a sandboxed view, never your raw warehouse.
So even if it tries something wild, it can’t fan out into expensive tables or join half your schema.

2. Query-level guardrails on the tool itself.
We let you set limits on row counts, frequency, and even block certain patterns (e.g. unscoped scans) via policies. If an agent tries to exceed it, Pylar shuts it down and logs the attempt.

On top of that, you get full audit logs + costs per tool call so you can see exactly which agent is expensive before the bill shows up.

Looking forward to having you try us out!

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Congratulations on the launch 🎉 🎉 !!

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@shubham_pratap Thanks for the support!

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@vishalbajaj Great product! All the best for your launch 🎉

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@zethleezd Thank for the support 🙌🏼🙌🏼
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@zethleezd appreciate your support Zeth

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Does Pylar throttle or rate-limit agent queries in any way? Congrats on the launch.

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@himani_sah1 Great question and thanks for the support. Rate limiting queries is going to be live on the product next week, but for now you can set additional guardrails like row limits and scoped filters with policies between your data and the mcp tools so an agent can’t over-query or wander outside the slice of data you’ve exposed. And every attempt gets logged so you can see if an agent is starting to push its boundaries.

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Congrats on the launch @hoshang_m this solves a serious gap for teams working with sensitive, structured data. I’m curious how Pylar handles evolving permission needs over time. If schema or data-access policies change, can sandboxes and guardrails adapt without teams rebuilding the entire setup?

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@harkirat_singh3777 Thanks for your support! The sandboxed view is the “source of truth.” If your schema changes or your data-access rules shift, you just update the view in Pylar - the agents automatically start using the new version. No redeploying, no rebuilding tools, no touching the agent builder again.

We basically treat it like a control plane: you tweak the view or the policy once, and every connected agent adapts instantly.

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This is pretty cool, I have been working with some fintech companies and the sheer volume of data they have is ginormous.

I love how it abstracts the base layer queries and have complex queries converted to tools. amazing job guys! Will try it for sure

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@ashish_dogra oh yes, we’ve been working with a few fintech companies as well and are seeing good results. We should chat!
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@Pylar Congrats on the launch! Securely connecting entire data stacks to AI agents is exactly what teams need as AI adoption scales.

Data security and access control are critical when agents interact with sensitive information. How does Pylar handle permission management across different data sources?

Are developers able to set granular access rules for specific agents or use cases? Curious about how the authentication flow works when connecting multiple platforms.

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@vimal_polara2 Pylar basically sits between your data sources and agents- you create sandboxed views from your sources, and each agent only gets access to the exact slice of data you choose. You can then create MCP tools that basically define how the agent is going to interact with this data view- all the permissions and controls, policies are set here. If something changes (schema, policy, whatever), you just update it once in Pylar and all your agents pick it up instantly. And on auth, we connect to your sources normally(OAuth/keys) but agents never see those creds. They just get a secure MCP server link to the governed view. Makes sense?
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I could see how integrating Pylar’s AI-driven workflow automation could streamline content and data processes inside our tool, and I’ll go check it out to explore the possibilities.

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@jamesjacksonleachatx that’s awesome! Please let me know if you need help ironing out your use cases.
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It's an amazing idea. So can the agent run analytical queries in the DB as well?

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@chilarai agents can run analytical queries, but only within the sandboxed view you expose to them.

So if you include things like aggregates, joins, or computed fields in that view, the agent can use them freely. What it can’t do is hit your raw warehouse or run heavy, unscoped analytics outside the boundaries you’ve set.

Think of it like giving the agent a curated data view purpose built for the agent to do its task well.

Here's more on this- https://docs.pylar.ai/learn/creating-data-views/overview

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congrats on the launch!

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@marek_nalikowski Thank you!

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amazing product guys well done !!

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@othmane_khadri Thank you for your support!

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Congratulations @hoshang_m
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@neelptl2602 Thanks Neel!

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@hoshang_m Congratulations. And happy product launch.

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@huisong_li Thank you! 🙌🏻

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@huisong_li thank you for your support Huisong!

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Congrats Hoshang! Pylar seems like a huge step forward for safely connecting agents to structured data.

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@abod_rehman Thanks for the support, Abdul!

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How do you monitor agent behavior across different builders (Cursor, LangGraph, n8n, etc.) from one place?

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@nuseir_yassin1 Our evals layer helps you measure how different agents across platforms like Cursor, LangGraph etc are interacting with your internal data.

Because of that, you get a single place where you can see:

  • what each agent is querying

  • how often it’s hitting your data

  • what was allowed vs blocked

  • and any odd behavior you should know about

So even if one agent is in Cursor and another is in LangGraph or n8n, all their activity shows up in one dashboard.
Also, if you update a data view, a rule or add more mcp tools in Pylar - every agent using it automatically follows the new version.

More on this here - https://docs.pylar.ai/learn/evals/evals-dashboard

Does this help?

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Custom APIs are a nightmare and MCP servers are a minefield. This feels like the first real governed layer built for agents. Good work!

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@zerotox Thanks for your support!

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Pretty amazing @hoshang_m. Congratulations on the launch. I will surely give it a shot
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@thepmfguy Amazing! Thanks Gaurav. Do let me know if you need anything!

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Don't fully understand what this is. What's the top 3 use cases for this?

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This tool caters to teams building or deploying AI agents: it lets agents leverage internal data (to deliver context-rich outputs) while maintaining strict control over data access—addressing both efficiency and risk management needs.

Do you plan to expand compatibility to niche or industry-specific datasources (e.g., healthcare EHR databases, financial ledger systems) for specialized use cases? Also, will Pylar include pre-built access control templates aligned with common compliance frameworks (e.g., HIPAA, GDPR) to accelerate secure setup for regulated industries?

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Great launch. congrats. Do you have custom guardrails option too?

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@ashish_dubey11 Thanks for your support Ashish. We do have Query-level guardrails on the tool itself.
We let you set limits on row counts, frequency, and regulate access via policies. If an agent tries to exceed it, Pylar shuts it down and logs the attempt. Are there any more guardrails that you would like to add between your data sources and the AI agent?

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Congrats on the launch. Do you have any list of data sources currently supports?
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@sriramg appreciate your support Sriram. We support a wide range of databases, data warehouses and Business Applications. The list of supported data sources can be found here - https://docs.pylar.ai/learn/making-connections/supported-data-sources.

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Congratz on the launch team! With agentic AI this will be a must.

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@mertbaser Thanks for the support, Mert! Would love to have you try Pylar out!

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congratulations for your product!!

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Love what Pylar is solving. As someone who works with founders handling fast growth + ops, I know how often “data safety + speed” becomes the invisible pressure behind the scenes.

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Awesome! Is it possible to have an agent that sync my Notion page with notes of different customers to my CRM system Attio?

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#2
GNGM
The sleep habit app for night-owls trying to reset
378
一句话介绍:一款为夜猫子设计的极简睡眠习惯应用,通过每日一次无压力的睡前打卡,帮助用户在自然放松的场景下重建规律作息,解决因过度追踪和复杂数据带来的睡眠焦虑。
Android Health & Fitness Productivity Fitness
睡眠健康 习惯养成 极简主义 夜猫子 心理健康 数字健康 无数据追踪 正念 生活方式 移动应用
用户评论摘要:用户普遍赞赏其极简、无压力的设计理念,认为它精准击中了传统睡眠应用数据过载的痛点。主要问题集中于功能细节:如睡眠节奏是否支持自由模式、提示是否会自适应、如何无追踪衡量进展、以及未来是否会增加个性化建议等。开发者回复积极,阐释了产品哲学。
AI 锐评

GNGM的出现,与其说是一款睡眠工具,不如说是对当前“量化自我”风潮的一次精巧反叛。它敏锐地捕捉到一个关键矛盾:旨在改善健康的追踪技术,其本身的数据负担和绩效压力反而可能成为健康的新威胁。产品将“睡眠”从需要优化和打分的技术问题,重新定义为需要仪式感和一致性滋养的自然节律,这切中了一部分对科技产生倦怠的用户的心理。

其真正的价值在于“减法哲学”:放弃监测生理数据这种看似科学却可能增加焦虑的“伪掌控感”,转而锚定“行为习惯”这一更底层、更可控的变量。通过一个极简的打卡动作,它试图重建用户与睡眠之间的直觉连接,而非依赖外部数据的中介。这种设计隐含了一个大胆的假设:对于睡眠紊乱,认知和行为上的“松绑”比更精细的监控更有效。

然而,其挑战也同样明显。在抛弃了客观数据后,其激励体系和效果验证将高度依赖主观感受和用户心流,这可能削弱长期坚持的动力,并让产品效果难以自证。评论中关于“自适应”和“个性化”的询问,也预示着用户在被初始理念吸引后,最终仍会期待智能化的深度服务。GNGM目前成功地树立了一个鲜明的对立面,但如何在坚持“无压力”核心的同时,满足用户进阶的、不可避免的“进步”需求,将是其能否从新颖概念成长为持久解决方案的关键考验。它更像一剂针对科技焦虑的“解毒剂”,但其长期疗效,仍需观察。

查看原始信息
GNGM
GNGM helps night-owls rebuild a gentle, consistent sleep rhythm with one simple nightly check-in. No trackers, no pressure, no data overload — just a calming routine that helps your body reset naturally.

Hi PH! 👋

We’re the makers of GNGM — a tiny habit for big sleep wins. After struggling with irregular sleep and feeling overwhelmed by trackers and metrics, we built something deliberately simple: one short, calming check‑in each night that helps night‑owls rebuild a consistent rhythm without pressure or data noise.

Why GNGM?

  • No trackers, no wearables: nothing to sync or monitor.

  • No shame or strict rules: a gentle routine, not a regime.

  • Designed for night‑owls: realistic prompts and timing that respect your lifestyle.

  • Minimal, calming feedback so you can see progress without getting obsessed.

How it works

  1. Quick nightly check‑in

  2. Subtle cues and nudges to help you wind down and establish consistency.

  3. Lightweight progress signals over time — enough insight to keep you motivated, never overwhelming.

We built GNGM because small, consistent rituals beat massive overnight changes. It’s for people who want to feel better rested without turning sleep into a full‑time project.

We’d love for you to try it and tell us what you think — what helped, what felt off, and any features you’d actually use. Ask us anything below; we’re excited to hear from other night‑owls and sleep-curious folks.

Thanks for checking us out!


— The GNGM team

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@justin2025 Justin, I stayed up till 2am doomscrolling last night, and dragged thru work today.

If GNGM can help me break my late-night habit, I'll call you my eternal hero!

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@justin2025 Always love seeing new tools in this space. Congrats on the ship! I'm in the trenches with you today (launched my app too), hope the algorithm treats us well!

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@justin2025 seems exactly what i need!

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This launch feels different for me tbh. I pulled way too many late nights building GNGM and kind of… burned myself into making a sleep app 😂


Pretty happy I don’t have to stay up that late anymore. Hope it helps you sleep better than I did while coding it.

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@polman_trudo  Haha please don’t believe him — he absolutely will keep staying up late, just on new features instead 😭

But seriously, it’s been fun building this together.

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Looks polished! Does it support "free-running" sleep rhythm?

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@conduit_design Love this question — and the short answer is:

yes, you can use GNGM even if your sleep cycle isn’t tied to the usual day/night schedule.

The routine is anchored to your chosen bedtime, not the world’s.

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Congrats on the launch

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Love the minimalist approach! Finally, a sleep app that doesn’t overwhelm with data. Subtle, soothing, and made for night owls — I’m in. 🌙

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Do the nightly prompts adapt over time based on my habits, or stay consistent?

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@abod_rehman They stay simple and consistent for now — because consistency is the magic.


That said, we do subtly adjust the flow based on whether you’re building momentum or losing it.


More adaptability coming soon!

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Wow using Suno for sleep sounds was super smart. Looks like it’ll be the norm for all kinds of use cases like this. Congrats on the launch!

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@thisiskp_ Thank you for the support, KP!


Yeah, Suno opened a whole new world for us — instead of stock sleep sounds, we can craft something that feels more personal, warmer, and a bit magical.

Right now we’re mixing custom ambient loops + gentle melodic textures made with Suno, and users have been loving the vibe.


More soundscapes are on the way too — can’t wait to share them!

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Congratulations on the launch 🎉 🎉 !!!!

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@shubham_pratap Thank you so much! 🎉

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Finally see a product like this! Sleeping is normal, but good sleeping is a big challenge. Hope this app can solve my problem

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@vincentwu800 Absolutely — sleeping is easy, sleeping well is the boss fight.


Really hope GNGM gives you that calm, gentle push you’ve been needing.

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Love the “no pressure, no trackers” approach. I’m a night-owl who’s failed at every strict sleep routine, so this feels really refreshing. Downloading now.

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@sandy_liusy Ahh a fellow night-owl


Same here — strict routines never worked for me either, so we designed GNGM to feel more like a gentle nudge than a checklist you can fail.

Hope it brings a bit more calm to your nights. Let me know how it feels after a few days — we’re building this with people exactly like you in mind.

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@jotzilla @polman_trudo Nice approach to sleep improvement without overwhelming users. I’m curious how GNGM measures progress in a meaningful way without relying on trackers, what signals or habits indicate someone is actually improving their sleep consistency?

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@harkirat_singh3777 Great question — and honestly something we thought about a lot while building GNGM.

Our approach is: measure the habit, not the data noise.

Instead of tracking heart rate or sleep stages (which often look scientific but aren’t super actionable), we focus on a few meaningful signals that actually reflect consistency:

• Nightly wind-down check-ins
Did you prepare for sleep at roughly the same time? This reflects the real start of your sleep rhythm.

• Morning reflection
Are you waking up roughly on schedule? How rested do you feel? These simple, self-reported signals correlate surprisingly well with long-term sleep stability.

• Habit streak & stability score
We track how often you hit your bedtime intention and how stable your pattern is over time — this is the strongest predictor of improved sleep quality.

• Gentle trends, not judgment
No “bad sleep” labels, no pressure. Just slow, steady progress toward a more regular rhythm.

Think of it less like “tracking sleep” and more like “training your internal clock.”

If you try it, I’d love to hear how it feels for you. Your feedback helps us shape GNGM into something genuinely supportive.

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@justin2025 Congrats on the launch 🚀

Can you please tell me how GNGM breaks our late night habits ?

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@aliena 

Thanks so much! Great question — and honestly, this is the core of GNGM.

We don’t try to “fight” your late-night habits with guilt or pressure.


Instead, GNGM works in three super simple ways:

1) A nightly wind-down check-in
Just one tiny action that tells your brain, “hey, the day is ending.”
It’s surprisingly powerful for resetting your rhythm.

2) Gentle bedtime reminders
Not aggressive alarms — just a nudge at the time you choose, helping you avoid the usual doom-scrolling spiral.

3) A calm space for sleep


Ambience + minimal UI so you naturally slow down instead of getting stimulated by screens.

No tracking, no charts yelling at you — just consistent tiny cues that help your body remember what “night time” feels like again.

If you try it tonight, I’d love to hear whether it helps you shift your bedtime even a little.

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Do you plan to add optional, low-intensity insights (e.g., mood/energy tracking) for users who want gentle feedback without data overload? Also, will the app include personalized, gradual bedtime shift recommendations tailored to individual night-owl patterns?

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How exactly does this software help night owls?

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The consistency and rituals actually work better! Really like the idea!

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Congos on the launch @justin2025

Dowloaded on android, see if you add setting to enable grayscale mode before bedtime

that will help me as a user.

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What a great tool! Congratulations. Sleep is so important and most of we ignore it.

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@justin2025 The sleep habit app for night owls is such a practical concept! Resetting sleep schedules is incredibly difficult, especially for people with naturally late chronotypes.

Love that this focuses on habit formation rather than just tracking. How does GNGM help users gradually shift their sleep schedule without disrupting their daily routines?

Are there specific techniques or nudges built in to make the transition smoother? The big sleep wins idea resonates!

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congrats on the launch! love the design

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Really love the vibe and mission behind GNGM. As someone who naturally leans toward late nights, the idea of a gentle, no-pressure nightly check-in instead of data-heavy trackers feels refreshing — it’s exactly what many “night-owls” like me need. The simplicity (no wearables, no complicated charts) is a strength: just a calming routine to help reset your rhythm. Looking forward to seeing how consistent use can reshape my sleep habits.

Do you plan to add customizable reminders or optional “wind-down rituals” (e.g. light stretching, breathing prompts, soft audio) to make the nightly check-in even more helpful?

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need this so bad
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@hehe6z Thanks for the support, Helena! Hope it helps you wind down a bit easier tonight!

BTW, we are currently considering adding audio bedtime stories powered by Fish Audio 😉

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looks cool, congrats for the team!

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@youssef_abdelwahed Thank you so much! 🙏

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I could see how our tool could plug into GNGM’s streamlined no-code workspace to simplify automation around our community workflows, so I’m going to take a closer look at this launch and explore the synergy.

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I seriously need this app! havent slept well since building my current project, and hope GNGM could save me out...

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@justin2025 Congratulations. And happy product launch.

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@huisong_li Thanks a lot for the support, Huisong! ❤️

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So the name GNGM means "good night, good morning"?

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@ristan_nakko yessir!

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Do you plan do add a feature like sharing the sleeping time with family?

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@tetiana_hryshmanovska thanks for asking! it's something we're exploring. no ETA yet, but we'll give hints once it's moving from idea to pipeline.

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Night owl here. Kinda burned out on rings/graphs. One simple check‑in sounds… doable. Curious what the wind‑down nudge feels like—like a tiny prompt or more of a ritual? Either way, I could use gentler evenings. Saving to try this week.

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@alexcloudstar glad this resonated. wind-down nudge is just a gentle prompt by design. let me know how it feels when you try it. thanks!

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Congrats on the launch! 👏
I haven’t tried GNGM yet, but the concept immediately stood out to me. Most sleep apps feel heavy with data, graphs, and pressure but this focus on a simple nightly check-in and gentle cues sounds much more realistic for people who just want a calmer routine.

I really like the idea of helping night-owls reset without turning it into another “project.” The minimal, non-judgmental approach feels refreshing.

A few questions out of curiosity:

  1. How did you validate that a single nightly check-in is enough to build consistency?

  2. Do the prompts adapt over time, or are they intentionally kept static to avoid overwhelm?

  3. Are you planning integrations (Apple Health, reminders, etc.) or deliberately staying “no-tracking”?

Looks great - wishing you a smooth launch day! 🚀

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Really nice launch, GNGM team. From a clarity & onboarding lens: when a user opens the app for the first time, what’s the one belief you want them to leave with in the first 10-15 seconds?
Is it:
• “I’m finally doing a simple routine I can stick with.”
Or:
• “This app understands my late-night rhythm and doesn’t judge it.”
Because in habit-change tools, the biggest barrier isn’t features—it’s the user’s belief that change is possible without pressure. Curious how you’re shaping that.

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@joydeep_pandey our aim in those first seconds is to signal that the user is stepping into something simple and supportive -- not pressure-filled with a number of bells and whistles. a sense of "i can actually do this, and it fits how my nights really work." that's the belief we're designing the onboarding around. cheers.

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#3
Documentation.AI
Build and update product documentation effortlessly with AI
369
一句话介绍:一款AI驱动的产品文档平台,通过内置AI代理自动编写和维护内容,并连接开发与支持工具获取上下文,解决了团队创建、更新文档耗时费力且文档易过时的核心痛点。
Developer Tools Artificial Intelligence
AI文档生成 知识库管理 开发运维一体化 SaaS AI助手 语义化搜索 文档即代码 技术支持自动化 产品增长
用户评论摘要:用户普遍赞赏其设计、速度和AI助手功能。核心问题集中于AI代理的自动化程度(主动建议更新)、与Git/支持工具的集成进度、私有化部署、多语言支持以及自定义样式指南。团队回复显示多项关键集成(如Linear、Jira)和自动生成功能“即将推出”。
AI 锐评

Documentation.AI 的发布,精准地刺中了AI时代一个被重新定义的核心矛盾:当AI智能体成为产品使用的主要接口时,陈旧、零散的文档从“成本中心”瞬间变为“增长瓶颈”。产品价值不在于其文档编辑器的体验,而在于其定位——将文档系统重构为“AI就绪”的基础设施。

其真正的犀利之处在于三层设计:第一,它不仅是内容生产工具,更是连接代码仓、支持工单等上下文的“中枢神经系统”,让文档从静态报告变为动态流。第二,它默认输出为语义化结构,直接适配主流AI的MCP协议,这本质上是为ChatGPT、Cursor等智能体铺设专用数据管道,让文档成为AI可高效消费的“燃料”。第三,内置的、提供溯源答案的用户助手,直接将文档从被动查阅转变为主动拦截支持请求的交互层,模糊了文档与客服的边界。

然而,其面临的挑战同样尖锐。从评论看,用户最期待的是全自动、基于事件触发的更新,这要求其AI代理具备极高的代码变更理解与需求提炼能力,目前仍处于“类Cursor”的辅助阶段。此外,其“默认公开Git仓库”的策略暴露了在企业级私有化、安全合规场景下的潜在摩擦。产品的成败将不取决于其写作体验,而取决于其与开发、支持工具生态集成的深度与可靠性,以及其AI代理在复杂信息中识别“需文档化关键点”的精准度。它试图成为AI时代的“文档水管工”,但这个管道能否承受企业级数据流的压力,仍需观察。

查看原始信息
Documentation.AI
Create beautiful, always-current product documentation with AI. A built-in AI agent helps you write and maintain content and connects to dev and support tools for context. Edit via web, AI agent, or docs-as-code. A built-in assistant gives users instant, cited answers, reducing support load.

Hey Product Hunt! 👋

We're excited to launch Documentation.AI, a platform that makes it incredibly easy to build, maintain, and scale beautiful, AI-ready product documentation.

I'm Roop, co-founder of Documentation.AI. Over the past decade, my team and I have built products across video streaming, edtech, AI agents, and more. No matter the industry, we kept seeing the same issue: documentation was always deprioritized, outdated, or both.

But with the rise of AI, documentation has never been more critical. Tools like ChatGPT, Claude, Cursor, and other AI agents are becoming the primary way users discover, understand, and integrate products, and they rely entirely on your docs as their knowledge source. Your documentation isn’t just a reference anymore; it’s a growth channel.

We noticed three big problems teams face:

  1. Creating great docs is hard — designing, writing, and publishing takes forever.

  2. Keeping them current is even harder — docs go stale the moment you ship new features.

  3. Most docs aren’t built for AI — despite AI agents depending on them, they’re not structured for semantic search, embeddings, or MCP workflows.

What makes us different

✨ Ship in under 5 minutes — Beautiful, fast docs out of the box, no design work required.

🔄 Stay up-to-date effortlessly — Our built-in AI agent helps you write and maintain content. It can analyze Git commits, support tickets, and more.

🤖 AI-ready by default — Structured for ChatGPT, Claude, and coding agents with MCP endpoints and semantic markup. Your docs show up where your users actually work.

🛠 Flexible editing workflows — Use our web editor, AI agent, or a code editor/coding agent via a docs-as-code workflow.

💬 Built-in AI assistant — Users get instant, cited answers without leaving your docs, dramatically reducing support tickets.

We'd love your feedback on:

  • What's your biggest documentation pain point today?

  • How do you keep your docs in sync with product/API changes?

  • What would make a tool like this indispensable for your team?

Happy to answer any questions! 🚀

You can also reach us via Slack if you want to chat directly.

50
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@roopreddy shipping in under five minutes feels huge. Do you see teams adopting this for rapid prototyping docs too?

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@roopreddy I absolutely love this!

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@roopreddy Looks clean and easy! Congrats on your launch!

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Congrats on launch! I like that the agent that audits for outdated sections and updates it. Something that a human writer would have done otherwise. :)
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@odeth_negapatan1 Thank you. As of now, the agent works more like a cursor. Integration with other tools like support, linear etc are coming soon.

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Congrats! Do we ask the AI agent for updates or it automatically proactively suggests updates?

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@nuseir_yassin1 Thank you, Nuseir! Big fan. Right now the agent works more like a helper that you ask for updates, similar to Cursor. Background agents are coming soon, and they will proactively look at support tickets, code commits, PRDs and feedback to suggest updates on their own.

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Congrats @roopreddy and the team! Does the AI agent support custom linting rules or style guides yet?
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@kate_ramakaieva Thanks so much! 🙌 Custom linting rules aren’t available yet, but our style guide support is currently in QA and on track to go live next week.

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Congrats on shipping! The built-in AI assistant for users is super underrated; support teams will love this. :D

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I really appreciate the focus on accessibility. Docs should be fast and yours clearly are. BTW, I was testing your page load speed.
39
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@abod_rehman Thanks a lot Abdul for checking it out. Speed is one of our top priorities, we still have room to get even faster, so your feedback means a lot.

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Beautiful launch. From the landing page to the assets, everything is super clean and neat. Well done!!
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@priyankamandal Thank you so much! The team put a lot into making everything feel clean and polished. Glad it came through!

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Great work!! Any plans to support multi-language documentation with automatic translations or it already supports?

37
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@himani_sah1 Thank you! We don't have multi-language support yet. We will soon support it.

36
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Does your product access my Git and, based on that, generate or edit documentation itself?

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@michael_vavilov Auto-generating/updating docs based on Git commits is in the pipeline. It will be available soon.

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This is seriously impressive because the structure for semantic chunking is something most tools completely ignore.
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@kruti_parekh Thanks you Kriti! Appreciate it.

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Looks good, love the design.

Creates a public GH repo though be aware if you want your documentation to be private.

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@boraoztunc Thank you!
Yes, we create a public repo by default as it’s helpful for OSS and others, and it also simplifies onboarding technically. You can switch it to private at any time. We’ll also make this clearer in the onboarding flow.

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The integration with Jira/Linear is super helpful. Devs and technical writers would love it.

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@zerotox yes, context is everything for an agent to write better documentation. We will soon integrate important support, project management, and Code commits in the coming weeks.

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Love the positioning. With AI agents everywhere, good documentation is becoming infrastructure, not a nice-to-have, but a must-have.

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@iamanantgupta Thank you, Anath!! Glad that it resonated with you. You put it even better..

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The looks great.
Definitely trying it out soon for for products.

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@noel_mathew Thanks, Noel. Please ping us on Slack, if you need any help.

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How you handle versioning across major releases? BTW, congrats on the launch

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@raihanshezan Thanks, Raihan!
To handle versions, we have something called Dimensions. For example, version, language, or multi-product. These dimensions make it easier for both humans and AI agents to understand and work with the product. There’s more detail about this in our docs.
https://documentation.ai/docs/customization-and-configuration/site-configuration#dimensions-layer

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Love the design quality. Fast-loading docs with semantic structure feels like the future of technical writing.

6
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@ilya_korzun thanks for your kind words!!

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Interesting approach with llms.txt. How customizable is the schema for complex API surfaces?

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@thisiskp_ We support OpenAPI 3+ in both JSON and YAML. You can fully configure how your APIs are organized in the navigation, including grouping and filtering endpoints using tags, so it works well even for complex APIs

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Congrats on the launch @roopreddy and Team! This resonates hard. We've struggled with keeping our API docs in sync with rapid feature releases for ResumeUp.AI. The Git commit analysis for auto-updates sounds promising.

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@hareesh_vemasani Thanks a lot Hareesh!!

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I love that you treat docs as a growth channel, Roop. That mindset is becoming so important with AI. :)

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@ragsyme Thanks Raghav! Most of what I ask in ChatGPT, especially about the ends up pulling straight from documentation and related sources.

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Congratulations on the launch 🎉 🎉

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The MCP integration caught my eye. Does it work with self-hosted LLM setups as well?

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@iftekharahmad Yes. As long as your self-hosted LLM can act as an MCP client, it will work with the MCP integration

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The toughest is to deciding what actually needs documenting versus what’s just noise. Products evolve every week, but not every update deserves a rewrite. Finding that balance between being comprehensive and being clear is honestly the struggle.

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@samantha_den absolutely agree. Not everything is worth documenting. That's why important to have human in the loop solutions rather than leaving everything to AI

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Product teams always struggle with outdated API docs. The monitoring of support tickets is a brilliant add-on :D

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@raghavendra_devadiga4 Thanks for your kind words!!

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Really awesome. Is there a provision in the generated docs to handle SEO, SEMs, LLM listings, etc., properly?

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@chilarai Thank you! We’ve put a lot of thought into giving you as much control as possible. You can configure all of these options from the Settings section of the dashboard, and page-specific settings from the page metadata. If you’re using an IDE, you can configure them in the documentation.json

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#4
Compass
Ask Slack about your data and get answers instantly in chat
338
一句话介绍:一款原生集成在Slack中的AI数据助手,通过自然语言查询,让业务团队能直接从数据仓库中即时获取深度业务洞察,解决了跨部门数据依赖导致的“知其然不知其所以然”和等待周期长的痛点。
Slack Artificial Intelligence Data & Analytics
数据查询与分析 Slack集成 自然语言处理 商业智能 AI助手 数据民主化 GitOps 实时洞察 协作分析
用户评论摘要:用户普遍认可其解决“数据获取难”痛点的价值,认为“聊天即分析”模式直观高效。主要问题集中于:具体使用场景、GitOps上下文管理机制、模糊查询处理、多平台支持计划,以及复杂查询与多源数据整合能力。
AI 锐评

Compass并非又一个简单的“Chat for Data”玩具,其真正锋芒在于试图用工程化思维解决AI数据产品的核心顽疾:混乱与失控。产品定位极其聚焦——深耕Slack场景,放弃大而全的独立平台,这既是精准的渠道策略,也深刻理解了“数据消费”发生的真实上下文,降低了使用门槛。

然而,其宣称的“根本性差异”中,“GitOps支持的上文管理”才是潜在的护城河。它将AI黑箱中最为关键的“业务上下文”定义、更新与审核流程化、版本化,让数据团队重掌控制权。这直接回应了企业部署AI时最大的顾虑:如何防止AI胡言乱语,以及如何让业务知识沉淀为可管理的资产。这本质上是在为“上下文工程”建立软件开发生命周期,是迈向企业级可靠性的关键一步。

但挑战同样明显。首先,其“多人在线协作”的理想状态高度依赖组织内已存在的数据素养和协作文化,否则线程中仍将是混乱的噪音。其次,将复杂分析压缩至Slack对话流,在应对需要多步探索、深度钻取的场景时,其交互深度可能成为瓶颈。最后,作为Dagster旗下的产品,其长期战略是成为其数据平台生态的“交互层”,还是旨在成为独立的最佳单品,这将影响其集成广度和功能演进路径。

总体而言,Compass是一次有价值的“降维打击”:将数据洞察从专业工具中解放,植入高频协作流。它的成功不取决于AI有多聪明,而取决于能否将“提问-回答-澄清-确认”这一数据协作循环,变得如日常聊天般自然且可追溯。这条路走通了,便是数据平民化的关键一步;若流于表面,则可能只是另一个昙花一现的聊天机器人。

查看原始信息
Compass
Compass puts data in your teams' hands, right in Slack. Ask in plain language and get instant insights from your warehouse, our prospecting data, or both. From tracking pipeline to sourcing leads, Compass helps every team move faster. Analysts stay in control with GitOps backed context that keeps things clean, clear, and far from AI chaos.

Hey Product Hunt, I’m Pete, CEO at Dagster! We just launched Compass: collaborative AI-powered insights in Slack powered by your data warehouse. Finally, you can get to the “why” behind your metrics in seconds, not days.

We originally built Compass as an internal tool to solve our own business problems. We have a great data team, and built out a comprehensive data warehouse containing all of our critical business data like sales opportunities, marketing campaign performance, and product engagement analytics.

However, we struggled to really leverage this data at our organization. Our BI dashboards were great at telling us the “what” - how our sales pipeline is trending, how many DAUs we have vs MAUs, what our AWS spend was last week, etc - but it didn’t tell us the “why.” Why is pipeline down? Why did DAUs spike? What drove our AWS spend increase? Etc.

We had these sorts of questions on a daily basis. And every time we did, we’d file a ticket for our excellent  data or revops teams, interrupt their day, and wait a few hours or day or two to get an answer.

Like many companies, we built an internal Slackbot to solve this problem. Anyone could ask it a question in natural language, and it would return an answer, complete with data visualizations and its methodology.

It took off like wildfire, and a majority of our employees started using it on a weekly basis. We decided to turn this internal tool into a fully supported product offering we’re calling Compass.

How Compass is different

We took a different approach than a lot of other AI tools in this space.

🖥️Slack native. We exist solely within Slack. There’s no separate web app to long into, so it’s easy for users to get started immediately.

👥Fundamentally multiplayer. We let data people, business stakeholders, and AI all work together seamlessly to iterate to the right answer.

🏋️Proactive. In addition to answering questions, Compass will deliver personalized data insights every day, surfacing useful trends and starting points for analysis. One of our customers (a highly successful tech unicorn) found a support issue impacting $10mm+ in revenue in the first week.

🧠Crowdsourced business context. This is our secret sauce: we automatically and continuously learn business context based on properties of the data, characteristics of the business, and, most importantly, end-user interactions.

All of this is governed by a gitops workflow, which keeps the data team in control and brings a real SDLC to context engineering.

Who is it for?

Compass is about bridging the data team and the business. Data teams - anyone that manages a modern data warehouse like Snowflake, Databricks, BigQuery or Athena - will benefit, as will their stakeholders: sales leaders, marketing leaders, recruiting leaders, executives, as well as ICs.

Get started at compass.dagster.io. Onboarding only takes a few minutes, and if you sign up before the end of the year your first month is free!

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@floydophone Hey! I’m a 16 y/o tech entrepreneur building foundrlist .com a space where makers get more visibility and people discover exciting new products.

If you’re interested, feel free to add your product. I genuinely think it would be an amazing fit! 🚀

FoundrList is growing fast we’re getting 1,000+ new visitors daily and 100+ new products listed every week, so your support would directly help expand something that’s already taking off.

Thanks so much!

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@floydophone Such a smart solution to a common problem. I can definitely see the use case for this. Giving you some support! (I'm launching today as well, wishing us both luck in the rankings!)

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If you dont mind me asking? What are the 3 top use-cases for this?

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@conduit_design From what weve seen internally and with our early customers, its been a major unblocker for non-data users that dont want to fiddle around with a dashboard or the warehouse. With that being said:

  1. Sales prospecting

  2. Product Managers understanding feature bottlenecks and adoption

  3. Customer success user understanding and proactive suggestions

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Strong launch Pete. Compass feels powerful and focused. Congrats to you and the team.

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@nimaaksoy Thanks!

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This is the kind of thing that makes you wonder why every data tool isn’t just… in chat already. Nice launch!

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How does GitOps-backed context actually work in practice? are all changes versioned and reviewable before going live? Congrats.

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@himani_sah1 The data team has access to the git repo where the context is stored, when someone in a compass thread makes a context update like "Claire and Jeff are CSMs not AEs, remember that for the future" A pull request is opened up in the context store for them to review and merge. The context is also automatically updated on a cadence to make sure its fresh

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Congrats on launch! Dagster Cloud looks super clean.
What’s the first “oh wow” moment you want new users to experience when they jump in?

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@joydeep_pandey the oh wow moment for me was asking Compass to perform a multi-step complex analysis that I always wanted to and didnt have the time. And then iterating in the thread by going back and forth around a few scenarios to get to a final answer and actionable insight.

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How does Compass handle ambiguous or poorly phrased queries in Slack? Does it ask clarifying questions or make assumptions?

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@nuseir_yassin1, the compass bot will ask clarifying questions in the Slack thread. Oftentimes, we see the data team or a informed stakeholder will jump into a thread and provide additional context to guide the conversation towards higher quality insights. Under the hood, Compass iterates over a few possible solutions until it finds the most optimal one.

0
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Do you plan to expand Compass to other collaboration platforms (e.g., Microsoft Teams) for teams using alternative workplace tools? Also, will Dagster offer pre-built connectors for top data warehouses (e.g., Snowflake, BigQuery) to accelerate onboarding for new users?

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@Dagster Asking Slack about your data and getting instant answers is a game changer for productivity! Chat based data queries eliminate the need to context switch between tools.

How does Compass handle complex queries that might require joins or aggregations across multiple data sources?

Are teams able to customize the natural language understanding for industry specific terminology? The real time aspect in Slack is brilliant for keeping workflows seamless.

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I could see how our tool could benefit from Dagster’s orchestrated, reliable data workflows to streamline automation and analytics — I’ll go check out this launch and dig in further.

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How do you handle conflicting interpretations from multiple stakeholders asking questions in Slack?

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Absolutely amazing!

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Dashboards tell you what, Compass finally tells you why—right where teams already live in Slack. Feels like a superpower for anyone tired of pinging RevOps for ‘just one more chart’.

0
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#5
Protaigé
Your AI marketing agency that launches branded campaigns
255
一句话介绍:Protaigé 是一个云端AI营销代理,通过整合策略、文案和设计工作流,在几分钟内生成符合品牌DNA的完整营销活动,解决了营销团队在追求速度与保持品牌一致性之间难以两全的核心痛点。
Marketing Artificial Intelligence Marketing automation
AI营销自动化 端到端活动生成 品牌一致性管理 云端创意代理 营销活动生产 品牌DNA 多智能体协作 跨渠道营销 SaaS B2B
用户评论摘要:用户普遍认可其“端到端生成”和“品牌DNA”概念,认为能解决传统AI工具输出零散、缺乏品牌灵魂的问题。主要问题/建议集中在:品牌语调捕捉的准确性验证、与社交/邮件平台的直接集成深度、以及内部是否“自食其果”使用产品。团队回复积极,透露了技术选型(如Nano Banana)和未来集成计划。
AI 锐评

Protaigé 的野心不在于成为另一个AI文案或设计工具,而旨在成为营销活动的“自动驾驶系统”。其真正价值并非单纯叠加多个AI任务,而是构建了一个以“品牌DNA”为控制核心、策略为先的决策闭环。这直击了当前企业应用生成式AI的核心尴尬:单点工具效率提升的“副产品”是品牌资产的碎片化和管理成本的激增。

产品将品牌指南、用户画像等非结构化数据转化为AI可执行的“护栏”,这是一个关键的技术与产品设计门槛。它试图将品牌管理从昂贵的人力审核流程,转变为可编码、可预设的规则系统。然而,其最大挑战也在于此:“品牌灵魂”能否被完全结构化?评论中关于“语调准确性”的疑虑正是这一挑战的体现。AI可以学习规则,但理解品牌与受众之间微妙的情绪连接是另一回事。

此外,其“策略优先”的流程是对当前“提示词即策略”的草根式AI应用的一种升维打击。它不再等待用户给出完美指令,而是尝试通过交互补全营销简报,这实际上是在教育市场、重塑工作流。风险在于,成熟营销团队是否愿意将策略构思的“黑箱”部分托付给AI?这或许解释了其初期目标用户更可能是人手紧缺的初创团队和中小型企业。

本质上,Protaigé 是在售卖“可控的规模化创意”。如果其品牌DNA系统经得起复杂品牌的考验,它将从工具演变为基础设施,成为企业数字营销的“操作系统”。反之,若只能处理中规中矩的品牌表达,它则可能沦为一个更高效的模板化内容生产器。其成败,系于“理解品牌”的深度,而非“生成内容”的广度。

查看原始信息
Protaigé
Delivering complete, ready-to-launch campaigns in minutes, not weeks. What makes Protaigé different: It doesn't generate headlines or banners. It generates the whole thing. AI agents work together on strategy, copywriting, and design - just like a real creative team. Your Brand DNA sits at the core, controlling every output. Guidelines, personas, products, and assets become guardrails ensuring campaigns stay on-brand across channels and markets. No fragments. No delays. Complete campaigns.

Hey folks!

We built Protaigé because we saw marketing teams facing a difficult choice: sacrifice brand consistency to move fast, or slow down to maintain quality. We wanted to build a third option: an AI system that understands your brand as well as you do.

Protaigé is a creative agency in the cloud. It takes you from a simple brief to a full campaign in minutes.

Here is what makes us different:

🚀 End-to-End Production: Protaigé automates the entire campaign production process. From your initial brief to the final export, we build every asset in one connected workflow. Unlike many other AI tools that are point solutions and handle just one task like copywriting or banner generation.

🧬 Brand DNA: Generic AI output often sounds soulless. We allow you to upload your brand guidelines and other relevant brand assets and documents. Our system ingests this to ensure every output aligns with your voice and visual identity.

💡 Strategy First: Most tools skip straight to execution. Protaigé starts with strategy by completing the marketing brief and then developing distinct creative concepts for you to review and approve before it builds a single asset.

Who is this for? We designed this for marketing teams and founders who need to scale output without scaling headcount. Whether you need a tactical push or an integrated campaign, Protaigé handles the heavy lifting.

Our Launch Offer: We are currently in Public Beta.
- Campaign Lite: You can try the platform on our free plan.
- Campaign Plus: For this launch, we offer a 75% discount on our Plus plan ($49/month) for small teams.

We want your feedback. Specifically, does the Brand DNA capture your tone correctly?

Excited to hear your thoughts! 👇

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@wawagilewski brand dna bit sounds huge, generic ai always feels flat. curious if it really nails tone tho

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@wawagilewski This looks solid. Congrats on the launch! I just put my own app live today too, so I know how much work went into this.

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are y'all using nanobanana? in curious, how are you tackling the text shape retention and are you getting variety in fonts?
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@ssindhia Protaigé fully retains your brand's original designs, even when using generative AI for images (and yes, we use Nano Banana). That has been a conscious choice from Day 1.


The way we achieve it is by limiting what the AI can generate to specific elements that are relevant for marketing campaigns. The most frequent use cases are producing variations of the hero image to A/B test, personalise, or localise the campaign. The rest of the designs stays true to the brand - so even if, hypothetically, a user went rogue, they wouldn't be able to break the design rules set by their company's brand team!

Design kits, as well as fonts, and the other brand assets (logos, colours, graphics, icons, photos) are all part of the Brand DNA that is defined at account setup and that serves as the foundation for anything Protaigé generates.

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Great! Do you also manage social media and email campaigns from your dashboard?

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@chilarai Yup of course. You can create campaigns and then use them across different channels - social, emails, search ads etc.

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@chilarai You can produce campaign assets for these channels within the platform and export them for upload. We're adding direct integrations with popular social platforms and a native publishing feature - coming real soon!

Do you mind telling me what platforms/clients you're currently using?

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It looks so easy to create a campaign! Great tool, my congrats!
And I was the 200th person to upvote Protaige :D

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@tetiana_hryshmanovska Thanks 200 times then! :)

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Seeing a full campaign appear instead of random headlines feels refreshing. No patching thigs together anymore.

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@simran_kumar Spot on. Let us know about the rest of your experience!

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Very smooth process!

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@osakasaul Thanks so much for the feedback! Have you gone through the entire brand setup process? (I'm not able to guess which one of the signups we got today is yours!)

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Seeing a full campaign appear instead of random headlines feels refreshing. No patching things together anymore.

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@shawn_idrees Thanks for the feedback and yes, indeed, we're very much focused on the end-to-end campaign production workflow. Unlike the myriad of AI point solutions out there that operate in a vaccum and give you only disconnected pieces...

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Really like the strategy first approach here. Most AI tools jump straight into spitting out assets, but campaigns only work when the thinking is solid. The Brand DNA angle is also interesting. Generic AI copy is a real issue when you’re trying to protect a brand's voice. Excited to see how well it adapts to different tone guidelines.

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@adnan_gradascevic Thanks for the feedback, glad the product resonates. I saw you've also launched today - congrats and wishing you all the best ;)

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@wawagilewski An AI marketing agency that launches branded campaigns is ambitious! The automation of campaign creation saves agencies and marketers massive amounts of time.

How does Protaigé maintain brand consistency across different campaign types? Are users able to input brand guidelines and tone of voice so the AI stays on brand?

Curious about how it handles campaign performance tracking and optimization over time.

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Congratulations on your product launch! Nice product concept. Would love to give it a spin. Wish you guys all the very best. 👍🏻
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@agzee Thanks a bunch! Do give it a try and let us know how we can make it better

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Did you use Protaigé to create the marketing assets for Protaigé?
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@nathan_darma If you're asking about our website, then yes, we demonstrate assets that were generated in Protaigé—display ads, emails, social posts, banners. We're also generating search ads, social ads, and landing pages for our ad campaign, so you can see we use Protaigé to scratch our own itch ☺️

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@nathan_darma Love this question. All our static assets are made in Protaigé with a human in the loop. Video is still in development, so those are currently done in-house, with Protaigé generated concepts. If we’re not using it ourselves, how can we expect anyone else to?

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digital marketers need to pay very close attention to products like this. Would love to give it a try for my side projects.

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@dbg1 Thanks and feel free to create an account for as many brands as you like.
One thing worth pointing out is that Protaigé falls within the purview of traditional marketers too, as it can generate all kinds ofoffline assets from billboards to flyers and extend those digital campaigns into out-of-home channels!
PS. I think I know your brother :)

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@dbg1 Hey I might know your brother too!

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The connected workflow approach could really help avoid the disjointed outputs we see with multiple AI tools.

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@abod_rehman That's one of the main reasons we built this. As a creative agency owner (or ex-owner now), we were frustrated by the copy-pasting between platforms.

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Excellent launch, Protaigé team. From a clarity & onboarding lens: when a marketing lead opens Protaigé for the first time, what’s the one belief you want them to hold in the first 10-15 seconds?
Is it:
• “I can launch a full on-brand campaign in minutes, not weeks.”
Or:
• “This system already knows my brand’s DNA—my work aligns automatically.”
Because in tools promising “speed + brand alignment,” the biggest adoption barrier isn’t features—it’s the user believing it fits me. Curious how you’re framing that for first-time users.

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@joydeep_pandey Great question. When you sign up as a new user, you'll see how we take you through an automated onboarding process to demonstrate the value upfront. After the initial Brand DNA is set up, we invite you to generate your first campaign to experience that platform's full capabilities ASAP.

"The biggest adoption barrier isn’t features—it’s the user believing it fits me" - true for any SaaS out there!

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do you use a variety of different models? or one in particular?

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@surtmcgert We use various models for different purposes, always matching the one we think is best for the specific task. Thanks for asking!

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@surtmcgert We use ALL the models 😆 It depends on what's needed eg core creative work (briefs, content gen) vs quick lightweight tasks vs image analysis and vision tasks vs generative imaging. We've found that matching the right model to each task gives much better results than relying on a single model for everything. Thanks for the great question!

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Congrats on the launch Wawa, Protaigé looks strong and well designed. Upvoted. I am co founder of bestofweb .site and after your launch if you want more visibility you are welcome to join and introduce it to our founder community.

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Thanks for the appreciation Nima and for bringing your directory to my attention - will give it a go!

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#6
8bitcn/ui
8‑bit UI components that work in any framework
250
一句话介绍:一套开源、可访问的复古8位像素风UI组件库,为开发者在前端任何框架中快速构建怀旧风格或游戏化界面提供现成解决方案。
Open Source Developer Tools GitHub
UI组件库 开源 前端开发 8位像素风 复古设计 可访问性 shadcn/ui生态 Vercel 游戏化UI 怀旧风格
用户评论摘要:用户普遍被其独特的复古美学和开源属性吸引,认为它“有趣且有用”。主要反馈包括:对shadcn/ui生态的认可;期待更多游戏化动画、音效及预置主题;开发者@orcdev的社区影响力受关注。无实质性负面问题。
AI 锐评

8bitcn/ui的价值远不止于一套“好看的皮肤”。其核心在于精准切入了一个被主流设计趋势忽视的细分市场——复古数字美学,并成功将其产品化。它并非简单复刻像素图形,而是将“8-bit”作为一种设计语言,通过组件化、可访问性及框架无关等现代工程实践进行封装,从而将小众情怀转化为可规模复用的生产力工具。

产品巧妙地依附于shadcn/ui建立的生态势能,降低了用户的认知和采用成本。其“Open Source. Open Code.”的口号,以及Vercel OSS计划等背书,进一步强化了其在开发者社区的信任度。评论中流露出的强烈情感共鸣——“刷新了红白机记忆”——揭示了其更深层价值:在高度同质化的现代UI中,提供了稀缺的情绪价值和品牌差异化手段。

然而,其挑战同样明显。应用场景相对垂直,主要服务于游戏、营销活动、特定品牌等有限领域,市场天花板可见。用户对动画、音效和主题包的期待,也暗示了当前版本在“沉浸式复古体验”上尚有欠缺。若停留在组件视觉层,易被模仿或沦为一次性的“新奇玩意”。其长期成功的关键,在于能否从“组件库”升级为“复古交互范式”的定义者,并围绕8-bit美学构建更完整的工具链和设计系统。在实用性与情怀之间找到持续平衡点,是它需要面对的终极考题。

查看原始信息
8bitcn/ui
A set of retro-designed, accessible components and a code distribution platform. Open Source. Open Code.

nerd alert: @orcdev turned @shadcn/ui into a beautiful 8-bit styled component library.

for me, it's an instant crush.

the project is backed by @Vercel's OSS program, sponsored by @Shadcnblocks, @Trigger.dev, and more; free and open-source. lfg!

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@fmerian hey man you hunt great products only as I see Just fall in love with this 8 bit components 🤣 Refreshed my memory with Mario Sonic and tanks on dendi and sega
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@orcdev  @fmerian Love the retro vibe! Do you plan to add more game-like animations or sound effects in future releases?

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@orcdev  @fmerian Looks great! it gives me vibes of old games I used to play :)

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Love it

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@malithmcrdev So glad to hear that! Thank you!

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I don't have a need for it (now), but I love it :)

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@ohansemmanuel Glad to hear that you like it! ⚔️ Thank you!

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It’s a fun project, and genuinely useful if you’re into retro-style UI. @orcdev has been doing amazing work creating videos and content for the shadcn ecosystem and I highly recommend you follow him on Youtube, my bet is hes the next big creator and Devrel at @Vercel - Keep up the great work mate!

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@ausrobdev Thanks for the kind words Rob! Really appreciate it!

Thank you also for the sponsorship and keeping the whole Shadcn community together.

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@ausrobdev 🐐
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This is awesome stuff, Orc friend! Here to support your launch. Good luck! 🙌

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@catalinmpit Thanks Catalin! Appreciate it!

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Upvoted my man :)

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@codewithguillaume Thanks Guillaume! 💚 Appreciate it!

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Love the retro design, also that it's Open Source. Knew immediately it has to do something with shadcn 🫡

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@jim_engine Open source. Open code. The only way :) Thank you!

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Love this! 8bitcn/ui brings a super fun 8-bit vibe to modern components. Clean, nostalgic, and really well executed. Huge props to the Orc — excited to see where this goes! 👾🚀

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@ajaypatel9016 Thank you so much Ajay! Big updates coming to 8bitcn :)

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Great components library for people who build retro games or websites! Awesome work @orcdev 👏

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@matsugfx Thank you Matt! Really appreciate your support 💚

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This looks fun and my thought is it would be cool if there was a small library of prebuilt 8-bit themes because I often struggle to match colors when I try to make playful UIs.

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Lets gooo big Orc :p

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@nikuscs Going strong!

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Let's go!!

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@dunsin to waaaaaaar

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Looks awesome, definitely want to try :)

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Cool stuff

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#7
Gemini 3 Deep Think by Google
Google’s best model for logical thinking and understanding
194
一句话介绍:Google推出的高级推理模型,通过并行推理技术处理复杂的数学、科学和逻辑问题,为需要深度分析和解决棘手难题的用户提供接近人类思维的AI洞察力。
Productivity Developer Tools Artificial Intelligence
人工智能 推理模型 逻辑思维 复杂问题求解 并行推理 Google Gemini AI订阅服务 科学计算 数学分析 高级AI
用户评论摘要:用户肯定其推理能力和处理复杂任务的准确性,期待与顶级模型竞争。主要疑问包括:使用门槛(仅限Ultra订阅者引发Pro用户不满)、多假设推理的具体机制、如何处理模糊问题,以及实际应用案例。
AI 锐评

Gemini 3 Deep Think的发布,本质上是Google在AI“智力竞赛”中一次精准的定点爆破。它不满足于通用对话,而是直指当前大模型最脆弱的腹地——深度、复杂的多步推理。其宣传的“并行推理多个假设”是核心卖点,这暗示其试图模拟人类专家在面临不确定性问题时的思维发散与收敛过程,而非沿着单一概率路径机械推进。

然而,产品策略暴露了其矛盾定位。仅向最高价“Ultra”用户开放,虽符合商业逻辑,却将最需要测试其极限、能提供关键反馈的资深科技用户(Pro用户)拒之门外,可能影响迭代速度与社区口碑。评论中的质疑非常尖锐:用户如何影响其推理路径?这触及了AI可控性与透明度的根本问题。如果“深度思考”只是一个更黑箱的自动过程,其价值将大打折扣,沦为更准确的“猜谜机器”。

真正的价值不在于解决几个预设的逻辑谜题,而在于能否成为科研、工程、战略分析等领域的“思维伙伴”,提供可解释、可干预、可协作的推理链条。目前看来,它在“准确性”上获得了早期赞誉,但在“协作性”与“透明性”上仍存巨大问号。它与其说是“人类般的洞察”,不如说是“专业化的问题求解器”。它的成功,将取决于Google是否愿意将这种顶级能力逐步工具化、民主化,而非仅仅作为彰显技术实力的橱窗展品。

查看原始信息
Gemini 3 Deep Think by Google
Gemini 3 Deep Think introduces Google’s most advanced reasoning model yet built to solve complex math, science, and logic challenges that push the limits of AI. Using parallel reasoning across multiple hypotheses, it delivers deeper understanding and human-like insight. Available now for Google AI Ultra subscribers in the Gemini app.
Hey everyone! Google just launched Gemini 3 Deep Think! A major leap in AI reasoning. Built to handle complex math, science, and logic tasks, it uses parallel reasoning to explore multiple ideas at once, bringing AI closer to human-like understanding. Ultra subscribers can try it now in the Gemini app under Gemini 3 Pro → Deep Think.
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@byalexai Congrats on the launch — this looks like a major advancement in reasoning models.
I’m curious how Deep Think decides when to explore multiple hypotheses versus going deeper on a single one.
Is that something users can influence, or is it fully automatic based on the prompt?

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@byalexai This is truly unbelievable! Congrats on this huge launch!

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Really cool. Been using gemini all summer. Really fast and nimble. Great for day to day work. Only using gpt5 and Sonnet for harder problems. So this is a welcomed model to compete with the elite LLMs. I hope its included in the startup perk package 😅🙏

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I am wondering how it handles ambiguous problems because my logic tasks often have multiple valid interpretations and I want to know if it can explore all possibilities without oversimplifying.

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Really exciting to see this launch because my past encounters with AI reasoning felt limited and this model gives me hope that complex problem solving might finally be more intuitive and human-like.

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this feels built for people who enjoy complex thinking. The whole design pushes beyond typical assistant-style replies.

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Tried a few logic and it handled them with such calm accuracy. Felt almost like talking to a real problem solver.

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So not yet for Pro users? I would honestly feel betrayed if I were paying for Pro and would like to test this new feature

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@jim_engine me too :D

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The human-like reasoning hits especially well on science problems. Got super clean explanations with zero fluff. 🔥

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Nice launch! Deep Think sounds like the “let’s solve the impossible” mode. What’s been the most memorable problem users asked it to solve so far, and how did they react when it actually delivered?

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#8
Slack Feature Request Agent
Track and fulfil customer requests directly on Slack
189
一句话介绍:一款集成于Slack的AI助手,通过自动抓取和分析客户通话记录,将功能需求自动转化为可追踪的Jira任务,解决了客户成功和销售团队在跨工具手动记录、追踪和反馈客户需求时的信息遗漏与流程断裂痛点。
Customer Success Customer Communication Artificial Intelligence
客户反馈管理 AI工作流自动化 Slack集成 产品需求收集 Jira自动化 客户成功工具 SaaS效率工具 智能工单创建 跨平台信息提取 客户闭环沟通
用户评论摘要:用户普遍认可其解决“需求黑洞”的核心价值,认为其无缝集成现有工作流是最大优点。主要问题与建议集中在:如何精准去重并关联现有Jira工单、路由规则的自定义程度、处理复杂边缘数据的能力,以及是否能与产品路线图工具集成。
AI 锐评

Korl的Slack Agent本质上是一个“流程缝合怪”,其真正价值不在于技术创新,而在于精准的流程定位和狡猾的“惰性营销”。它没有创造新流程,而是用AI自动化了那些存在于每个SaaS公司、人人厌恶却又不得不做的“脏活”:从海量对话记录中人工摘取需求、跨平台复制粘贴、以及事后告知客户。这击中了客户成功和产品团队一个隐秘的痛点——道德负债,即承诺了客户却因内部流程繁琐而遗忘所导致的愧疚感。

产品聪明地避开了“又一个仪表盘”的陷阱,选择寄生在Slack和Jira这两个已被验证的工作流枢纽上,降低了采用阻力。其宣称的AI能力,如从多种工具提取信息、向量搜索去重,在技术层面已非壁垒,真正的考验在于对业务上下文的理解深度:能否准确区分客户随口一提的愿望与严肃的功能请求?能否在嘈杂的销售对话中识别出真正的需求信号?评论中关于边缘案例和复杂数据的担忧,正是其商业化落地的命门。

然而,其商业模式存在隐形天花板。作为附着于现有工作流的“胶水型”工具,其功能边界极易被上游平台(如Slack、Jira自身)或更庞大的客户数据平台(CDP)所覆盖。它的长期生存策略,或许不在于成为独立的“大脑”,而在于持续深化其作为最灵活、最轻量“神经系统”的定位,在巨头缝隙中提供极致专注的自动化缝合服务。成功与否,取决于它能否将看似简单的“捕捉-跟踪-通知”循环,做到远超用户自身手工操作的可靠与精准。

查看原始信息
Slack Feature Request Agent
Korl’s Slack Agent uses AI to automatically capture and track customer feature requests – without adding new tools to your workflow. Here’s how: 1. Extracts requests from customer calls in Gong, Zoom, Fathom, Fireflies, and more 2. Routes requests for review so you can file or update Jira tickets right from Slack 3. Notifies you when features ship with a personalized update for customers It helps CSMs avoid the request “black hole” while giving Product visibility into what customers need.

Hey ProductHunt! 👋

I’m Berit, co-founder of Korl. Thanks for checking out our launch!

This Slack agent actually started as a hacky internal workflow we built for ourselves. We were tired of trying to remember to log Jira issues after every customer call. We were building things our customers had asked for… but forgetting to close the loop when they shipped. We knew AI could automate this, and we didn’t want yet another system to log into.

So we stitched together a rough agent that reviewed our Fathom call transcripts, flagged feature requests, and pushed them into Slack for quick triage.

Then one of our customers saw it and asked, “Can we have that?” That’s when we realized this should be part of our product, not just an internal tool.

Today’s launch is that productized version. It:

• Captures feature requests automatically from call recordings

• Routes them to Slack so CSMs or Sales can add or update Jira issues from Slack

• Tracks progress and drafts personalized updates when features ship

We’d love to hear from you. What’s your current process for tracking customer requests? And what would make this agent more useful in your workflow?

Thanks again for your support and for being part of the Korl community!

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@berit_hoffmann Exactly, as Berit said: the 'black hole' of customer requests was a real pain for us. As a co-founder, I was constantly struggling to keep up with customer requests and prioritizing them. Like the best folks you work with, this agent meets you where you are. To me, that’s the best part. It doesn’t require behavior change or nudges. You just have your call, and Korl handles the admin work in the background. I’ll be hanging out in the comments all day. Hit me with your toughest questions about our roadmap or how the agent works under the hood!

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@berit_hoffmann Huge congrats on the launch! The design overhaul is exactly what was needed. Waiting to test out the new features right away.

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@berit_hoffmann This looks incredibly polished. The onboarding flow seems really smooth. Launching my own product today, so I know how stressful it is to get the pixels perfect. Upvoted!

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Beautiful launch Berit. Korl feels simple and powerful. Congrats to you and the team.

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@nimaaksoy Thanks so much! We really appreciate your support

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Cool. And finally, do you allow the presentations to be exported to different formats?

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@chilarai Yes. You can go into present mode from Korl, or you can export to common formats like PDF or Google Slides. Korl itself has full editing capabilities on the slides as well, many of which are powered by AI and much more efficient than editing in common tools like GSlides.

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Oof, this hits my “where’d that request go?” panic before QBRs. Pulling asks from Gong → Slack/Jira then nudging when it ships… nice. Also into the auto-deck angle. Curious how well it de-dupes and maps to existing tickets.

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@alexcloudstar the deduping against existing Jira tickets uses vector search, so it captures matches even when they're not a keyword match or are phrased differently. We also surface the top 3 matches in Slack so you can choose which one is the best match (or file a new ticket if none of them are).

Obviously proof is in the pudding once you try it on your data, but one of our early adopter customers has been using this for a little over a month and of the 100+ requested they've captured, about 70 of them were linked to existing issues!

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Impressive launch, Korl team. From a clarity & onboarding lens: when a customer-facing team opens Korl for the first time, what’s the one belief you want them to hold in the first 10-15 seconds?
Is it:
• “I understand each customer’s unique value path, not just their usage data.”
Or:
• “My presentation will reflect their brand, context, and issues—no generic slides.”
Because in tools aimed at personalization at scale, the biggest adoption barrier isn’t features—it’s belief that it gets the customer, not just the data.

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@joydeep_pandey Good question. The belief we want them to hold is:

"Korl prepares me to speak directly to value for this customer, based on their unique requests, use cases, and priorities."

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Korl hits a major pain point for CS/AM teams: the grind of turning scattered product + customer data into polished, personalized decks and renewal materials. Rather than wrestling with spreadsheets, Jira tickets, Slack threads, and having to build each customer‑specific slide by hand, Korl pulls everything together and auto‑generates meaningful presentations.

I especially like that it doesn’t treat “presentations” as generic templates — it builds them around real context: who the customer is, how they use your product, what their priorities are, and what value you’ve delivered or could deliver next. That shift from generic to personalized is where automation actually adds value.

For startups or small SaaS companies that can’t justify a full‑time CS ops or presentation builder, Korl seems like a tool that lets you punch above your weight: better customer communications, stronger renewals, and more consistent value messaging without scaling headcount.

That said — the real test will be how well the “AI + data sync → presentation” pipeline handles edge cases, complex data, and constantly evolving products. If that holds up, I think Korl could be a game‑changer for customer-facing teams.

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@andrew_azman Thanks for the comment! Definitely agree the real test is in handling edge cases and complex data. That's why we offer a free trial so people can see how Korl does on their own data.

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I could see how our tool could benefit from Korl’s workflow automation and streamlined collaboration features, so I’m thinking this could work well together and I’ll go take a closer look at their launch.

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@jamesjacksonleachatx Glad to hear! Feel free to reach out if you have any questions as you are getting started.

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How customizable is the routing to Slack channels or Jira projects?

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@abod_rehman Very customizable. You choose:

  1. The Slack channel you want to post the summary of calls + requests

  2. Where you want requests sent for review/triage (default is a DM to the call attendees, but you can fall back to a shared channel if you'd like)

  3. Which Jira issues to compare against for matching

  4. How to file new requests in Jira: which fields to update, which project new requests should go to, what type of issue (story, bug, epic, etc.)

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@berit_hoffmann Tracking and fulfilling customer requests directly in Slack is perfect for customer success teams! Keeping everything in one place reduces friction and speeds up response times.

How does the agent prioritize feature requests when multiple customers ask for similar things? Are teams able to connect this to product roadmap tools for seamless workflows?

The AI component could be huge for identifying patterns across requests.

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This is definitely useful. A lot of customer complaints are about not getting quick responses and no one taking charge.

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#9
Bun
A fast JS runtime Node.js replacement with built‑in tools
184
一句话介绍:Bun是一个集运行时、打包器、转译器、任务运行器和npm客户端于一体的快速JavaScript/TypeScript工具链,旨在通过一体化设计解决开发者需要配置和维护多个独立工具的效率痛点。
Open Source Developer Tools GitHub
JavaScript运行时 TypeScript支持 前端工具链 打包工具 任务运行器 npm客户端 开发效率工具 Node.js替代方案
用户评论摘要:用户普遍赞赏其一体化设计带来的便捷,但也指出Windows ARM支持等兼容性问题。有评论深入探讨了其核心定位应聚焦“开箱即用的兼容性”还是“极致的速度与工具整合”,这是其市场传播的关键。另提及被Anthropic收购的动向。
AI 锐评

Bun的亮相,与其说是一款技术产品,不如说是一次对前端工具“封建割据”现状的精准打击。它宣称的“All in One”并非简单的功能堆砌,其真正价值在于试图重新定义现代JavaScript开发的“工作流单位”——从以文件或项目为单位,转向以“运行时”为基座的一体化操作单元。这直接挑战了由Webpack、Babel、npm等独立工具构建起的庞大生态与开发者肌肉记忆。

然而,其最大的挑战并非性能,而是“生态兼容性”与“心智转换成本”。一条高赞评论犀利地指出了核心矛盾:开发者首次打开时,应被灌输“无缝兼容”的信念,还是“更快更强”的认知?这本质是市场策略的选择题。前者降低迁移门槛,但可能弱化其革新性;后者强化优势,却可能吓退保守用户。目前看来,Bun在Windows ARM等边缘场景的兼容性瑕疵,正为“无缝兼容”的叙事留下了裂痕。

此外,被Anthropic收购一事虽在评论中被轻描淡写,实则暗藏玄机。这标志着主流AI巨头开始系统性布局底层开发工具链,其意图可能远超优化JavaScript本身。Bun或许不仅是Node.js的替代品,未来更可能成为AI原生应用(如智能代码补全、调试)的首选高性能载体。它的终极战场,可能不在与Node.js的缠斗,而在为AI驱动的编程范式铺设基础设施。当前版本是利剑出鞘,但真正的战争,才刚刚开始。

查看原始信息
Bun
Bundle, install, and run JavaScript & TypeScript all in Bun. Bun is a new JavaScript runtime with a native bundler, transpiler, task runner, and npm client built-in.

Bun is around for quite some time, I wonder why it never made it to PH. Also, haven't they been bought by Anthropic now?

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I ❤️ bun. But I made sure my project also works with NPM. Turned out. Bun didn't support windows arm executables. But NPM did. So for win arm exe. I use NPM. For other targets. Bun.

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Impressive launch, Bun team. From a clarity & onboarding lens: when a developer opens Bun 4 for the first time, what’s the one belief you want them to hold in the first 10-15 seconds?
Is it:
• “This runtime just works with my existing stack, no rewrites.”
Or:
• “I can build faster and ship earlier, and the tooling problem is solved.”
Because for developer tools, the adoption barrier often isn’t features-it’s the dev believing this fits how I already build. Curious how you’re framing that.

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Seeing a tool combines, task running, and npm support makes me smile because my old workflows were a patchwork of half a dozen utilities.

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It would be cool if the runtime gave me quick feedback on errors because I hate waiting for the build to finish just to find a tiny typo.

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Congrats! Bundling, running, and installing in one runtime is an elegant developer DX win.

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Now owned by Anthropic! https://www.anthropic.com/news/a...
0
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#10
Unosend
Send transactional + marketing email w/ 99.9% deliverability
172
一句话介绍:一款为开发者打造的电子邮件API,以99.9%的到达率、透明的定价和丰厚的免费额度,解决了初创公司和独立开发者在邮件发送成本与可靠性方面的核心痛点。
API Email Marketing Developer Tools
电子邮件API 交易邮件 营销邮件 高到达率 开发者工具 免费额度 成本优化 替代SendGrid 替代Resend 初创公司友好
用户评论摘要:用户普遍认可其定价和免费额度价值,并询问与Resend的具体差异、送达率保障机制、功能细节(如跟踪、防滥用)及未来路线图。同时,有用户指出官网存在深色模式显示问题,并建议优化与Resend过于相似的UI以建立独立信任感。
AI 锐评

Unosend的亮相,精准地刺向了当前开发者邮件服务市场的软肋:定价不透明与功能割裂。它并非技术上的颠覆者,而是一个精明的市场定位者和体验整合者。

其真正的价值不在于宣称的“99.9%送达率”(这已是行业头部玩家的标准话术),而在于它试图重构“开发者友好”的边界——从单纯的API优雅,扩展到商业模型的友好。将免费额度提升至5000封/月,并在基础套餐中捆绑联系人管理和广播功能,直接针对了Resend等对手“功能模块化、付费碎片化”的痛点。这本质上是在售卖“省心套餐”,降低开发者的集成与管理心智负担。

然而,其面临的挑战同样鲜明。首先,高度对标Resend的UI和API设计是一把双刃剑,虽降低了迁移成本,却也削弱了品牌独特性,甚至引发“山寨”质疑,损害信任根基。其次,评论中暴露的官网显示bug虽是小事,却对其宣称的“开发者体验”专业性构成了微妙打击。最后,也是最核心的:在由SendGrid、Postmark等巨头把持的邮件服务领域,作为新入局者,其“自有基础设施”能否长期、稳定地维持所承诺的送达率与发信信誉,仍需时间验证。这不仅仅关乎技术,更关乎运营、合规与对抗滥用的能力。

总而言之,Unosend是一次出色的市场侧翼攻击,用更具侵略性的定价和功能打包策略吸引价格敏感且渴望简化的开发者。但它能否从“更便宜的替代品”成长为值得长期托付的独立品牌,取决于其能否在保持价格优势的同时,快速建立不逊于竞品的、坚实可靠的技术声誉与独特的品牌身份。

查看原始信息
Unosend
The best email API for developers. Send transactional and marketing emails with 99.9% deliverability. Simple REST API, competitive pricing, and 5,000 free emails/month. Better than Resend & SendGrid. Start free today.
Hey Product Hunt! 👋 I'm excited to launch Unosend—the email API I wish existed when I started building. The Problem: Every email API either charges too much, has confusing pricing, or lacks features developers need. I've used Resend, SendGrid, Resend and Postmark-they're all great but expensive for growing startups. The Solution: Unosend gives you: - 5000 free emails/month - Transectional and marketing emails. - Simple, predictable pricing as you scale - The same reliable infrastructure and deliverability - A developer experience we're proud of Why we built this: As developers ourselves, we wanted an email API that doesn't punish you for success. When your app grows, your email costs shouldn't eat into your margins. What's next: - React Email integration - More SDKs (Rust, Java, .NET) - Advanced analytics - Email automation workflows I'd love your feedback! Try it free (no credit card needed), and let me know what you think. Happy to answer any questions! 🚀
5
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@bittucreator Advanced analytics could be super useful.

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@bittucreator Congrats on the launch! Any plans on integrating Unosend with @weMail ?

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Your landing page is partly broken

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@jim_engine It looks like a dark mode thing, but yeah the styles do look a bit broken.

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@jim_engine  Explain bit more

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pricing feels fair, especially for small projects that still need professional delivery.

2
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@frances_diazon Your products looks amazing! I’d love to collaborate with you if you’re interested. message me on zangi:49_4234_0277 OR telegram username below 👇 @Fanspage12p
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@frances_diazon 

For small projects, the combination of competitive pricing and professional deliverability is exactly the sweet spot—it keeps costs sane while still hitting inboxes consistently.

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Do you offer tracking, and also is there a way to detect if the mail has landed in spam?
Would love to try it

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@chilarai 

Thanks for the interest! 🙌

Yes, we offer tracking!

  • Open tracking - Know when recipients open your emails

  • Click tracking - Track which links get clicked

  • Delivery webhooks - Real-time notifications for delivered, bounced, and complained events

About spam detection:
Directly detecting if an email lands in spam isn't possible (no email provider can do this - it's determined by the recipient's mail server). However, we help you maximize inbox placement:

  • 📊 Bounce & complaint monitoring - High rates often indicate deliverability issues

  • 🔐 Full authentication - We handle SPF, DKIM, and DMARC automatically

  • 📈 Sending reputation - Our infrastructure maintains high sender reputation

If you're seeing deliverability issues, the complaint/bounce rates in your dashboard are usually the best indicators.

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@chilarai Your products looks amazing! I’d love to collaborate with you if you’re interested. message me on zangi:49_4234_0277 OR telegram username below 👇 @Fanspage12p
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So the only thing this one better than Resend is the number of free emails?

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@buiducnhat 

The free tier is definitely a highlight (5,000 emails/month vs Resend's 3,000), but there's more:

Beyond the free tier:

  • 💰 Better value - $20/mo gets you 50K emails AND 10,000 contacts (Resend's $20 only gives you 50K emails, no contacts included)

  • 🚀 Higher rate limits - 50 emails/sec vs Resend's 10/sec

  • 🔌 Same simple API - If you know Resend, you already know Unosend (drop-in compatible)

Same great features:

  • Beautiful developer experience

  • Webhooks, tracking, templates

  • React Email support

  • All the SDKs you need

We built Unosend because we love what Resend did for email DX, but felt the pricing was holding back indie hackers and startups. Same philosophy, friendlier on the wallet 🙌

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Very cool product :)
Looking forward to trying it!

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@lev_kerzhner Thanks Lev — appreciate it!

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Nice project, @bittucreator! It’s much-needed. I also love the simple and clean UI. Congratulations on a successful launch!

Do you have any plans for a PHP/Laravel package or library that can be used to send emails using UnoSend?

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@hasin 

Thanks so much! Really glad you like the clean UI - we put a lot of effort into making it developer-friendly 🙏

Great question about PHP/Laravel! Yes, we have a PHP SDK ready to go:

For Laravel specifically, you can also use it as a mail driver.

We're working on a dedicated Laravel package with Mailables support and would love your feedback on what features would be most useful!

Check out our docs: https://unosend.com/docs

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Well done Venkat. Unosend is clean and practical. Congrats to you and the team.

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@nimaaksoy 

Thanks, Nima, that means a lot. We aimed for a developer-first flow: fast setup, clean API, and predictable pricing.

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@bittucreator @Unosend 99.9% deliverability for transactional and marketing emails is impressive! Email deliverability is such a pain point for businesses, especially as inbox providers get stricter.

How does Unosend achieve such high deliverability rates? Are there built in tools for domain warmup and reputation management?

Curious about how it handles bounce rates and spam complaints to maintain that deliverability level over time.

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@vimal_polara2 


How we achieve 99.9% deliverability:

  1. Own infrastructure - We run our own mail servers, full control over IP reputation

  2. Automatic authentication - SPF, DKIM, DMARC configured automatically when you verify your domain

  3. IP warmup - Gradual ramp-up for new senders to build reputation

Bounce & complaint handling:

  • Real-time bounce detection - hard bounces are auto-suppressed

  • Complaint tracking - users who mark spam are removed from future sends

  • Reputation monitoring - accounts with high bounce/complaint rates get flagged

Best practices enforced:

  • Domain verification required before sending

  • Rate limiting prevents sudden spikes that trigger filters

  • Separate IP pools isolate bad actors from good senders

TL;DR: Verified domain + automatic authentication + reputation management = inbox delivery. We handle the hard stuff so you just call the API.

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landing page looks pretty wack on darkmode firefox.

as a paying resend user, why should i switch to unosend?

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here are some features that are fairly table stakes to me:

- be able to have multiple projects with their own domains
- simple API

-deliverability metrics

- (nice to have) some idempotency protection

-( nice to have) a sense of best practices and if my emails meet them

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@catt_marroll 

Dark mode bug: Thanks for flagging - will fix that ASAP.

Why switch from Resend:

Multiple projects with own domains - Yes, built-in
Simple API - Same RESTful simplicity you're used to
Deliverability metrics - Opens, clicks, bounces, complaints
Idempotency - Coming soon
Best practices check - On the roadmap

What you get that Resend charges extra for:

  • Contacts/Audience - built-in, no external DB needed

  • Broadcasts - send to all contacts natively

  • Webhooks - included, no Zapier required

Pricing: More generous free tier + lower costs at scale.

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How does deliverability compare to Resend? Are you likely to end up in spam for gmail or outlook? Additionally, do you have any protection in place to prevent people abusing the service, and then get the other people using the service to be marked as spam?

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@joshh_founder 

Deliverability:

We run our own email infrastructure - full control over IPs and reputation. Proper SPF, DKIM, DMARC is automatic for every verified domain.

Abuse Prevention:

  • Domain verification required before sending

  • Rate limiting & bounce monitoring

  • Separate IP pools - bad actors don't affect you

  • Dedicated IP option on Scale/Enterprise plans

Bottom line: Verified domain + our authentication = inbox delivery. We maintain our IP reputation and isolate problematic accounts to protect everyone.

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@bittucreator I will definitely give unosend a try!

My recommendation would be to change up the UI a little, it feels like a clone of resend (which I currently use) and I think that could hurt the trust of customers who already know Resend.

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@soyzamudio 

Thanks for the honest feedback! 🙏

We actually just redesigned our entire UI with a fresh new layout. You can check app now.

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I'm really interested in using it for a Waitlist🙏🏽my flow is: user signs up, unosend collects the email as contact, unosend sends Email confirmation to user, 1 week later Unosend automatically sends a reminder to All users. Can I create all that with Unosend alone? I went through your Docs, I think Unosend can do all that. Just wanted a short confirmation before I start hacking. Resend forces me to buy webhooks externally (zapier, supabase, mailchimp) which for me defeats the purpose of using Resend at all.
1
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@nrique Your products looks amazing! I’d love to collaborate with you if you’re interested. message me on zangi:49_4234_0277 OR telegram username below 👇 @Fanspage12p
0
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@nrique 

Yes, Unosend can handle that entire flow!

Here's how:

  1. User signs up → Use our REST API to add them as a contact (Audience/People)

  2. Collect email as contact → ✅ Built-in with our Audience feature

  3. Send email confirmation → ✅ Use our Send Email API immediately after signup

  4. 1 week later send reminder → ✅ Use our Broadcasts feature to send to all contacts, or set up a Campaign for scheduled/automated sends

The key difference from Resend: We have built-in:

  • Audience/Contacts management - no external database needed

  • Broadcasts - send to all or filtered contacts

  • Campaigns - scheduled and recurring emails

  • Webhooks - track delivery, opens, clicks natively

No Zapier, no Supabase, no external webhooks needed. Everything is built-in.

Start hacking! 🚀

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@bittucreator @Unosend Looking good and feature packed, pricing also makes sense. Two questions though -

1. Is there plan for drag and drop templates?
2. Why is regional pricing only for India, when there are other countries where PPP is needed even more?

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I signup and add domain but email are not going to recipient

on api response showing success

{"id":"ba75eee6-853e-4b60-8cb6-a0834a9b0a47","from":"verification@no-replay.mingleq.com","to":["sankalpchoudhary8@gmail.com"],"created_at":"2025-12-05T06:04:33.245466+00:00"}

Show raw log

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Running into this issue when setting up outgoing mail with Supabase

In your case, Supabase’s auth service is doing this:

  1. Connects to smtp.unosend.co on whatever port you specified.

  2. Tries to use TLS (either because you told it “SSL/TLS” in the settings or because it does STARTTLS if the server advertises it).

  3. During the TLS handshake it checks the certificate.

  4. The server presents a cert whose hostname is localhost.

  5. Supabase compares that to the host you configured smtp.unosend.co and goes “nope” and throws:

tls: failed to verify certificate: x509: certificate is valid for localhost, not smtp.unosend.co

I don't see a way to contact support anywhere on the site? So I am posting here to hopefully make the devs aware of this issue and resolve it?

0
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#11
Google Workspace Studio
Build your AI agent in minutes to delegate the daily grind
151
一句话介绍:Google Workspace Studio是一款内置于Gmail、Docs等办公套件中的无代码AI智能体构建平台,通过自然语言指令创建自动化工作流,在邮件处理、报告生成等日常办公场景中,解决了团队重复性工作繁琐、效率低下的痛点。
Productivity Artificial Intelligence No-Code
AI智能体 无代码开发 办公自动化 Google Workspace Gemini 3 工作流自动化 企业SaaS 生产力工具 团队协作
用户评论摘要:评论普遍对产品发布感到兴奋,认为其将普通用户转变为“AI自动化设计师”,并认可其推理能力的提升。一条评论提及“Golden Kitty”奖项,并联想其未来可能向AR/VR搜索场景扩展。
AI 锐评

Google Workspace Studio的发布,远不止是在现有办公套件上增加一个“智能功能”。它标志着谷歌正将其最核心的企业产品矩阵,系统性、平台化地推向“智能体化”时代。其真正价值在于两点:一是“入口即平台”,将全球数十亿用户早已习惯的Gmail、Docs等入口,直接转化为低门槛的智能体开发与部署环境,这种迁移成本之低是任何独立创业公司无法比拟的;二是“去技能化赋能”,它试图将原本需要流程分析、API集成乃至基础编程知识的自动化构建,降维成自然语言描述,让“自动化设计”从IT部门专项能力,泛化为普通知识工作者的基础技能。

然而,其面临的挑战同样尖锐。首先,在封闭的Workspace生态内生成的智能体,其能力边界和对外部数据的连接能力存疑,可能沦为“温室里的自动化”。其次,将复杂业务逻辑交由自然语言描述和AI理解,其过程的可靠性、可调试性与权责界定,是企业级应用必须跨越的鸿沟。最后,这本质上是谷歌对其企业用户工作流与数据的更深层次绑定,在带来便利的同时,也引发了关于生态锁定的新一轮顾虑。

总体而言,这是一步极具野心的战略落子。它并非追求功能的炫技,而是旨在重塑企业办公的生产关系——将人从执行流程的节点,逐步转变为定义和优化流程的“管理者”。成功与否,将取决于其智能体在实际复杂工作场景中的真正“智商”与“可靠性”,而不仅仅是演示中的“情商”。

查看原始信息
Google Workspace Studio
Google Workspace Studio lets anyone build AI agents inside Gmail, Docs, Sheets, and more! No coding needed. Powered by Gemini 3, it turns natural language prompts into workflows that can triage emails, generate reports, or coordinate projects. Designed for teams, it brings real agentic automation to everyday office work.
Hey everyone! Google just launched Workspace Studio! An agentic AI platform built into Gmail, Docs, and Sheets. You describe the task, Gemini 3 builds and runs it. Feels like the moment Google turns everyday Workspace users into AI automation designers.
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Really curious to try this out, the reasoning improvements sound solid.

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The Golden Kitty nod shows impact. What’s next, maybe expanding search into immersive AR or VR contexts?

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Excited to try this out!

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#12
TypMo
Write wireframes. Generate prompts. Ship products.
146
一句话介绍:TypMo是一款将文本描述、草图或提示词即时转换为线框图的工具,并能为AI编程工具生成详细实现提示,在早期产品设计阶段以极低成本快速厘清结构、验证想法,解决“盲目提示、开发返工”的痛点。
Design Tools User Experience Prototyping
线框图工具 AI提示工程 设计转代码 产品原型 Markdown设计 快速迭代 设计协作 AI辅助开发 设计系统 前端设计
用户评论摘要:用户普遍赞赏“Markdown画线框图”的简洁理念与即时渲染的流畅体验,认为其在灵活性与清晰度间取得平衡。主要问题集中于商业模式、处理复杂多屏流程的能力,以及输出提示与具体AI工具(如Cursor)的对接细节。
AI 锐评

TypMo的实质,是试图在“想法”与“代码”之间,重新夺回并标准化“结构设计”这一关键环节的控制权。它敏锐地戳中了当前AI编码热潮中的一个隐性成本:由于缺乏前置的、机器可理解的结构化设计,开发者与AI之间陷入低效的“提示-试错”循环,导致时间与金钱的浪费。

其价值并非在于创造了多强大的线框图工具——市场上此类工具已很丰富——而在于它充当了一个“结构编译器”。它将自然语言、草图等模糊输入,以及其特有的类Markdown文本语法,编译成一种既人类可读(可视化线框图)又机器可读(结构化提示)的中间层表示。这个中间层,正是当前AI开发工作流中缺失的“设计契约”。

“60+组件,零学习曲线”的宣传,凸显了其降低早期设计门槛、鼓励快速实验的定位。然而,其真正的挑战与天花板也在于此:当设计从“可视化拖拽”简化为“文本描述”时,其表达复杂交互逻辑和精细视觉层级的能力是否会受限?它生成的“详细实现提示”能否真正满足不同AI编码工具(如Cursor、Claude、GPT)的差异化需求,还是需要二次调整?这决定了它是仅适用于早期头脑风暴的“玩具”,还是能贯穿至详细设计阶段的“生产力工具”。

创始人强调“Clarity before code”(清晰先于代码),这切中了要害。TypMo的真正对手或许不是Figma,而是混乱的提示词和昂贵的开发试错。如果它能成功地将“先画图,再提示”的工作流植入开发者心智,并使其生成的结构化提示成为AI开发的事实接口之一,那么它的价值将远超一个工具本身,而成为AI时代产品定义流程的新标准组件。但目前来看,它仍是一个前景可观但需验证其边界与深度的早期解决方案。

查看原始信息
TypMo
TypMo is where wireframes become prompts. Write UI in simple text syntax, like Markdown, or generate from prompts and sketches. 60+ components, zero learning curve. Iterate freely when changes are cheap, share with stakeholders, gather feedback. Then export detailed implementation specs for AI Coding tools. Clarity before code. Wireframe first, prompt with precision.

Hey Product Hunt! 👋 I'm Adit, founder of TypMo. In the age of AI coding tools, I noticed a problem: we're spending significant time and money prompting without structural clarity. The wireframing stage is where experimentation should happen, it's fast, cheap, and low-risk. So I built TypMo—where wireframes become implementation prompts.
It's Markdown for wireframes, a simple text syntax using design vocabulary you already know. No learning curve. Just type and see your UI render instantly.

With TypMo you can:

  • Generate wireframes from prompts, sketches, or PRDs

  • Run IA/UX audits on your structure

  • Iterate on hierarchy, flows, and components freely

  • Export implementation prompts when you're ready

That's where TypMo lives - the cheap zone where messy ideas become organized, prompt-ready structure. Experiment freely, validate fast, then let AI build exactly what you need, the first time.

Clarity before code. Wireframe first, prompt with precision.

I would love to have your feedback! Thank you!!

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@aditgupta @TypMo

I’m really impressed by TypMo — it strikes an excellent balance between flexibility, speed, and clarity. Writing UI in simple text (like Markdown) feels natural and removes the friction of traditional drag-and-drop design tools. The ability to instantly render wireframes and then export detailed implementation specs is a huge win — especially useful when you want to quickly iterate on ideas or hand off to developers or AI-based tools.

What truly stands out is how TypMo makes “iterate first, refine later” a seamless workflow: early ideas can stay messy while you experiment, then once you’re confident, you convert them into clean, prompt-ready UI structure.

Overall, TypMo helps turn messy brainstorming into organized, actionable design — highly recommended for anyone building interfaces, prototypes, or prepping designs for coding or AI-assisted development.

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@aditgupta Markdown for wireframes feels like the right level of simplicity.

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@aditgupta Congrats on the launch Adit, TypMo looks clean and useful. Upvoted. I am co founder of bestofweb .site and after your launch if you want more visibility you are welcome to join and introduce UX Assist to our founder community.

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Super nice. Congratulations on the launch!

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@chilarai Thank you!! 🙂

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Sounds really interesting! How is the business model behind?

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@german_merlo1 Thank you! It's a freemium subscription model. I have started with an early launch price of $39.99/year for next one month. Very soon we will have monthly and team plans too. 🙂

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Congrats.. interesting product .. all the best
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@dessignnet Thank you!! 🙂

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Translating wireframes into UI prompts – I really like the thinking and agree with the problem this is trying to solve. I will definitely give it a try!

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@jamiesunde Thank you, Jamie! 🙂 This is super motivating to hear!

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Congratulation @aditgupta Love the “Markdown for wireframes” idea - that’s a super clean mental model.
How well does TypMo handle complex multi-screen flows?

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@digitalpreetam Thank you Preetam! TypMo supports multi-screen flows for both wireframing and prompt generation. Here's one small video about it - https://youtu.be/mtIf2vH7urk

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Very unique and convenient. Check if I understand it correctly, we need to write our structure and it designs a wireframe and the output is the prompt that we can feed into cursor?

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@himani_sah1 Thank you so much!! 🙂 Yes, you can either write the structure (my preferred way!) OR generate it from prompt or by uploading your sketch. Three different ways to get the wireframe and then generate production-ready prompt for any AI coding tool. The generated prompt will have the following:

1. Project overview and architecture - key features, success criteria, user flow
2. Project structure
3. Data models and typescript interfaces
4. Detailed component breakdown
5. Routing and Navigation
6. State management
7. Authentication
8. Accessibility
9. Performance Optimimisation
10. Testing Strategy
11. Styling approach
12. Error handling and edge cases

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#13
2025 Annual Review
It's like Spotify Wrapped for Your Journal
143
一句话介绍:一款AI驱动的年度回顾生成工具,通过一键分析全年日记内容,自动生成结构化的年度总结初稿,解决了用户在年终复盘时面对海量记录无从下手、耗时费力的核心痛点。
Health & Fitness Productivity Artificial Intelligence
个人成长 日记分析 年度复盘 AI摘要 心理健康 效率工具 生成式AI 生活方式 数字记忆
用户评论摘要:用户普遍认可“日记版Spotify Wrapped”概念,认为其降低了复盘门槛。核心反馈包括:1. 建议增加对未来目标的规划功能;2. 好奇AI分析的具体参数与逻辑;3. 探讨如何通过即时反馈和长期视角提升用户留存与“顿悟时刻”。
AI 锐评

“2025 Annual Review”精准切入了一个被长期忽视的“后市场”:日记记录之后的价值挖掘。它聪明地避开了与Day One等巨头在记录功能上的正面竞争,转而扮演“记录终结者”的角色,将用户已沉淀的、非结构化的文本数据转化为结构化洞察。

其真正价值并非炫酷的AI技术本身,而在于它通过自动化“初稿”创造了一个极低的反思启动成本。正如联合创始人Dave所言,它“不取代深度反思工作”,而是解决“从0到1”的最大阻力。这击中了现代人“想复盘但畏难”的普遍心理。然而,这也恰恰暴露了其核心挑战与潜在局限:产品的终极价值高度依赖于用户原始日记的数据质量与连续性。对于“三日记”用户,再强大的AI也难为无米之炊。这迫使产品必须反向促进更优质的记录行为,其评论中提到的“即时洞察”功能正是对此的补足。

从商业模式看,它可能成为日记应用的“标配功能”而非独立生态。其未来想象空间在于能否从“年度总结”扩展到更丰富的叙事生成(如项目复盘、旅行记忆),并建立基于用户许可的、去隐私化的群体情绪或趋势洞察数据库,从而构筑更深壁垒。目前,它是一个优雅的“功能型产品”,但要从“有用”到“不可或缺”,仍需在激发持续记录与提供更深层认知价值上,找到更独特的答案。

查看原始信息
2025 Annual Review
This year we have completely reimagined the Annual Review. With a single click, Reflection instantly gathers your 2025 journal entries to generate a beautiful "first draft" of your year. See key moments, wellness overview, growth patterns, all formatted in a stunning and easy to edit recap. Giving you a massive head start on your end-of-year reflection without the heavy lifting. We can't wait to hear what you think!
👋 Hey hey! Dave here, co-founder of Reflection. We all know the power of an Annual Review. Looking back helps us move forward with intention. But for many.. the process is usually a slog. Re-reading a year's worth of journal entries, your photos, your calendar... can take hours (or days), and it’s easy to get lost in the weeds without actually doing a meaningful retrospective. This year, we completely reimagined the process. With a single click, our new Annual Review scans your 2025 entries and generates a "first draft" of your year. Think of it like Spotify Wrapped for your journal. 🎧 It instantly highlights: • Title to summarize your review • Wellness Overview • Top Memories • Growth Patterns • And more. It doesn’t replace the deep work of reflection—it just gives you a massive head start. You can edit anything, add your own nuance, and even share it with a private link. Excited to hear what you think! Dave
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Congrats on the launch!

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Thanks @francescod_ales !!

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Great idea with the year-end summary. Can the app also suggest a plan, motivation, and goals for next year?

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I've tried every journaling app out there—Day One, Journey, you name it. They all felt like digital storage boxes. Reflection feels like a conversation. The AI prompts aren't generic; they actually pick up on what I wrote yesterday and ask follow-up questions that make me dig deeper. It's like having a therapist and a life coach in my pocket. The cross-platform sync is flawless—I start on my Mac at work and finish on my phone in bed. Truly a game-changer for my mental clarity.

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I love the concept and great timing on bringing it on here one day after the wrapped came out of Spotify 🤣, but i do believe that for us to understand what's to come, it's very important to revisit the past, and i love how you're product helps the users do a context dive. All love, wish you the best.

I am curious tho, what parameters are you reading the delta for?

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@ssindhia haha thanks! honestly, the timing was pure luck. we were already planning to launch today, and I had no idea that Spotify Wrapped was just rolling out for everyone. feeling really lucky about that. 😅

The annual review starts with entries based on January and goes through to the end of December. But the user can always regenerate after adding new entries at any point.

And yeah, I agree. I think it's actually important to revisit and reread a lot of the entries. Our goal here was to remove the friction, allow users to see the benefit, and then go back, edit, update, and enhance their annual review.

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Congrats on the launch. Many journaling apps struggle because reflection still feels like a task. From an onboarding & retention perspective, what’s the moment when a user actually feels the reset, not just sees the prompts? That feeling is usually what drives long-term use.

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Thanks @joydeep_pandey You're spot on. That "aha" moment is tough to nail, especially with journaling. Sure, there's that instant clarity you get right after writing an entry. But like you're saying, the real value comes from doing it consistently and then looking back to gain perspective.

We actually rolled out a feature a few months back where we show users insights right after they create an entry—stuff that connects to their past entries. We noticed this made a huge difference in how people felt after journaling and whether they'd come back. Seeing those connections and getting a quick synthesis of their entry helps users feel the benefits immediately. And the more they journal, the more perspective they build up over time.

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#14
Stardrift
Your Personalized AI Travel Planner
133
一句话介绍:Stardrift是一款个性化AI旅行规划助手,通过与用户对话并整合日历与实时价格信息,在复杂的多行程旅行规划场景下,解决了用户因比价繁琐、行程协调困难而拖延预订并最终支付高价“恐慌税”的痛点。
Productivity Travel Business Travel
AI旅行规划 个性化行程助手 实时比价 日历整合 免费旅行工具 机票酒店预订 Amtrak查询 行程管理 智能助理 出行科技
用户评论摘要:用户普遍认可其解决行程规划繁琐的核心价值,对日历同步和实时价格功能表示期待。主要问题与建议集中在:是否支持团队旅行规划、多城市及紧密换乘规划能力、“预订”按钮跳转逻辑不统一、未来是否整合餐厅/活动推荐及完整行程规划。创始人积极回复,透露餐厅推荐等功能已在规划中。
AI 锐评

Stardrift切入了一个看似拥挤但实则未获根本性解决的赛道:个性化、端到端的复杂旅行规划。其宣称的价值不在于简单的信息聚合,而在于充当一个理解个人日程与偏好的“执行助理”,试图将用户从数十个浏览器标签的碎片化信息中解放出来。这是一个高明的定位,直接瞄准了商务人士和精打细算旅行者的“决策疲劳”与“恐慌性消费”痛点。

然而,其面临的挑战与机遇同样尖锐。从评论反馈看,其“真正价值”的兑现度尚存疑问:其一,技术整合深度。“连接日历”与“获取实时价格”是基础能力,但关键在于AI能否真正理解“会议冲突”的优先级或“价格/时间权衡”的个人偏好模型,这需要远超当前规则引擎的推理能力。其二,商业模式悖论。作为免费工具,其“预订跳转至航司官网”的设计,虽规避了牌照与佣金难题,但也将最关键的交易与用户体验断点拱手让人,未来商业化路径模糊。其三,场景扩展压力。用户已开始追问团队出行、餐饮推荐等延伸需求,这与其当前聚焦“物流规划”的定位产生张力。分散精力可能削弱核心,但固守一隅又难以构筑壁垒。

本质上,Stardrift的价值不在于替代Skyscanner或Google Flights,而在于试图成为旅行决策的“智能层”与“协调中枢”。它的成功不取决于功能清单的长度,而取决于其AI在模糊、多约束条件下做出“令人信赖的优质推荐”的能力,以及能否在免费模式下找到不损害用户体验的可持续生存方式。目前看来,它点燃了一个正确的需求引信,但炸药当量能否炸开OTA巨头的城墙,仍是未知数。

查看原始信息
Stardrift
Stardrift is your personalized AI travel agent - chat with it to plan your next trip, as if it's your dedicated executive assistant. Stardrift fetches live prices, connects to your calendar and learns your preferences to find the right flights, hotels and train journeys for you.

Hey Product Hunt! I'm Leila, the founder of Stardrift.

Have you ever put off booking a trip too long because it's such a pain - and paid for it by buying last-minute tickets at a steep price?

It’s complicated! You need to check your schedule, weigh off different price/time comparisons, and think about every leg of your trip and make sure your connections work.

In an age of AI, it's crazy that there isn't a better solution. That's why we built Stardrift, your personalized AI travel planner. Stardrift can:

  • ✈️ Pull live hotel, flight and Amtrak prices & availability

  • 💵 Help you construct an end-to-end itinerary, pricing out and comparing each leg

  • 🗓️ Connect to your calendar and find the details of any meetings or conflicts

Even better, it's entirely free and available today - no waitlist or demos. Sign up and try it out today at stardrift.ai!

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@leilaclark great ai planner idea... does it work to create travel plans for groups?

I just launched yesterday and I see potential collaboration in the future if you are open to it ;) We have complementary solutions for sure.

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We're also live today on Twitter! Check us out here: https://x.com/stardrift_ai

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Great launch Leila. Stardrift feels sharp and useful. Congrats to you and the team.

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I always put off booking then pay the panic tax. If it really pulls live fares and checks my Google Cal, I’m in. Curious about multi-city and tight Amtrak connections. Trying it on my NY-DC-Philly run next week.

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It was always a headache opening 10 tabs to compare flights and hotels. Thanks for building this

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This is clutch! Love that it syncs with your calendar.

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@ramnik_arora Thanks! :)

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The “book” button just redirects to an airline website, not to a specific flight. Is that by design?

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@ihor_onyshchenko It depends on the airline! Usually they should link to the specific flight.

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I’m excited to be a power user - congrats on the launch; this looks awesome!

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This is amazing @leilaclark ! Will we be able to also get restaurant/event recommendations?

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@lusine_mnatsakanyan4 We expect to add restaurants down the line!

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Great launch, Stardrift team. From a clarity & onboarding lens: when a frequent traveller opens Stardrift for the first time, what’s the one belief you want them to hold in the first 10-15 seconds?
Is it:
• “This trip will work optimally for me, not just a flight booked.”
Or:
• “This assistant already knows how my schedule and constraints matter.”
Because in complex-trip tools, adoption hinges more on mental alignment than features. Curious how you’re shaping that.

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Congrats! Besides transport and hotels, are you planning to add full trip itinerary planning too?

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@zhiqi_shi Our main focus right now is on the logistical planning, but we may add it down the line!

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#15
Seedream 4.5
High-fidelity multi-image editing & dense text rendering
125
一句话介绍:Seedream 4.5是一款面向专业视觉创作者的AI图像编辑工具,通过高保真的多图融合与精准的密集文字渲染功能,解决了复杂视觉设计中元素整合困难与图文排版失真的核心痛点。
Artificial Intelligence Photo editing
AI图像编辑 多图融合 文字渲染 高保真 专业设计工具 视觉创作 多模态模型 图像生成
用户评论摘要:用户普遍赞赏其多图融合与文字渲染效果出色,图像真实感强。主要与Google Nano Banana Pro对比,认为其在性价比上有优势,但后者在图像真实感和多人场景处理上仍略胜一筹。有用户询问未来是否会支持更多语言。
AI 锐评

Seedream 4.5的发布,与其说是一次版本迭代,不如说是一次精准的赛道卡位。它避开了与巨头在“通用文生图”质量上的正面肉搏,转而深耕“多图像编辑”与“密集文字渲染”这两个专业创作中的硬骨头。其宣称的“空间逻辑”能力,本质上是将AI图像生成从“像素合成”推向“视觉推理”,试图让AI理解图像中元素的布局、透视与逻辑关系,这正是当前专业工作流中最迫切的需求。

然而,光环之下暗藏挑战。用户评论虽积极,却反复将其与“Google Nano Banana Pro”对标,这本身就揭示了Seedream仍身处巨头的阴影之下。评论指出其在“图像真实感”和“多人场景”上的细微差距,恰恰点中了专业级应用的生命线——极致效果。目前其优势看似是“性价比”,但这在技术快速迭代的AI赛道是一个脆弱的壁垒。一旦巨头降价或推出针对性功能,优势可能瞬间蒸发。

其真正的价值,在于为专业视觉创作者提供了一个高度垂直且效率导向的“手术刀”。它不是万能的“瑞士军刀”,但可能在特定的商业设计、营销物料合成、复杂排版等场景中,成为不可或缺的生产力组件。它的成功与否,将不取决于能否全面超越巨头,而在于能否在其细分领域建立起足够深的护城河,并快速将技术优势转化为不可替代的工作流集成。下一步,它需要证明的不仅是模型能力,更是对专业场景更深度的理解与生态构建能力。

查看原始信息
Seedream 4.5
Seedream 4.5 achieves all-round improvements via model scaling. It excels at accurate multi-image editing, strictly preserving reference details, and rendering dense text/typography with high fidelity—built for professional visual creatives.

Hi everyone!

@Google Nano Banana Pro has just met a serious challenger. Seedream 4.0 was already impressive, but 4.5 takes multi-image fusion and dense text rendering to a completely new level.

It nails the details when blending multiple inputs. The typography is crisp and it finally handles complex layouts without messing up the text. Thanks to the "Spatial Logic".

The industry consensus is clear. The next phase of image generation is about logic and reasoning instead of just pixels. Top-tier multimodal models lower the barrier for visual creation. Seedream 4.5 makes professional expression efficient and accessible for everyone.

@Higgsfield , Fal, and @ImagineArt already support 4.5. The list is growing!

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Just tested it and it's realy good. I still think google Nano Banana Pro is better with more realistic images and multiple people in an image. But price-wise Seedream 4.5 beats Banana Pro and they are trying to really close the gap to google's SOTA image model.

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I think the images are fire, I love this tool. And what you say is actually true Nano banana Pro even though is better I think you two are competing.

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Any chance you’ll be adding more languages in the future?

The realism of the photos is honestly amazing••••

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Very realistic gallery. Really impressive

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It is so good that it is scary. Crazy how AI can replicate visuals to such an extent.

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#16
Claude-Mem
An AI that takes notes on other AI's work in real-time
119
一句话介绍:Claude-Mem是一款实时记录AI工作内容的工具,在软件开发等长期项目协作场景中,解决了AI助手因会话隔离导致的“记忆缺失”痛点,将碎片化对话转化为可搜索、可追溯的永久知识档案。
API Developer Tools Artificial Intelligence GitHub
AI记忆增强 开发协作工具 会话存档 知识管理 实时旁注 上下文持久化 软件工程 智能压缩 团队协作 Product Hunt发布
用户评论摘要:用户肯定产品解决了AI“健忘症”的核心痛点,期待“记忆涌现”时刻。创始人详述了从“简单存档”到“智能压缩”的产品逻辑。技术询问聚焦于运行方式(IDE插件/独立服务)与自动化程度,与手动保存Markdown的区别是关注重点。
AI 锐评

Claude-Mem的野心不在于“记录”,而在于“定义记忆”。它戳穿了当前AI协作的一个华丽假象:我们以为在与一个持续学习的智能体对话,实则每一次回车键后,面对的都可能是一个“最熟悉的陌生人”。产品将“记忆”重新定义为“有损压缩”,而非“完整存储”,这是其最犀利的洞察。

然而,其真正的挑战与价值均在于此。价值在于,它试图将人类项目协作中至关重要的“上下文”和“决策流”结构化,让AI从“临时工”转向拥有“项目经验”的“长期雇员”。这直指AI赋能深度工作的核心障碍。挑战则在于,如何确保“压缩”算法抓取的是真正关键的“灵光时刻”,而非无关噪音。创始回复中“它几乎不需要回头看”的表述,既是理想状态的描绘,也暗含了最大的风险——如果记忆的提取与注入存在偏差,用户将在无形中被一份可能失真的“历史”所引导。

当前它更像一个精巧的技术实验,其成败将取决于压缩算法的“智慧”程度。若能成功,它将成为AI融入复杂工作流的“中枢神经系统”;若失败,则可能只是另一个制造信息坟场的优雅工具。它提出的终极问题比产品本身更深刻:在AI协作中,究竟什么值得被记住?

查看原始信息
Claude-Mem
Transform ephemeral AI conversations in REAL-TIME as a permanent, searchable archive. Visualize development timelines, track decisions across commits, and collaborate with your team.

Congrats on the launch! Claude Mem looks like the next step in making AI actually meaningful over time. What’s the moment users say, “Oh wow—it remembered what I said last week”?

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@joydeep_pandey it takes about a week for them to have that revelation 😂

Thank you so much for the kind words. :))

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You know that moment when you open a new Claude session and realize you have to explain everything again? "So we decided to use SQLite because—" Stop. Claude doesn't remember. You're strangers again. That frustration is why I built claude-mem. AI assistants have amnesia. For quick questions, it doesn't matter. But real software projects span weeks. You make decisions on Tuesday that matter on Friday. You debug for three hours and finally find the root cause. That insight should persist—but it doesn't. Every session starts from zero. The naive solution was obvious: save conversations, search later. Tried it. Useless. Thousands of tokens of noise. What matters isn't the forty-seven files Claude opened—it's the moment you realized why the bug happened. Memory isn't storage. It's compression. So claude-mem watches Claude work, captures what matters, compresses it, and injects it into future sessions. Invisibly. You don't see memory forming—it just happens. Context arrives before you notice it was missing. The whole thing was built using itself. This comment? Written by Claude searching its own memories of the last ten weeks of development. Would love to hear how others are thinking about AI memory and continuity. What would you want an AI assistant to remember?
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@az_ne This resonates with project work, what’s the most surprising thing Claude remembered that changed your process?

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@az_ne Congrats on the launch Alex, this is sharp work. Upvoted. I am co founder of bestofweb .site and after your launch if you want more visibility you are welcome to join and introduce Claude Mem to our founder community.

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@az_ne Everything... that's part of my problem though. I'd want it to track keyword and build sentiment rich knowledge graphs. Basically autorag with a wiki index.

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Wow! This is really amazing idea.
So does it stay inside an IDE as an observer or inside a Git repo?

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@chilarai the plugin runs a worker that queues tool use responses and prompts, that generates observations

Worker is on :37777

There’s an http api in there

And then search-server is an mcp file that is routed to the http API to stay DRY and offer ability to use MCP anywhere

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I usually store research conversations as markdown. And give it to an AI to then implement in the code. Is this what this sort of does, but more automatically? Or how doe sit work?

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@conduit_design no this takes notes in the background while you work.

You build with Claude code, and in background in real-time Claude-Mem uses anthropic’s agent-sdk to essentially run another Claude code alongside, that watches live, generates observations.

Then a timeline of the work u did plus id’s for the full observations so Claude can look stuff up if it needs to. But it barely ever needs to.

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#17
Weather mini 3
Trip forecasts with on-device AI
117
一句话介绍:一款通过本地AI提供旅行天气一站式预报的轻量级天气应用,解决了用户在规划多城市行程时需要反复切换查询的痛点。
Productivity Weather Artificial Intelligence
天气应用 旅行规划 本地AI 苹果生态 轻量级 设备端智能 隐私安全 极简设计 多端同步 情景化预报
用户评论摘要:用户普遍称赞其极简主义设计和精美的插画。开发者积极互动,解释了采用本地AI(Apple Intelligence)的隐私与便捷优势,并回应了关于Mac版核心价值(Dock栏快速浏览)的探讨。有用户提出了与第三方高精度数据API合作的可能性。
AI 锐评

Weather mini 3的叙事巧妙地站在了当前AI应用的两个风口:一是“设备端AI”带来的隐私与即时性红利,二是“情景化”而非“工具化”的产品思路。它宣称通过系统框架实现,避免了大型语言模型的下载与数据上传,这与其轻量级的定位一脉相承,本质上是将苹果的系统能力进行了精明的产品化封装。

其核心价值“旅行预报”,看似是功能的叠加,实则是场景的切割。它没有选择与专业天气应用在数据维度上竞争,而是精准切入“多城市行程规划”这一具体、高频的决策场景,将分散的天气信息整合为一份行程报告。这使其从一个“查询工具”转向了“规划助手”。

然而,其挑战也隐含其中。首先,其体验深度高度依赖苹果生态系统(WeatherKit, Apple Intelligence)的能力边界与迭代速度,自主性有限。其次,“轻量级”与“高精度”常存有内在矛盾,当用户对预报准确性提出更高要求时(如评论中提及的滑雪场景),仅依赖系统数据可能成为短板。最后,其精美的插画与情感化设计固然能建立差异化,但作为效率工具,长期留存的关键仍在于情景化预报的准确性与实用性是否足以改变用户的工作流。

总体而言,这是一款在苹果生态内做得相当聪明的产品:用最小的技术负债,抓住设备端AI的早期叙事,并将天气信息重新包装为一种情景服务。它未必能满足所有天气查询需求,但旨在成为特定场景下最优雅、最省心的那一个。

查看原始信息
Weather mini 3
Weather mini 3, with all-new illustrations and helpful trip forecasts, is now available on more devices. New trip forecasts show all your stops at once, instead of checking the weather city by city. On-device Apple Intelligence provides helpful trip insights directly from the device, making it safer and faster.

You nailed minimalistic design!

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@busmark_w_nika Thanks so much! Glad you like it! 😊

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Hi Product Hunt!

We first launched Weather mini for Mac here in 2020. Since then, a ton has changed — and today we’re back with Weather mini 3, a lightweight weather app for iPhone, iPad, Mac, and Vision Pro.

What’s New in Version 3

  • All-new weather illustrations with animations

  • New widgets & Dock icons

  • Trip forecasts with Apple Intelligence

Trip forecasts is a new feature for iOS and iPadOS. (coming very soon to Mac and Vision Pro)

It lets you check the weather for places and dates all at once, so there’s no need to jump between apps when planning a trip, especially to unfamiliar places.

With on-device Apple Intelligence, you can just type something like “Tokyo and Hong Kong next week” and get trip insights like daily weather, summary, notes, city context, and clothing tips in a few seconds. All happens right on the device since we just use system frameworks like WeatherKit, no 3rd party services at all, which means: there’s no huge LLM downloading, no data sharing or uploading, no usage limits in the app.

That’s it, new design, same lightweight weather app, now available on more Apple devices.

Please share your thoughts and feedback with us in the comments if you try it.

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Such beautiful illustrations. Just love how the color palettes and tones combined with UI.

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@winterx Thank you! We wanted the illustrations and colors to soften those “bad-weather” moments. Really happy you felt that!

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Will try out your app before planning my skiing trip. Thanks!

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@stanislav_terk Awesome, thanks! Let me know how it works for your trip!

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Wonderful. Something I was looking for a long time.
Will try out

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@chilarai Awesome! Would love to hear your feedback.

3
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Oh wow I love the UI design here. Really amazing! Great work guys!

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@ansh_deb Thanks so much! Glad you like it!

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Why an illustrated weather app?

As the designer behind Weather Mini, I wanted weather to feel less cold and data-heavy.

Even on a rainy day, a little illustration can brighten the moment.

If Weather Mini can give someone a tiny lift when the sky looks gloomy, that’s the goal.

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Hey guys, great launch! Upvoted! Maybe a collab with rainbow ai could work for you well — they have the most accurate weather data (mostly precipitation for now) in the world and give it by API to others
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@svyat_dvoretski Thanks so much for the upvote! We really care about forecast accuracy as well. I will definitely take a look at Rainbow AI and see what they offer.

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When designing our AI features, we avoided third-party cloud services and heavy local LLM setups. Instead, we rely on what’s already built into users devices — no accounts, no downloads, no configuration. The goal is simple: a truly easy, “just works” experience that’s good enough to be useful in real life.

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Great to see Weather mini for Mac back and stronger. From a clarity & onboarding lens: when a user opens the app for the first time, what’s the one belief you want them to hold in the first 10–15 seconds?
Is it:
• “I can glance at this and immediately know what matters for my day.”
Or
• “This isn’t just weather—it fits my workflow, right in the dock.”
Because for glanceable Mac utilities, the difference between “nice app” and “essential app” often comes down to that first felt alignment.

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@joydeep_pandey For Mac users, Weather mini means: glance at the Dock, instantly know today’s weather — no windows needed. That’s the kind of small, essential Mac app we’re building.

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@joydeep_pandey That’s the magic of the Dock and Retina display. Imagine how the calendar app works: glance at the Dock to know the date, open windows for detailed information and interactions.
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@joydeep_pandey Thanks!
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Thanks for checking out Weather mini 3!

I’m Kai, developer of Weather mini, here with @Ann, who’s the designer of Weather mini. We are happy to answer your questions about development, new design, on-device AI, etc.

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#18
Orca
AI Agent for Game Development
117
一句话介绍:Orca是一款基于网页的AI游戏开发助手,通过自然语言对话即可生成代码、修复Bug、创建资产并整合实时游戏机制,让没有专业开发经验的创意者能快速将想法转化为可运行的游戏原型。
Indie Games Artificial Intelligence Games
AI游戏开发 无代码/低代码 网页应用 原型设计工具 AI智能体 创意实现 2D游戏 快速迭代 游戏资产生成
用户评论摘要:用户普遍对产品理念感到兴奋,认为其能大幅节省开发时间。主要反馈集中在:期待游戏托管/发布功能(团队回应即将推出)、建议增加游戏导出选项(如HTML)、遇到前端界面点击和登录等技术性问题。有评论深入探讨了产品应如何在初次接触时建立用户对“工作流契合度”与“可扩展性”的信任感。
AI 锐评

Orca的亮相,精准刺中了“创意过剩而技能不足”这一大众游戏创作市场的长期痛点。其宣称的“聊天构建游戏”并非简单的代码生成,而是试图扮演一个覆盖代码、资产、逻辑测试与迭代的“全能代理”,这比当前市面上专注于单一环节的AI工具有着更宏大的叙事。

然而,其真正的挑战与价值内核并非技术演示,而在于能否成为可靠的“共创者”。从评论看,早期用户已超出“猎奇”,转而关注实际产出物的处置(托管、导出)与协作深度(如何调整平衡性)。这预示着产品成功的关键,将从“能否做出东西”迅速过渡到“做出的东西是否可用、可迭代、可分享”。它必须构建一套AI能理解且稳定的游戏开发“语义体系”,将用户模糊的反馈转化为精确的工程调整。若仅停留在根据提示生成孤立片段,则易沦为玩具。

团队定位“辅助而非替代开发者”是明智的,但其愿景的实现,依赖于将非专业用户的自然语言,转化为专业、可扩展的游戏项目结构。这条路充满陷阱:既要足够简单以降低门槛,又要足够严谨以支撑稍复杂的项目。否则,“快速原型”之后,便是用户激情撞上能力天花板的时刻。其长期价值,在于能否成为连接创意与复杂工程实践的那层关键抽象,而不仅仅是又一个令人惊艳却短暂的AI快消品。

查看原始信息
Orca
Build games by chatting. Orca is a web-based AI agent that writes code, fixes bugs, creates assets, and assembles real-time mechanics with no setup required. The simplest way to go from idea to a running prototype.

Congrats on the launch guys! I’m so excited to use this 🫶

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@ay_ush Thanks Ayush! Looking forward to playing your games.

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Hey Product Hunt! 👋 I'm Ege, co-founder at Orca with Ali. We've always loved playing games, they made so many of our best memories growing up. Whenever we'd play something inspiring, we'd dream about making our own, but there was one problem: we're not game developers. My first attempt at coding was actually trying to make a game in high school. It didn't work out. Fast forward to a few months ago, Ali and I were working on AI for a different product, decided to pivot, and spent a few days just... playing games. Then we both ended up in Cursor trying to build something, anything, with AI. The problem? Existing tools weren't made for AI game development. We hit wall after wall. Cursor's amazing for code, but games need so much more like assets, logic, testing, iteration cycles. We realized that if we're frustrated, other aspiring game makers probably are too. That's why we built Orca, an AI game dev agent that: Generates playable games from your ideas Create 2D characters and animations from chat Iterates with you, give feedback, refine, and actually ship Web-based agent, so no complex setup We're not trying to replace game developers. We're trying to help people like us who have ideas and passion but not years of Unity experience or money to hire a team, actually make something real. For Product Hunt: Get early access with code PRODUCTHUNT for exclusive launch pricing. Would love your feedback: What's a game you've always wanted to make but couldn't? What's holding you back? Thanks for being here! 🙏
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@egkduman I saw that Orca doesn’t just generate code but also iterates through a test–feedback loop.
In the early versions, which part does it focus on refining the most?
For example, can it adjust things like game balance or difficulty as well?

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Having an agent that actually assembles everything together saves hours. love how smooth that feels 😌

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Are we able to host the games we build for others to play? I couldn't catch that info. from the homepage.

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@nuseir_yassin1 Hey Nuseir, we are actively working on this, hopefully rolling it out in the next week or so! :)
ps: it will be as easy as clicking a button

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This is incredible and super bullish on the team!! Congrats on the launch, be right back, going to make some games now

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I tried the application and played and created a simple game. It was able to fix the bugs in the game after a few prompts.

Let users export the game and publish it as HTML or something. You can monetize that like Bolt or v0

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Solid launch, Orca 3 team. From a clarity & onboarding lens: when a developer opens Orca 3 for the first time, what’s the one belief you want them to hold in the first 10-15 seconds?
Is it:
• “This tool actually aligns with how I think and build, not just how someone expects me to build.”
Or:
• “I can trust this model/tool to scale with my workflow, not hold me back.”
Because in high-performance dev/AI tools, adoption hinges less on specs and more on the belief that it fits me. Curious how you’re shaping that moment.

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I can’t click on any of the games or assets shown in the home page.

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@admiralrohan Hey Rohan, we are building those as we build more games, the main product right now is the AI agent making the games. please do sign up and give it a try and if any issues do give me a ping :) we will soon enable hosting games so they are just as easily playable by others.

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Can't wait to try it. The website won't let me login

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@akeseer Thanks! are u trying with google or with email address?

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#19
IMAI Studio
AI Studio behind Product Creation
117
一句话介绍:IMAI Studio是一款AI驱动的产品视觉化工具,能将单张产品照片快速生成多种设计变体、高品质效果图及营销素材,解决了时尚消费品行业在原型设计、内容制作和营销测试中流程缓慢、成本高昂的核心痛点。
Design Tools Marketing Artificial Intelligence
AI设计工具 产品可视化 时尚科技 营销素材生成 3D/AR资产 快速迭代 电商赋能 设计协作 概念验证 数字样机
用户评论摘要:用户普遍认可其节省成本、加速迭代的价值,并获知名品牌使用验证。核心问题聚焦于目标用户信念塑造、适用品类拓展及具体使用场景(概念验证vs营销素材)。团队回复透露了视频生成、协作功能和品牌化UX的路线图。
AI 锐评

IMAI Studio并非又一个浮于表面的AI图像生成器,它精准切入了一个被“美化型AI工具”长期忽视的工业级缝隙市场:产品从设计到营销的可视化工作流。其真正价值不在于技术炫技,而在于充当了一个“可视化翻译器”,将设计师、制造商、营销团队之间极易失真的沟通,统一为可即时迭代的视觉语言。

产品介绍中“校准过的行业级色彩、材料和设计预设”是关键,这暗示其AI模型经过了特定垂直领域的专业数据训练,旨在解决通用AI工具输出“颜色怪异、场景不实”的行业痼疾。这使其从“玩具”升级为“工具”,直接对标昂贵的3D渲染、实物打样和摄影棚拍摄。

评论中透露的客户名单(H&M、Tata等)和亚洲市场的强劲需求,验证了其解决“海量SKU、紧迫工期、本地化内容”痛点的有效性。更有趣的是,团队提到制造商(品牌代工厂)的采用,这揭示了其可能从产业链上游切入,改变产品开发源头的协作模式,护城河更深。

然而,挑战同样明显。其一,如何在“赋予创意控制感”与“提供专业预设”之间取得平衡,是其用户体验设计的核心命题。其二,当从时尚品类拓展至珠宝、美妆等领域时,其对材料质感、光泽等极度专业细节的还原能力将面临严峻考验。其三,其长期价值可能不仅在于素材生成效率,更在于沉淀品牌专属的设计资产与迭代数据,这将是其从工具演变为平台的关键。

总体而言,IMAI Studio展现出了难得的产业深度思维。它不是在用AI替代设计师,而是在用AI加速并赋能整个实体产品开发的价值链。其成败将取决于对垂直行业细节的深耕程度,以及能否构建起以视觉资产为核心的协作生态。

查看原始信息
IMAI Studio
IMAI transforms a single product photo into precise variations, real studio-grade mockups, lifestyle scenes, videos and even 3D/AR assets - all calibrated with a curated library of industry-ready colors, materials and design presets.
Hi everyone - we’re the team behind IMAI Studio. For years, bringing physical products to life has been slow and layered. Multiple rounds of prototyping. Weeks lost in sampling. Materials consumed. Miscommunications in translation. And an industry where decisions increasingly demand speed, clarity, and the ability to iterate fast. AI tools have appeared, but most still fall short - inconsistent quality, unrealistic scenes, strange colors, and results that don’t match what real teams need. We built IMAI to fix that gap. IMAI transforms a single product photo into precise variations, real studio-grade mockups, lifestyle scenes, videos, and even 3D/AR assets - all calibrated with a curated library of industry-ready colors, materials, and design presets. Instead of replacing teams, IMAI gives them the ability to explore more ideas, iterate faster, and make decisions without burning time, materials, or budgets. Redesign a shoe in minutes. Test six colorways. Drop a bag into an editorial scene. Generate marketing assets instantly. Or validate concepts long before any physical prototype is made. Today, teams inside H&M, MK, Kitex, Brandix, and Tata are already using IMAI to work more intelligently and move with greater agility. If you design, build, or market fashion and lifestyle products, IMAI will help you save time, reduce risk, and unlock far more iterations - with results that feel genuinely usable from day one. We’d love for you to try it, explore, and tell us what you think.
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@viola_schritter This is a game changer, it will make product iterations faster, save more time and money. it will make users have an idea of how their products will look like before mass production.

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@viola_schritter looks super promising. I have tried it!

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Great launch, IMAI Studio team. From a clarity & onboarding perspective, when a creator opens IMAI Studio for the first time, what’s the one belief you want them to leave with in the first 10–15 seconds?
Is it:
• “I can turn my idea into a visual prototype in minutes.”
or
• “Design isn’t the barrier anymore—I’m in creative control.”
Because in ideation-to-prototype tools, the adoption lever isn’t just features—it’s the user believing they can visualize their idea. Curious how you’re shaping that belief.

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@joydeep_pandey 

Love this question Joydeep - you’ve basically described the exact debate we’ve been having internally. 🙌

Our belief is a blend of those two lines, but if we had to choose, it’s closer to:

“Design isn’t the barrier anymore - I’m in creative control.”

And we try to prove that in the first 10–15 seconds by making one thing obvious:

“Drop a product → click a preset → see 4 new ideas in minutes.”

A few ways we’re shaping that belief right now:

  • Zero-jargon first screen: You see a single path: upload a product photo or use a demo, pick a scene or style, hit Generate. No wall of controls.

  • Opinionated presets instead of tools: “designs references", "pattern references", "aesthetics" and curated color palettes.

  • Instant win moment: The first grid of variations is designed to feel like, “Oh, I can actually play with this” - change colors, swap scenes, try wild ideas without breaking anything.

Our bet is: once a creator feels that control in the first interaction, “I can turn my idea into a visual prototype in minutes” becomes an obvious side-effect.

Really appreciate you framing this around belief vs features - if you’re up for it, we’d love to keep sharing iterations of the onboarding with you as we refine it. 🚀

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It feels like an absolute cost saver for e-commerce products. Great job
Any other category are you targetting?

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Hi @chilarai , thank you for your feedback. Currently we are targeting apparels, shoes & bags mainly.

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@chilarai the same pipeline works really well for any visually-driven e-commerce brand, so we’re already seeing interest from beauty, jewellery and D2C lifestyle teams too

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I honestly didn't know H&M and Tata use IMAI! That's a really positive product validation!

I am sure you must have identified innumerable use cases for IMAI Studio in retail/e-commerce space, @viola_schritter

What has been you experience with Asian retail space w.r.t the usage of this tool? I mean, were you able to penetrate into the global markets so far?

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@ashok_nayak 

Hi Ashok, thanks for your message. Appreciate your comment.

Teams at H&M, Tata International, Pantaloons and Brandix are using IMAI in their design and studio workflows. It has been the most validating part of this journey. 🚀

In Asia specifically, adoption has been stronger because the pain is so acute:

  • huge SKU counts,

  • tight timelines,

  • and the need to create localized visuals for marketplaces, retail, and social - without doing a new shoot every time.

It is not just for the brands but we finding use cases where the manufacturers for these brands (the ones who make the sample collections for them) and even bigger on adopting the platform.

Most teams start with simple things: turning 1-2 base photos into full e-commerce catalogs, quick colorways for internal decisions, or testing campaign visuals for different regions. Once they see that works, they move into more advanced use cases like concept mockups, seasonal drops, and even 3D/AR experiments.

On the global side, we started in Asia by design, but we’re already have started working with teams that operate across North America as well. It’s still early for us, but the pattern is clear: wherever brands are fighting the “design and content bottleneck” between product and marketing, IMAI fits right in. 🌍

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Great work, I tested out IMAI for a while, and I think there's lots of potential use cases (product ideation, product design, marketing). What are the major next features on the roadmap @viola_schritter ?

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@lcseidl Hi Leander,

Thanks so much for testing IMAI. On the roadmap, we’re focusing on:

  1. Simpler video generation - users can upload a product and get full scripts or ads with one click, no starting image needed.

  2. Collaborative features - so teams can work together seamlessly.

  3. Branding UX - users can apply brand guidelines across the workspace automatically.

Excited to see what you think!

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Congrats on the launch! Many businesses need this product 👏🏼
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@alyona_mysko thanks for your kind words
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@alyona_mysko thank you Alyona!!

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Congrats on the launch. Quick question, is IMAI being used more for early concept validation, or more for instantly generating final marketing assets at scale?

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@lusine_mnatsakanyan4 

Thanks Lusine! Today usage skews slightly toward final marketing assets.

The best workflow we see is validating a concept and then using that same reference to spin up full campaigns. Because everything updates live for everyone in the project, design tweaks and marketing experiments stay in sync with the whole team, which makes iterating on both sides much faster.

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https://www.youtube.com/watch?v=1Jb8OwDJOIU

Hi everyone, here’s a quick walkthrough of IMAI in action - how we go from a single product photo to multiple design ideas, studio shots, and ad-ready visuals in minutes. Would love your thoughts on what feels most useful (and what we should add next). 🚀

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@viola_schritter This is too good! A decade ago nobody would have even imagined something like this!
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Planning the composition and visualizing the final result usually takes so much effort. This seems like it would be really helpful for that part of the process.

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@new_user___3352025aaad15cafb976078 thanks for your feedback. Sincerely appreciated. Any feedback you have?
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Congratulations on the launch! After trying IMAI Studio, I'm convinced this is the future of product creation.

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@shivamhacks thanks so much Shivam. I’m thrilled to hear that.

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Huge congrats on the launch! IMAI Studio is a game changer. The future of product visuals is here.

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@anna_nevmerzhytska thank you for your kind words Anna!

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#20
Antigravity
The world's first 8K 360° drone
113
一句话介绍:Antigravity A1是全球首款8K 360°无人机,通过双镜头隐形技术和“先飞行后构图”的操控逻辑,在航拍和内容创作场景下,解决了传统无人机需要高超飞行技巧与实时构图能力的核心痛点。
Drones Hardware Photo & Video
消费级无人机 8K 360度相机 第一人称视角 免后期隐形 手势操控 沉浸式飞行 超轻量化 航拍革新 Insta360孵化 后置构图
用户评论摘要:用户普遍惊叹其低于250g的超轻设计和隐形技术,认为它打破了航拍与FPV的界限,带来了纯粹的飞行乐趣。主要问题与建议集中在:对隐形技术的隐私担忧、对后期多角度预览工作流的询问,以及对未来加入AI辅助构图和降低价格(目前价格未披露但被用户认为较高)的期待。
AI 锐评

Antigravity A1的宣称,与其说是一次参数跃进,不如说是一场对无人机产品逻辑的“降维打击”。它巧妙地用360°相机的技术路径,绕开了传统航拍无人机在云台机械结构、飞行稳定性与实时操控上的复杂博弈。其核心价值并非“8K”,而是“隐形”与“后置”。

“隐形无人机”概念通过双镜头视差缝合实现,这本质上是将复杂的物理避障和构图难题,转化为一个已相对成熟的360°影像算法问题。这使其在合规性(<250g)和易用性上占得先机,但真正的颠覆在于“后置构图”。它将飞行与创作这两个高压力环节解耦:飞行回归直觉与体验(如鸟般飞翔),创作则沉淀于地面端的冷静选择。这精准切中了非专业用户的最大痛点——不是不会飞,而是飞的时候根本顾不上、也不懂如何构图。

然而,其光鲜背后暗藏隐忧。首先,产品逻辑高度依赖于母品牌Insta360在360°影像缝合与软件生态上的积累,其独特体验能否形成壁垒存疑。其次,“后置构图”意味着海量数据(8K 360°)的处理压力与存储成本完全转嫁给用户,对移动端硬件和软件流畅度提出严峻考验。最后,其定位游走在专业与消费之间:极客与创作者青睐其灵活性,但普通消费者可能被其工作流和潜在的高昂售价劝退。它开启了一个新品类,但能否从惊艳的玩具成长为普及的工具,取决于其能否在价格、工作流效率与核心画质间找到更优的平衡点。

查看原始信息
Antigravity
Antigravity A1 is the world’s first 8K 360° drone. With its dual-lens design, the drone becomes invisible in your footage. Put on the Vision Goggles, use the motion controller to point-and-fly, and reframe any angle after you land. No pilot skills needed.

Hi everyone!

For a long time, the drone market has felt a bit stagnant. We’ve been choosing between "flying tripods" that require careful framing or FPV drones that require months of practice. Antigravity A1 breaks that dichotomy.

Incubated by @Insta 360 , this is essentially an 8K 360° camera that flies.

The Invisible Drone tech is magic. Because of the lens placement, the drone stitches itself out of the footage completely, leaving a pure, unobstructed view of the sky.

You can fly first, then frame later. You don't need to stress about composition mid-flight. Just put on the Vision Goggles, use the motion controller to point where you want to go (literally just waving your hand), and enjoy the view. Just pick the perfect angle—forward, backward, or top-down after you land.

It brings the wonder back to flying. It’s less about being a cameraman in the sky and more about being a bird. Plus, at 249g, it’s regulation-friendly in many regions.

Yes, we finally get a drone that feels like play, not work :)

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@zaczuo 249g??? That's like some spy drone. :D I would be so suspicious if something like this were to circle around me. But maybe I wouldn't notice :D

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@zaczuo Being able to reframe after the flight seems incredibly useful.
Does the app let you preview multiple angles quickly, or is it more of a manual workflow?

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Amazing! How on earth you got this below 250g I will never know - kudos to the design and manufacturing teams. I'll be ordering one shortly 👍🏻

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Could future updates add AI‑assisted framing suggestions to make editing even smoother?

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Almost thought this would be a launch of Google's coding agent Antigravity 😅 But damn I realy want an FPV drone and feel like I'm flying myself through my neighbourhood but pricing is unfortunately too big for my budget. I hope that these type of drones could go down to like $300 and I would be so hyped. But still, this drone looks sick, also with the 8k 360 video ability

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