PH热榜 | 2026-03-15

Bringing Dynamic Island to Mac fills a genuine UX gap — macOS notifications have felt stale for years while iPhone's Dynamic Island became genuinely useful. The multi-app notification support across iMessage, WhatsApp, Telegram, and Slack with inline replies means this could replace the need to constantly check separate apps. How does it handle notification priority when multiple chats fire at once — is there a smart queue or does it stack them?

I’ve had a notched MacBook for a while and never thought about that black bar — until DynamicLake. Now I check my calendar, control music, and see notifications without leaving what I’m doing. The design is clean and doesn’t feel like a third‑party hack. For me it’s one of those “why didn’t this exist before?” tools. If you use a notched Mac every day, it’s worth trying.

Love this. The best products often feel obvious after you see them and bringing a native-feeling Dynamic Island experience to Mac is exactly that kind of idea.

Great tool! Love the Dynamic Island experience on Mac.

As someone who lives in multiple apps all day, I really like the idea of pulling notifications and quick actions into one interactive layer instead of bouncing between windows. The drag-and-drop interactions look especially useful. Curious how you decided which integrations to prioritize first (Slack, WhatsApp, etc.) and whether more app integrations are on the roadmap?

Great idea! Dynamic Island on Mac feels very natural.

How's the performance impact on older MacBooks?

Looks great, congrats on the launch!

Congrats on the launch! I always appreciate it when non-AI products show up these days. 🎉

I just bought the app... but it crashed on every open unfortunately.

"Clean design, love the simplicity. How long did it take to build?"

Love the focus on improving notifications here. Multi-line replies and quick reactions sound really handy to me as well. Maybe filters or smart grouping for notifications could be a nice addition too.

Congrats on the launch

Congrats, looks very clean. Does it work on a monitor?

Porting Dynamic Island to macOS fills a long-standing UX gap. Notification handling on macOS has lagged behind for years, while Dynamic Island on iPhone demonstrated how contextual, interactive notifications can improve workflows. With multi-app support across iMessage, WhatsApp, Telegram, and Slack — plus inline replies — it could significantly reduce context switching. How does the system manage notification priority when multiple chats arrive simultaneously? Is there a smart queuing mechanism or simple stacking?

Is there any way to try your app before I buy it?

Also, what kind of user permissions does this need in order to run properly?

is there a video demo?

Google Workspace CLI is a command-line tool that lets humans and AI agents control the entire Google Workspace... Drive, Gmail, Calendar, Sheets, Docs, Chat, Admin and more, from one CLI.

The problem: When AI agents connect to Workspace using MCP servers, tool definitions often get loaded into the agent’s context window. Some setups consume 37k–98k tokens before the agent even starts reasoning, which can eat a huge chunk of the context.

The solution: This avoids that “context tax.” Agents read a lightweight skill file, execute a CLI command (like `gws drive files list`), and receive clean structured JSON, without loading massive tool definitions into the context.

What makes it different:

• Commands built dynamically from Google’s Discovery Service, so it stays current automatically

• 100+ agent skills for Workspace workflows

• Works with human CLI usage and AI agents

• Supports CI/headless environments and encrypted credentials

• Can even run as MCP over stdio if you want MCP transport

Key features:

• One CLI for the entire Workspace API surface

• Structured JSON output

• Helper workflows (email, meetings, standups, file sharing, etc.)

• Runtime discovery of new Workspace APIs

Who it’s for: Developers building AI agents in Claude Code, Cursor, and agentic workflows, or anyone who wants a faster way to automate Google Workspace without writing REST calls.

If you're building agents that touch Workspace, this is definitely worth checking out.

I hunt the latest and greatest launches in tech, SaaS and AI, follow to be notified → @rohanrecommends

Finally a single CLI that actually covers the whole Workspace stack — Drive, Gmail, Calendar, Sheets, Docs, Chat — instead of stitching together curl and REST docs. I use it for quick scripts (list recent Drive files, send a mail, check today’s agenda) and the --dry-run + --help on every command make it safe to experiment. The fact that it’s built from Google’s Discovery API means new endpoints show up without waiting for a release. For automation and AI agents, the structured JSON output and the bundled skills are a big step up from hand-rolled API calls. Auth was straightforward (including service account and token export for CI). Not officially from Google, but it’s become my default way to touch Workspace from the terminal.

The GitHub README states it's not a Google product, yet it's published by a Google developer and uses the Google logo. Do you know why?

Congrats, this is awesome!

The "context tax" problem with MCP tool definitions consuming 37k-98k tokens before the agent even starts working is a real bottleneck that most developers building agentic workflows have hit. Routing through lightweight CLI commands with structured JSON output is an elegant solution that keeps the agent's context window free for actual reasoning. Does the runtime discovery from Google's Discovery Service handle deprecated API changes gracefully, or could an agent break mid-workflow if Google sunsets an endpoint?

I can see the “human & agents” token handling being a neat fit for serverless functions that need to rotate service‑account credentials on the fly. Does the CLI expose a way to batch‑apply ACL changes across Drive, Calendar and Meet in a single command, or is that left to custom scripting? I once built a nightly sync that pulled Drive permissions into a CSV via raw curl – the CLI would have saved me a dozen of those frantic command‑line gymnastics.

Oh the context tax thing is painfully real. I run MCP agents and the tool definitions alone eat like half my context before the agent does anything useful. Going CLI-first with skill files makes way more sense than loading everything into context.

Hello something like that, but for GMP tools

- Google Analytics 4
- Google Tag Manager
- Google Search Console
- Google Ads

Can u see more at: https://www.npmjs.com/package/@lucianfialho/gmp-cli

Dealing with the raw Google Workspace API is always a massive pain when I just want to script some basic admin tasks. A dedicated CLI that agents can tap into is a brilliant way to handle headless account provisioning for new hires. I would love to know if you are managing the OAuth token refresh lifecycle entirely under the hood.

Hey Product Hunt! 👋 I'm J.D., founder of ClawSecure.

Your AI agents are running third-party skills with full system access, no verification, no permissions, no oversight. 41% of top OpenClaw skills are dangerous. 1 in 5 are quietly sending your data to attackers. 22.9% changed their code after install.

After a decade building and securing AI and Web3 platforms at scale (2x exited founder, JP Morgan, Galaxy Digital, Bloomberg, NYSE), I've watched billions disappear when ecosystems scale faster than their security. It's happening again.

We built what the ecosystem was missing. ClawSecure is the most comprehensive security platform for OpenClaw agents: 3-Layer Audit, real-time monitoring, marketplace and identity security clearance, and 10/10 OWASP ASI. Free. No signup. 30 seconds.

We're excited to bring this to the PH community 🚀

Ask us anything, challenge us, or share what security concerns you are having with agents — we'll be here all day to chat!

Does this only work with OpenClaw or can it extend to other agent frameworks?

This is honestly scary. 41% dangerous skills? Makes me wonder how many agents are already leaking data without builders realizing it.

Are there plans for alerts via Slack or Discord when Watchtower detects suspicious behavior?

Grats on launching.
Is it possible to have false positives? How do you differentiate risky patterns from legitimate agent automation??

Great concept @jdsalbego. Any plans to open-source parts of the scanning engine?

The stat that 22.9% of skills changed their code post-install is alarming and makes Watchtower's hash drift detection genuinely critical infrastructure, not just a nice-to-have. Focusing on securing the source before execution rather than runtime monitoring makes sense given OpenClaw's lack of sandboxing. Is there a plan for a community-driven threat intelligence feed where security findings from one audit automatically protect the broader ecosystem?

If I had to rewrite your launch post tagline, I would write, “antivirus for OpenClaw AI agents". Congrats on shipping.

Congrats @jdsalbego @fiatretired

Are you mapping agent behavior dynamically or just scanning the skill code?

Congrats on the launch!

"This solves a real pain point. What's your tech stack?"

Claws have been naked for a while... the security issues are critical! Hope Clawsecure could be a cure.

This is addressing a massive blind spot in the AI agent ecosystem. The stat about 22.9% of skills changing their code after install is genuinely alarming. Love that you focused on securing the source rather than trying to patch things at runtime. What happens when a skill that was previously marked as "Secure" gets flagged by Watchtower after an update?

Congratulations on the success of your product. But are there any guides for newcomers? I don't know much about technology but I'd still like to learn more about OpenClaw. I hope to see the next steps in the product's development.

Really cool idea. Could be interesting to see CI/CD or GitHub integrations so skills get scanned automatically before deployment.

Congrats on the launch!

Been running some OpenClaw agents for a side project - the "secure by default" claim caught my eye since mine keep trying to access things they shouldn't. Does this actually sandbox the agents at runtime or is it more of a monitoring/post-mortem setup? The pricing page mentions per-agent fees which gets pricey fast when you're experimenting.

Congrats on the launch, @jdsalbego! The real-time Watchtower monitoring is cool. I like how it keeps checking skills all the time. Makes me feel safer using OpenClaw agents.

Congrats on the launch!

Great work, congrats!

Security for agent ecosystems is massively under-discussed. Appreciate this product, very refreshing :))

Security is rarely glamorous but always necessary. This might become essential infrastructure if agent marketplaces keep growing. Smart category to build early. Congratulations!!

This reminds me of early Web3 security tooling. Ecosystems move fast, security tooling always lags behind. Congrats on the launch, J.D.

Congrats on the launch! The vertical play on OpenClaw is counterintuitive but smart if adoption curves hold enterprises hate switching security vendors once integrated. So does your "complete" coverage extend to post deployment agent behavior mentoring or only pre prod. vulnerabilities?

following

ElevenCreative by @ElevenLabs looks like a powerful step toward an all-in-one AI creative stack. It’s a platform to generate, edit, and localize premium audio and video content in minutes.

The problem many creators and teams face today is that producing high-quality media requires multiple tools, complex workflows, and high production costs. ElevenCreative solves this by bringing voice, video, music, sound effects, images, and localization into a single workspace.

What makes it interesting is the end-to-end workflow: create assets using ElevenLabs’ models, refine everything in the browser-based Studio, and localize content into 70+ languages for global reach. It also offers 10,000+ AI voices, voice cloning, video generation, music and SFX creation, templates, and automation.

The benefits are clear: faster production, lower costs, and the ability to scale content across formats and markets. It seems especially useful for creators, marketing teams, and media companies working on ads, voiceovers, localization, social media content, or storytelling.

If you’re building content with AI, this looks like a platform worth exploring.

I hunt the latest and greatest launches in tech, SaaS and AI, follow to be notified → @rohanrecommends

Consolidating voice, video, music, SFX, and localization into one platform eliminates the duct-tape workflow most content teams live with — exporting from one tool, importing to another, losing quality at every step. The 70+ language localization is where the real ROI scales, since creating content once and distributing globally was previously a full production team's job. How does the voice cloning handle brand consistency when localizing a spokesperson's voice across different languages?

Congrats on the launch!

Consolidating all of this into one workspace is the obvious win, but I'm curious how collaboration works when multiple people are editing the same project? Does it support real-time co-editing or is it more of a handoff workflow?

"Interesting approach! What's on your roadmap for the next few months?"

I was specifically curious about how the voice cloning handles brand consistency across languages. Testing a brand voice in French and Japanese, the emotional cadence of the original speaker carried over far better than any other tool I’ve tried. For marketing teams, this alone justifies the platform - you get global reach without sounding like a robotic translation.

The pivot from standalone voice tools to a full creative suite is smart. The hardest part of content creation has always been the blank page — once AI can handle the initial draft across audio, video and text in one place, creators can spend their energy on taste and refinement rather than production. Congrats on the launch!

Congrats on the launch! You folks empower us, which is great.

Looking forward to checking out the new product. At the same time, never stop developing new models — competitors aren’t sleeping. I realized that after not using it for a couple of months and trying it again recently.

what can i say, i got lobster-hooked 🦞🪝

its fun but also feels really natural to coordinate meetings by chat.

for the past 3 weeks i have been toying with my own openclaw agent interacting with our API v2 and today we're super excited to release a whole catalog of useful skills, tools, APIs, CLIs and more.

for those who don't wanna set up OpenClaw (fair), get the beauty of natural language agents into your Slack channel or text via Telegram.

we have a whole list of use cases https://cal.com/agents#use-cases explaining what you can do with our Cal.com Agent so get creative!

at this point im really just vibing, the agentic space is fun to tinker with. not sure if this is gonna be a $100B product but be my guest and play around with it.

we are announcing a hackathon in the next few days as well so make sure to join the waitlist! go.cal.com/hackathon

been using Cal.com for a while…
really cool direction for the product.
ai powered scheduling for humans and agents is a very interesting step.

Congrats Peer! Very cool.

There’s a big number of meetings being scheduled via text/chat. This is the way

Congrats on the launch!

Adding AI agents to Cal.com's scheduling infrastructure is the natural evolution — most scheduling friction comes from the back-and-forth negotiation that an agent can handle autonomously. Being open-source gives Cal.com a trust advantage over closed competitors when it comes to letting an AI agent manage your calendar. How do the agents handle scheduling conflicts where both parties have tight windows — do they negotiate alternative times proactively or just surface the conflict?

Congrats on the launch!

Finally. Do the agents handle timezone hell properly though? Like Google Calendar + Outlook, people in 3 different timezones — that's always where scheduling stuff breaks down.

AI agents handling scheduling is one of those obvious-in-retrospect ideas. The friction of back-and-forth booking is real and unsolved for most small businesses. Excited to see how Cal pushes this beyond simple booking into proactive outreach and follow-ups. Congrats on the launch 🚀

Way to go Peer! This makes me very excited to see from you guys; and great timing to build something as valuable as Cal.com, because every single AI writing code is going to pick you all.

The open-source angle matters more than people realize for calendar agents. When you give an AI write access to your schedule, being able to audit exactly what it does is a real trust unlock. For founders juggling multiple investor meetings per week, the text-based booking removes genuine friction — the back-and-forth that kills deal momentum is one of those invisible time sinks nobody talks about. How are you handling timezone negotiation when both parties are in different regions?

This is exactly the kind of tool that changes how you think about time. Not just scheduling meetings — actually protecting the hours that matter most. Congrats on the launch! 🎉

make time programmable 👀

Windows has been underserved for polished screen recording tools — most of the best options are Mac-only, so filling this gap with automatic mouse smoothing and zoom-ins is a real differentiator. Adding camera, microphone, and AI-powered captions in one update turns Motion from a recording tool into a full video production workflow. How does the AI caption model handle technical jargon and code-related terminology that's common in demo recordings?

It is so nice to finally see a modern screen recording tool built natively for Windows instead of just macOS. Do you have any plans to add automatic cursor smoothing or auto-zooming for feature highlights? That would make this the absolute perfect tool for recording quick devlogs or build-in-public updates.

Looks pretty handy Pablo, and best of luck with the launch!

Hey Pablo! It's ideal for product demos like some of my portfolio. I'll take it a look cause I feel it's gonna help me a lot, and of course, I'll back with deeper feedback

Nice launch, congrats!

Congrats on the launch!
The design looks amazing!

Yesterday I was recording a video for LiveDemo,
And the two features that I needed which really made the difference between choosing a recording software
Were the already pre-selected background music choices and the custom camera layouts.

Ended with screenstudio, but would have definetely picked something else if it had these features.
Wondering what features are you thinking of adding next?

The auto zoom-ins and mouse smoothing are the kind of details that turn a raw screen recording into something you'd actually put on a landing page. Most recording tools give you the footage but the post-production to make it presentable is a whole separate workflow.

Any plans to add export presets optimized for specific platforms? Something like a one-click "PH gallery" format (1270x760) or "App Store preview" would save a lot of manual resizing for indie devs prepping launches.

The UI in the demo looks incredibly clean. so many Windows capture tools feel clunky or outdated, but this actually looks modern and polished.

Clean, async screen recordings are underrated for team productivity. For remote teams working alongside AI, having a simple way to document workflows visually makes handoffs so much smoother. As agents start building professional portfolios and work histories, video walkthroughs could become a powerful way to demonstrate capabilities — similar to how agents on networks like Moltin.work showcase their work.

Preserving the speaker's actual voice, tone, and emotion during real-time translation is the crucial detail that separates this from robotic translation — a call where you hear a synthetic voice immediately feels impersonal no matter how accurate the words are. The pay-per-minute model with no subscription is perfect for travelers who need it sporadically. How noticeable is the latency during a live conversation when translating between structurally different language pairs like English and Japanese?

When the website greets you in your mother tongue, it is a totally different and convenient experience. Nice idea, Sam! :)

Breaking real language barriers in communication is becoming essential for both people and AI agents. As autonomous agents start working across countries for global clients and interacting within multi-agent systems, smooth multilingual communication shifts from a bonus feature to a core requirement. I’m curious whether you’re also considering scenarios where agents need to communicate directly with other agents.

What happens when the translation doesn't quite land mid-conversation? Is there any way for the listener to signal confusion without breaking the flow of the call?

This is really cool! Do you envision this being used more so for personal or professional use cases?

could you tell me some use case beyond translations?

Congrats on the launch! The "preserve your voice" angle is what sets this apart — most translation tools strip all personality out. Excited to see where you take this. Good luck! 🍌

The detail that stood out to me is preserving the actual voice, tone, and emotion during translation.

Quick question for the makers: How does it handle the natural flow of conversation, like interruptions or talking over each other? That’s where most real-time translation apps fall apart. Really curious.

Communication that truly bridges language barriers is something humans and agents alike need. As autonomous agents increasingly work across borders for global clients and collaborate in multi-agent systems, seamless multilingual communication becomes a real requirement — not just a nice-to-have. Curious if you're thinking about agent-to-agent communication use cases too!

The pay per minute model is really smart, way better than yet another subscription for something you might only use when traveling. Preserving the actual voice tone is what makes this feel like a real conversation instead of talking through a robot. Curious, does it work well in noisy environments like airports or crowded streets?

Looks Promising and a cool idea, what are some of use cases that you saw in beta version, that was unexpected ? Also did the team explore the possibility having a micro LLM model installed along with the app for offline usage ?

Hey Product Hunt! 👋

Andy here, founder of ByteRover.

Over the last few months, we’ve watched developers try to scale autonomous agents (like OpenClaw and local Ollama setups) and hit a massive brick wall: Agent Amnesia.

An agent solves a bug or writes a script, and then immediately forgets the context. To fix this, teams are dumping entire codebases into giant vector databases or blindly prepending massive context windows, resulting in insane API token bills and VRAM crashes.

We got tired of these manual workarounds. So we built Memory Skill for OpenClaw.

It is a deterministic, file-based memory system (.brv/context-tree) that lives directly in your local environment.

How it works:
🧠 Selective Retrieval: Instead of blindly injecting everything, ByteRover actively curates decisions and feeds the agent exactly what it needs to know.
📉 Cuts Token Burn: Our users are seeing token usage drop by ~40-70% because the prompts stay noise-free.
📂 Local & Portable: Your memory is version-controlled via Git, preventing silent context drift. What Git did for code, we are doing for AI context.

We’ve seen 26k+ downloads from OpenClaw power users in the last week, hitting a 92.19% retrieval accuracy on the LoCoMo benchmark.

I would love the community’s feedback on our architecture. Drop any questions below I’ll be here all day answering them! 👇

I have been using Byterover for a while with Claude Code for memory management with my team at Studio1. And that was a great experience. Having used OpenClaw for last month, I can definitely say the experience wasn't that good. And I am so excited to try out ByteRover with OpenClaw. huge congrats to the team

70% token savings is the real headline here. The MEMORY.md approach works until you hit ~50k tokens of context and your agent starts hallucinating its own history. Context-tree architecture is the right abstraction - hierarchical retrieval instead of dumping everything into the prompt. 26k users in a week tells you people were desperate for this.

Agent amnesia is the most underrated bottleneck in agentic workflows — an agent that forgets what it just debugged three turns ago is essentially starting from scratch every time. The 40-70% token reduction from selective retrieval instead of blindly injecting everything is a massive cost saving at scale. How does the deterministic file-based approach handle conflicting memories when two team members' agents produce different context about the same codebase section?

100% agree the default memory setup can get noisy fast. The win is separating short-term daily logs from curated long-term memory + good retrieval. Less token burn, better continuity, fewer hallucinated “memories”.

Goodl luck today! Question: How does ByteRover achieve 92%+ retrieval accuracy with file-based memory. Are you using embedding indexes with semantic ranking, or a hybrid approach combining structured metadata and vector search?

Congrats, love this!

The idea of a free, local version with no friction (no accounts required) really motivates me to try our the CLI.

Seeing >92% retrieval accuracy on pure file‑based memory is impressive - especially given the usual latency vs. persistence trade‑off. I’m curious how you keep the index in sync when source files are edited in place; do you rely on a change‑detection layer or periodic re‑embedding?

I've been using ByteRover for a while and really love the ease of set up, work smoothly from my IDE. Can't wait to get my hand on the OpenClaw version.

Finally, a cure for agent amnesia

"Interesting approach with local file-based memory. How does this compare to cloud-based memory layers for non-developer users?"

What does this do

Congrats on the launch! I've been using this for the last month to solve what I call "cognitive debt." I was losing about 15 minutes every morning just re-explaining my architecture and past decisions to my coding agents. Vector similarity wasn't cutting it—it would hallucinate or pull the wrong files. Moving to a curated Context Tree (domain→topic→subtopic) completely fixed the amnesia. The fact that the memory is just markdown files makes it so easy to version control and review. It’s like my agent actually "remembers" where we left off.

Nice, we could add some bookmarks tab too?

How did you get that idea to sell the art with this tool?

This only works if it becomes a daily habit, which is the hardest UX problem to solve. Is there anything in the app that helps build that routine, or is it left entirely up to the user?

my macbook isnt accepting it says security risk?

Definitely thought this was a rebrand of @Morgen ...

Nice work, congrats!

Replacing the 12-tab morning ritual with a single local-first dashboard is solving a problem most people don't even realize costs them 50 minutes because the friction is distributed across so many small actions. The MIT license and zero-cloud approach means you can trust it won't become another subscription service down the road. Is the dashboard customizable per day of the week — for instance, showing different widgets on workdays versus weekends?

Alright, so I just tried out the app, and one thing I would definitely say that I like about it is that streaks are optional instead of being forced to commit to a reading goal.

I also like that the app notifies you with an article pick and to finish an article.

This is a really cool app!

Congrats on your launch!

Running AI summaries and daily digests entirely on-device with zero cloud dependency is the privacy gold standard that most "private" apps claim but don't deliver. The quiz cards generated from saved articles are a clever retention mechanic that actually reinforces what you read. How large is the on-device model, and does it noticeably impact battery life during longer digest generation sessions on older iPhones?

Hi Product Hunt! 👋 I’m Divya, and we built Aura Water because we were tired of health apps treating our biology like a commodity.

Most trackers harvest your data and sell it to third parties. We took a different path with our 'Sovereign Health' framework: 100% Offline AI: Your hydration coach lives on your phone, not a server. Zero Friction: No accounts, no cloud sync, and no invasive data collection. ADHD-Friendly: We replaced boring logs with a 'hydration battery' and interactive avatars to make habits stick.

We believe health tech shouldn't be a surveillance business. Check out our deep dive on Kidney Sovereignty here: Article.

I’ll be here all day to answer questions. How do you stay hydrated?

The hydration battery concept is such a clever way to gamify something as simple as drinking water. And the fact that it adapts to activity levels and weather without sending anything to the cloud is impressive. I always forget to drink during long work sessions so the ADHD friendly design resonates. Is there Apple Watch support for quick logging without pulling out the phone?

Really interesting idea, especially the privacy first hydration tracking.

One small observation from the launch visuals. The screenshots feel a bit similar and don’t fully tell the product story yet. On App Store, stronger visual storytelling could help highlight features like the AI hydration insights and privacy angle much better.

Improving this could also help users understand the value faster, which can lead to higher app downloads and better engagement metrics.

Curious to see how the product evolves.

One of my favorite things about Aura is the ADHD-friendly design. ⚡ We purposely made it lightning-fast to log your water so you can stay healthy without the app feeling like a distraction. Would love to hear from other productivity fans—how do you manage your hydration during deep work sessions?

That’s useful — congrats!

Could you clarify one thing: are you using AI for some kind of personalized methodology, or mainly for message generation?

That's very cool. I recently saw smart bottles that track your hyderation and remind you to drink at set intervals. Any plans to extend to hardware like that?

Congrats on the launch!

Making a water tracker fully offline and private is a refreshingly honest approach — most health apps collect way more data than they need for their core function. An AI hydration coach that runs locally without sending your habits to a server shows that privacy and personalization don't have to be mutually exclusive. Does the AI adapt recommendations based on activity level or weather, or is it purely based on manual intake logging?

We built habit tracking into FuelOS and the single biggest drop-off point was the logging step itself. How many taps does it take to log a glass of water from a locked screen? That number matters more than almost anything else for daily retention.

If this helps me drink water as consistently as I check Slack, I’m sold.

Congrats on the launch

Automating furigana annotation for kanji solves one of the biggest friction points for intermediate Japanese learners — constantly looking up readings breaks the reading flow and kills motivation. The vertical-to-horizontal layout conversion combined with side-by-side translation output is particularly useful for academic papers where you need both the original and translated text for citation purposes. Does the audiobook generation handle the pitch accent differences across Japanese dialects?

This is actually pretty handy for digitizing a lot of Japanese paperwork as well. Nicely done!

Congrats. Does it support conversion to Kindle version as well?

Really cool niche product. The automatic furigana annotation alone would save so much time for anyone reading Japanese content above their level. Being able to go from a raw PDF to an audiobook in one step is a killer feature for commuters studying Japanese. Do you plan to expand this to other CJK languages like Chinese or Korean in the future?

The claim that Mooon does OCR, layout analysis and semantic extraction in a single step is intriguing – does the engine run the whole pipeline on‑device or does it fall back to a cloud service for the heavy lifting? I could see it slotting nicely into a CI job that validates Japanese contracts before they hit a legal‑review board.

Love the idea of bringing Japanese document processing to the modern stack. The attention to workflow detail shows. Congrats on shipping! 🎉

Great, this engine handles Japanese files in one step and even adds furigana and audio. Scrolling through, I can see it works for papers and manga. Feels like someone thought of everything. Good luck!

What I like about this is what it doesn't do. No algorithm deciding what's important for me, no personalization rabbit hole, no engagement tricks. Just the story, short, with a link to the source. I've been reading news through Twitter and aggregators for years and honestly forgot what it feels like to just scan headlines and move on with my day. The 400-character constraint is smart too - forces clarity instead of rewording the whole article. This might actually fix my morning doomscroll.

This takes me back to when feeds actually helped you stay informed instead of just doom scrolling. Love the constraint of 400 characters per summary, it forces real clarity. The fact that it links back to the original source instead of trying to replace it shows a lot of respect for journalism. Are you planning to add topic based daily digests or is it purely a feed experience?

Impressive. I love tools that get straight to the point without missing the key details. I read multiple articles every day, and this would save a ton of time while still showing the full story. I especially like how each summary makes it clear why it matters. Congrats on the launch @colooch!

What sources are we able to add? media sites, social media and blogs?

This solves a real pain point. Building RAG pipelines from scratch every time you want an agent to access documents is such a time sink. Having parsing, chunking, and embeddings handled behind a single API is exactly what most developers need. How does it handle version updates when a document changes, does it re index automatically or do you need to trigger it manually?

Congrats on the launch!

Building RAG pipelines from scratch is one of those things that sounds straightforward until you're deep in chunking strategies and embedding models. Abstracting all of that into one API is the right call ,it lets builders focus on what the agent actually does, not on the plumbing. Congrats on the launch, excited to see where this goes! 🚀

Congrats on the launch!

👋 Anushrut here, Founder of Fermeon.

I jump between Claude for coding, ChatGPT for brainstorming, and Gemini for research — and every context switch is a tax on my flow. Re-explaining my project stack, my goals, my constraints… it adds up fast.

Fermeon started as a frustration fix and became something much bigger — a portable layer of you that travels with your work across every AI.

To answer the three questions from a builder's lens:

• Most friction? Switching into AI coding tools like Cursor or v0 mid-project. Rebuilding context there is especially painful.

• Automatic vs manual? Manual with a single shortcut feels right — you stay in control without the cognitive overhead.

• Next tool? Cursor and Notion AI would unlock a massive chunk of the dev audience.

Really proud of what we've shipped here. If you're an AI power user who's tired of your tools having amnesia, give Fermeon a try. 🚀

Well Honestly , This has to be the most coolest and most useful thing any AI user needs at this point of time , we have super powerful models to work with but when it comes to context switching they are the worst , it increases the product time so much , just for reexplaining the context from one tab to another or from one tool to another

Congrats on the launch, super useful and comes in clutch during peak prompting :)

Calibrated tone for observational commentary without interrogative elements

The real insight here isn't the extension - it's that context has become the most valuable thing in AI workflows and no platform wants to let you take it with you. Everyone's building walled gardens around your conversation history. A portable memory layer that you own is the kind of infrastructure play that gets more valuable the more AI tools people use, not less.

Congrats on the launch!

Comparison:
Recordly is the only free, open-source screen recorder in this niche that has smooth cursor movement, or zoom animations that are faithful to Screen Studio's. Alternatives are mostly paid and offer choppy zoom animations and/or no smooth cursor movement, and/or lack other features.

Try it now: recordly.dev
Star on Github: https://github.com/webadderall/Recordly

Feature list:
• Add zooms automatically (based on mouse activity) or manually, anywhere on the screen.
• Cursor animations (smooth path, motion blur effect, as well as click animations and cursor size, all customisable)
• Annotate with text, images or arrows
• Record from menu bar HUD - capture app windows or full screen
• Add prebuilt backgrounds to your recordings or upload custom ones
• Timeline-based editor - drag tracks to change video speed, trim, add annotations or add zooms
• Save your projects as .recordly files and come back to them later
• Record system audio or from audio source
• Export as MP4 or GIF with adjustable resolution and aspect ratio
• Runs on all platforms (macOS, Windows & Linux)
• (coming very soon) Webcam overlay bubble

Disclaimer: Recordly substantially modifies OpenScreen to add native capture pipelines for macOS and Windows, a cursor animation system, zoom animations like Screen Studio, and more major tweaks.

I'll be happy to answer any questions!

Love that this is open source. The auto-zoom on cursor movement is one of those features that looks simple but makes a huge difference in demo videos. Are you planning to add any audio/voiceover sync features, or is the focus purely on the visual recording side? I make a lot of product demo content and clean video tooling like this is hard to find.

👋 Hey Product Hunt – Joey here, co-founder of Klipy.

Companies spend thousands on ads, outbound, and lead gen to fill their pipeline. But what happens once those leads actually show up? Conversations scatter across email, LinkedIn DMs, WhatsApp, and Zoom. Follow-ups slip. Context gets lost. Deals go cold — not because the prospect wasn't interested, but because nobody followed through.

You're spending money to find leads, then leaving money on the table with the ones you already have.

That's the blind spot. And it's everywhere.

Klipy fixes it.

Klipy captures every sales conversation — across every channel — and then does the work that comes after. Automatically.

- Every conversation captured. No manual logging, no tab-switching.
- Full context on any contact in seconds — every touchpoint, every channel, one view.
- Follow-ups drafted and queued before deals slip. You review, approve, send. Always human-in-the-loop.
- Ask Klipy anything about your pipeline — like talking to a teammate who's been on every call you've ever had.
- Real visibility for managers — what's actually happening, not what got logged.

We're already used by 2,000+ sellers across 56 countries, processing over 2 million emails a month. Here's what one of our users said:

"Having my 'PA' as a platform is making me save approx 1-1.5hrs per day + saving the expense of a virtual assistant. Looking forward to what's coming next”

Most sales tools optimise for top-of-funnel volume — more leads, more emails. Klipy optimises for deal momentum. Keeping every opportunity moving once the conversation starts.

We built this for B2B sellers and founders who are tired of watching deals die in the silence between conversations.

Free to start. No credit card. Set up in under 4 minutes.

👉 https://klipy.ai/directories/pro...

Would love your feedback — especially if you've ever lost a deal you should have closed.

– Joey, Jung, Tina

Congrats on the launch, @joeywslee! I just went through the landing page. You are solving the leaky bucket problem, but your Scenario 2 (The Unibox) is your biggest weapon.

Klipy pulls in WhatsApp and Telegram. In many markets, deals live and die in the DMs, not just email. By framing it as a Sales OS, you might actually be underselling how much mental clarity a founder gets when they don't have to hunt through three different chat apps to remember what a lead said.

You’ve built a second brain for revenue. This is amazing.

I’ve been using Klipy as my main CRM in my day‑to‑day sales role for over a year, and it’s become the only place I trust for my pipeline. It automatically logs my emails, client interactions and meetings, keeps deals updated without me touching the CRM, and the AI follow‑up suggestions are actually useful, not gimmicks. I spend less time on admin and more time talking to customers, which is all a sales rep really wants – huge congrats to the team on building something truly helpful. 🙌

The "blind spots" framing is spot on ,most CRM problems aren't about the tool, they're about the data that never makes it in because logging feels like admin work. Automating that capture across email, WhatsApp and calls is where the real value is. 3rd launch and still iterating, that says a lot. Congrats and good luck today! 🚀

Lost a deal last quarter exactly like this - prospect went quiet on WhatsApp, I forgot to follow up for five days, done. The multi-channel capture is what stands out here. Most CRMs only care about email, but half my conversations happen in LinkedIn DMs and WhatsApp. Having everything in one view without logging anything manually would've saved that deal. Nice execution.