PH热榜 | 2026-06-08

Hey Product Hunt 👋

I'm Shrey,

Over the last year, we've watched AI agents get remarkably good at using browsers. But we've also noticed something strange: every time an agent visits a website, it starts from zero.

It re-explores the interface, re-discovers buttons, re-learns navigation paths, and re-finds the same workflows it already completed yesterday.

Humans don't work that way.

Once you learn how to search Zillow listings, review a GitHub PR, or book a campsite on Recreation.gov, you don't relearn the entire website every time you come back.

Agents shouldn't have to either.

That's why we built Browse.sh, an open catalog of browser skills that agents can install and reuse across the web. Instead of exploring a website from scratch, agents load the relevant skill and execute against a known workflow.

The result is faster execution, lower token costs, more reliable outcomes, and better multi-site workflows. Today, the catalog includes 250+ skills across real websites and applications, including partner skills like submitting reimbursements on Ramp, creating projects on Lovable, extracting document data on Reducto, and many more.

And when a skill doesn't exist yet, Browse.sh can create one.

Behind the scenes, Browse.sh is powered by Autobrowse, our system that runs tasks in real browsers, analyzes traces, DOM changes, network activity, screenshots, and failures, then continuously improves the workflow until it converges on a durable strategy.

Over time, one successful browser run becomes a reusable skill that anyone can install.

Browse.sh is open source, free to use, and available today.

We'd love your feedback:

- Which websites do your agents struggle with most today?
- What skills should we add next?
- What workflows are you automating with AI agents?

We'll be around all day answering questions. Thanks for checking us out 🤞

Hello hunters! We're so excited to be back and launching browse.sh. I'm Paul, founder of Browserbase. If you have any questions, I'd be happy to help answer them.

Congrats the on the launch! We've been using Browserbase to benchmark https://github.com/pixiebrix/agent-browser-shield and prototyping how to enforce/apply the browse.sh content at the harness layer instead of context layer! Love it!

Looks nicely done, looking forward to try it !

The web was built for humans, and we are happy to launch this skills catalog that finally makes the web a playground for your Claude Code! You're building a web app that needs data that doesn't exist on an API, or you're just looking to automate your weekly lunch planning? Browse.sh is for you!

This looks very interesting, definitely going to try a few of these skills this week.

The "muscle memory" framing resonates — we deal with a similar problem in Telegram moderation where the AI needs to accumulate trust signals from cross-community behavior rather than re-evaluating from scratch each interaction. Curious how you persist agent state across sessions — is the memory layer per-task, per-user, or per-organization? The trade-offs around isolation vs reusability feel close to what we hit when designing cross-group reputation.

Interesting angle. For agent browser automation, the thing I’d want to inspect first is not just success rate, but replayability: logs, screenshots, failed steps, and whether the agent can hand control back cleanly when the page changes.

Congrats on the launch! What are some surprisingly hard websites/workflows for agents to automate today that Browse.sh makes easier?

@shrey150 nice! I have been perplexed as to why the Claude browser plug-in doesn't already have this feature. I have wasted so much time re-reaching Claude the same steps over and over again because of this exact problem. Look forward to trying this out.

This is a great use of memory! How do you deal with information recency?

this is very smart. i worked at Strawberry Browser before and this was a thing i thought about a lot

curious how you handle quality for open skills? like preventing stale, brittle, or low-quality workflows from spreading through the catalog

The "npm for browser skills" framing is exciting and honestly a little scary. With an open catalog and community contributions, when two skills exist for the same site, how does an agent decide which one to trust? And what stops a subtly wrong or even malicious skill from spreading before your weekly revalidation catches it? Feels like skill provenance and reputation become the real product once the catalog gets big.

This makes a lot of sense. Agents relearning the same website flow every time feels like such a waste. Curious how you handle it when a site changes its UI slightly. Does the skill update itself or need manual fixing?

great ship guys! composio loves browserbase

love the domain based installation!

browse skills add amazon.com

recreation.gov skill is a life-saver!!

I like the idea of agents not starting from zero every time. Re learning the same website flow feels like wasted time and tokens. How do you handle skills when a website changes its layout or button names?

@shrey150 The idea that agents should have muscle memory like humans do is so obviously right that it’s wild nobody shipped this sooner. Watching an agent re-explore the same GitHub PR workflow for the tenth time feels like watching someone forget how to use a doorknob... and now there’s finally a fix. Yaay!

The "agents start from zero every time" framing is exactly right. I drive a browser agent every day for marketing routines and the recurring tax is re-finding the same comment box, the same upvote button, the same auth modal. Reusable SKILL.md per domain is the unlock - and an open catalog turns it into a network effect. Following.

fire proposition. played around with browser automation to scrape scholarships off the web; wonder if something like this could help me apply to them automatically asw ...

Memory seems useful when an agent is actively working, but the harder problem feels like deciding what deserves to be remembered in the first place.

Have you found the biggest gains come from long-term memory across sessions, or from reducing context loss within a single workflow?

agents have no muscle memory, and that's a real cost in tokens, in time, in reliability.

the open catalog model is interesting. curious how skill quality is managed as it scales. is there a review layer or does it mostly rely on community signal to surface what actually works?
good luck with the launch!

How much of an issue have you found captchas to be? Are websites trying to restrict agents or are they open to agentic browsing?

"Muscle memory for agents" nails the problem — re-deriving the same web flow on every run is where agent automations get slow and brittle. Congrats on the launch. Does the recorded memory adapt when a site's DOM shifts, or does it need a re-teach?

This makes a lot of sense. Teaching agents the same website every day feels a bit like deleting your browser history before every session 😄 Congrats on the launch!

The interesting part for me is not just reusing browser steps, it is making them reviewable.

For agent workflows I’d want to see how a skill handles the boring cases: site layout changes, failed clicks, partial completion, and logs that explain why the agent chose a path. That is usually where browser agents either become useful or become hard to trust.

The 'muscle memory' framing is apt: it's really a domain-specific replay buffer for web interactions. We've been building AI agents that automate customer workflows and session state management across sites is genuinely hard. How does Browse.sh handle sites that frequently change DOM structure? Does the agent re-learn from scratch or do partial cache invalidation?

Anyone made a ryanair skill yet? I guess we need GPT 6 or 7 before its possible to navigate that website with AI 😬

Hey Product Hunt 👋

I'm Ryan, one of the makers of Honen, and I'm pumped to finally share what we've been building!

Quick backstory: at StudyFetch, we've helped 8 million students understand everything from first-year history to advanced healthcare topics. 

So we took everything we learned and brought it to businesses and the workforce. That's Honen.

The problem we kept seeing: Companies are spending billions on generic training that teaches outdated material and leaves people behind. By the time a course is finished, the skills it teaches are already half-stale.

What Honen actually is: A platform that automates a company's entire learning and training infrastructure,  so businesses can teach new skills faster and adapt their people to an ever-changing world.

How it works:

🟢 Building a course starts in seconds. Drag in your existing training docs, connect to internal knowledge sources, or just type a topic. Honen acts as a researcher and curriculum designer at the same time, it reads your material, understands the subject, and builds the full course structure. You pick how interactive and how deep.

🟢 Ship it instantly. Send the course to any learner with a link, or sync into your existing LMS / HR system.

🟢 Built for engagement, not just completion. Our AI teacher guides learners through visuals, interactive artifacts, podcasts, games, and flashcards,  each personalized to the learner's interests and preferences.

🟢 Hands-on projects, not just videos. Live scenarios where a learner runs a mock virtual client meeting and is graded on how they handle it. Screen-share projects where the AI teacher walks them through setting up and using 3rd party software in real time.

🟢 Admins get a real-time view. You can ask the course agent anything — "my learners are struggling with this topic, what's going on?", and Honen visualizes the answer, then uses what it knows to auto-adjust the content or teaching style.

🟢 One knowledgebase, two kinds of learners. Drag any file into Honen's knowledgebase or write new ones with the Workspace Assistant. Then turn that knowledge into courses for your people and serve it to your AI agents over MCP.  We call it parallel training, a single source of truth that teaches your team and gives the agents working alongside them the same context and skills, so everyone in your org stays in sync.

Launch news: As a first step, we're collaborating with NVIDIA to bring professional AI training to students and professionals, starting with 250,000 high school students nationwide.

Our goal with Honen is to let every business, whether you've got 10 employees or 10,000,  invest in their people in the most efficient and scalable way possible. So learning actually continues across someone's entire career, not just during week-one onboarding.

Free to try at honen.com, no card needed. Your first course takes about 30 seconds.

Hanging in the comments all day,  ask us anything 🙏

This looks amazing, Ryan! And I just learned about StudyFetch as well (I'm a retiree who's now a part-time tutor of high school students, so that one really hit home for me).

Your point about the traditional training courses being outdated at businesses (I also worked at a Fortune 500 company for 25 years) is so true. I imagine your business clients will be even more amenable to AI tools, so this seems like an idea whose time has definitely come! Good luck with your new product; you have my upvote!

Congrats on the launch! When a knowledge base item changes, the course update is gated behind approvals right? But does the MCP feed to the agents wait on that same approval or get the raw change immediately?

hold upppp!!! it's so incredible that it turns source into sections/lessons so that I won't be swamped with unstructured docs & resource. I really like it

what's your take on honen positioning vs notebook LLM?

btw I found some text/title is hard to read. some tweak there and should be good to go.

andddd when will we have dark mode? I'm a night learner and would love it!!!

congrats on the launch! it looks promising

Hey! I'm Josh, COO at StudyFetch. AI is changing the what the workforce needs to know faster than ever, and the ability to learn new skills quickly matters more now than it ever has. We've been using Honen internally and our team members have picked up new skills and expanded their roles, and the whole company runs more efficiently because we can train our own people this fast with our own product. We're excited to get this out to the world so other teams can feel that too. Happy to answer any questions!

The auto-adjust loop is the part I keep coming back to. When the course agent flags "learners are struggling with topic X," how does it tell apart why? E.g., is it weak content, a missing prerequisite, or just disengagement? Those three need opposite fixes, so how confidently it diagnoses the cause before it rewrites the lesson. Feels like the whole thing lives or dies on getting that read right.

The auto-updating piece is the real standout, internal courses always go stale because nobody maintains them, having the course rewrite itself when the source docs change solves the exact reason corporate training fails the version history with rollback per cohort is a smart touch too, most tools would just push changes live and break things mid-course, one question, how do you handle the case where a doc gets updated badly or with wrong info? does a human have to approve before it reaches learners or can a bad edit silently propagate?

Hey everyone! 👋

I'm Kiran, CMO at StudyFetch.

I've had a front-row seat watching our team build this from the ground up, and it's incredibly exciting to finally share it with the Product Hunt community.

We believe there's a huge opportunity to help upskill the workforce, and Honen is our step toward that vision.

Thanks for checking us out today. We'd love to hear your thoughts and answer any questions!

The half-stale-by-launch problem is real - I've watched companies spend 6 figures on training that's outdated by Q2. Auto-updating from the actual docs/tools beats curated content by a mile. Curious how you handle role-specific deltas (e.g. ops needs a different slice of the same source). Following.

The auto-updating piece is the standout for me — training that rewrites itself when the underlying docs change solves the exact reason internal courses go stale. Congrats on shipping. How do you decide which changes actually warrant a lesson update versus noise?

Congrats! Integrating professional AI training for students alongside corporate training is a unique way to scale impact.

How do you prevent it from teaching the wrong thing if a doc gets edited badly or is outdated?

The automatic course updating definitely caught my eye. How seamless is that process in practice? If we completely overhaul our internal wiki, does Honen flag the changes for admin review first, or does it just push the new course version live?

The stale training problem is very real. Course generation is useful, but the stronger part is keeping courses connected to the knowledge base so updates don’t depend on someone remembering to fix onboarding docs later.

the parallel training idea is what makes this different from every other course builder. training your team and your AI agents from the same knowledge base so everyone stays in sync is something I haven't seen anyone else do. also the auto-update when source docs change is huge... we've had onboarding materials go stale within weeks because nobody remembers to update the training when the product changes

Hi Product Hunt,

I'm Phillip, another one of the makers of Honen, and I'm stoked that this day is finally here.

@ryan_trattner already covered what Honen is. I want to talk about the thing that took the longest to get right.

The easy version of this product is a course builder. Drag in docs, generate a course, ship it. That part works and it's genuinely fast. But a course builder is still just a fancier static file. You make it once, it sits there, it goes stale.

The hard version is making the course aware of itself. Knowing when learners are stuck. Knowing when the material no longer reflects how the world actually works. Having a course update itself without having to go back in, identify, and make the changes yourself. That's what we kept pushing toward.

The other thing that took real focus: one knowledgebase that trains your people and your AI agents at the same time. Same source of truth, same context, in sync. We call it parallel training and I think it's the most forward-looking part of what we built.

Honen.com, free to try. First course takes about 30 seconds.

Hi everyone!

I'm Esan, cofounder/CEO at StudyFetch

We've been heads down building this for a while, so it's exciting to finally share Honen with all of you.

The idea behind Honen is: Companies have more knowledge than ever, and context is changing almost everyday, but turning that knowledge into training is still way too slow and manual. We wanted to change that.

We're still early, but the response so far has been incredibly encouraging, and we're excited about what's ahead.

Thanks for stopping by and supporting the launch. I'd love to hear your thoughts and answer any questions.

Congratulations on the launch team 🙌
The parallel training concept is genuinely interesting
quick Q, how does the MCP integration work in practice? Do the agents pull from it dynamically, or is it a one-time sync?

The live client meeting simulation is a standout feature 🙌
what criteria is the AI actually grading on? Is it customizable per company or is it a fixed rubric?

@ryan_trattner Thanks for sharing what you've been building!

As others have previously indicated, the auto-updating aspect of the @Honen system is a notably attractive feature. Since human reviewers will necessarily approve updates before deployment, I'm curious about the process for review. How will the proposed changes be marked for the reviewer? How will the reviewer approve/deny a given change?

my friends and I have been talking about a product like this for some time now and its cool to see someone working on this! would you say that it is specifically designed for corporate learning or something that could be extended to desk-less workers as well?

this is very interesting. i have courses on GEO and it's actually hard to update them. creating is easy but so many things change that it's hard to keep up.

Hey Product Hunt 👋
I'm Abhinav Mohan, founder of Vaani.

🎬 How Vaani started

I was working on a personal video project a while back and wanted to make it accessible in a few languages beyond English. So I went looking for a tool and was genuinely shocked at what came back.
Voices that sounded like a customer-service IVR reading off a script. Lip sync that drifted two or three frames every line. Output that felt robotic in a way audiences clock instantly, even if they can't say why.
I kept thinking someone must have solved this for serious creators by now. Turns out, not quite. Most tools optimise for speed and the lowest acceptable output, not for keeping your actual voice intact across languages.
The more creators and brand teams I talked to, the clearer it became everyone was hitting the same wall.
And the data backs it up: a well-made dub routinely outperforms the original by 2–3× in non-English markets. But bad auto-dubbing actually hurts creators in the global YouTube algorithm, watch time drops, ranking falls, and channels lose ground in markets they used to win.
The wrong tool punishes you for trying to go global. That gap is exactly what we built Vaani for.

✨ What Vaani does

Vaani captures the fingerprint of your voice, timbre, cadence, breath, the way you swallow small words, and redraws it in 40+ languages with frame-accurate lip sync. One shoot. One render. Heard everywhere.
The core loop:
• Drop a video
• Pick the languages
• Vaani traces your voice, regenerates it in each script, and re-times every mouth frame by frame

👉 Try the interactive demo
https://app.arcade.software/share/zfXKZAc2lBD70Md6PzPm

⚡ Why Vaani is radically better

• Most tools translate words. Vaani retells meaning, so jokes land and tone holds.
• Most tools overdub audio. Vaani re-times every mouth frame by frame, so lips actually match. No other tool does frame-accurate lip sync at this scale.
• Most tools give one generic voice. Vaani captures your voice fingerprint and redraws it across 40+ languages, with more Indian languages than any other dubbing tool.
• Most tools make you dub one video at a time. Glot is a node-based batch canvas, drop multiple videos, fan out to multiple languages, add lip sync, render in parallel, download a zip.
• And it does all this at a fraction of the cost of existing tools.

👥 Who it's for

• YouTubers and podcasters reactivating their back catalog in 40+ markets
• Global brands shipping one ad in every language they sell in, same budget
• OTTs and studios regionalizing long-form content without losing the lead actor
• Course creators and educators reaching global cohorts
• Filmmakers who want a lip-synced, voice-cloned dub at a fraction of traditional cost

7 free minutes at signup,. Valid the next 7 days.

👉 Try Vaani free at https://vaani.media

💬 What we're hoping for today

Honestly? Feedback. Not upvotes. Specifically:
• What kind of content you'd try Vaani on first
• What's missing, every request goes into Linear, no exceptions
• If something breaks, please yell at us in the comments 🐛

🤝 The team

Built by a small team of four out of Bangalore 🇮🇳. I'll be in the comments all day myself, but the team's reading along, drop any technical, design, or roadmap question and we'll get it answered.

📬 Reach us

• 📧 hello@vaani.media
• LinkedIn: https://www.linkedin.com/company/advant-ai
• Discord Community: https://discord.gg/nJ5Meuh6v

Huge thanks to @rohanrecommends for hunting us, the @producthunt team for the launch infrastructure, and every one of you for reading this far. ❤️
I'll be in the comments all day (and most of the night, we're in IST, please forgive typos after midnight 🌙). Ask me anything.

Abhinav Mohan
Founder, Vaani

Voice preservation is the part I keep coming back to. Most dubbing tools flatten the speaker into a generic AI voice, so holding the original timbre across 40+ languages is a real differentiator. I work on voice AI for older adults, and we've found that a familiar-sounding voice changes how much people trust and engage with it, sometimes more than raw transcription accuracy. Curious how you handle emotional prosody: does the clone carry tone and pacing across languages, or mostly the timbre? Impressive that the lip sync stays frame-accurate at that scale.

I need this to be a plugin for Zoom / MS Teams - working live during the meetings.

The creator-trust angle here is strong. Bad dubbing doesn’t just sound off; it can make the original creator feel less credible in a market they’re trying to enter.

One workflow detail I’d care about: can users review the meaning/tone changes separately from the lip-sync render? For brand, education, and founder-led videos, the scary failure mode isn’t only “the lips drift,” it’s “the joke, caveat, or claim survived grammatically but not contextually.”

If Vaani can show a lightweight line-by-line review before final export — original intent, localized wording, voice/tone note, then render — I think teams would trust it for much higher-stakes content than simple back-catalog translation.

Wishing you success with the launch! Out of curiosity, which type of content do users test first: short-form videos, ads, or long-form series?

Do you let users review and change individual lines before export, or is it mostly one click end to end?

Love how Vaani focuses on keeping the creator’s identity intact instead of just translating words.

The frame-accurate lip sync + voice fingerprinting sounds like a game changer, especially for long-form content and ads.

Quick question: how does it handle humor, cultural nuances, and fast-paced dialogue?

Killing it Abhinav this has huge potential! 🔥

The fast-dub seems handy. I'll just add that if you would like a promotional "war room" for your projects, see The Den in mentionfox.com Engagement HQ for everywhere and to everyone you should comment/reply on, a Grants Search module, Accellerators Search & Apply Advice, and far more. Without it I'd be hard-pressed as a solopreneur.

As a music producer the "preserves your music" bit is what got me — most dubbing tools trash the background track the second they touch the vocal. Are you splitting out the music stem and dropping the cloned voice back over the original mix, or regenerating the whole thing? Curious how clean the music stays.

Lip-sync is key on video creation/edition and it's gonna help enough on it. Wish you all the best here guys!

You said the quality of the auto output is the thing people need to see first. How consistent is that first render when the input is messy, multiple speakers, background music, fast cuts? I'm curious whether a new user reliably hits the wow on clip one, or whether the result leans a lot on having clean source audio. If it does, do they find that out before they burn their 7 free minutes on the wrong test video?

Voice-preserving across languages is the right wedge - I build voice agents and the same gap exists in cloning: "close enough" voices break trust within seconds. Watch-time / ranking falling in non-English markets when you ship generic-voice dubs is a brutal stat. Following.

The lip-sync is the hard part most dubbing tools skip, so leading with it is a strong signal. Congrats on the launch. How do you handle emotion and tone carrying across languages — does the dub keep the original delivery?

The local-first no-cloud call is the interesting bet! Is no-sync a privacy stance you're committed to or a v1 scope line you'll cross later with end-to-end encrypted sync? Cheers

At first, I was like "Ok raycast has solved it already, and now it is native to macos" but when I'm seeing the interface, it looks really nice. I love how you use the dynamic island style.

What if I already have an app that uses the notch? Could I use another UI?

Congrats!

@soltwagner The visual timeline approach feels like the right fix for clipboard managers that turn into unreadable text dumps after an hour of deep work.

Curious if the app-level filtering works reliably with Electron apps like Figma or VS Code, since they often report generic window titles instead of meaningful context?

That’s usually where visual clipboard tools start to lose their edge over plain lists.

Drag-and-drop clipboard. I love that!

Clean, native-feeling clipboard managers are weirdly rare on macOS, so this is welcome! Congrats on launching. Does history sync across devices, or stay local for privacy?

As someone constantly juggling UTM parameters, ad copy variants, and brand hex codes, this looks like a massive lifesaver. Does Supaste allow you to pin or organize specific clippings into folders/tags for different campaigns?

That's a clean take. Is cross-device sync on the roadmap, or is it intentionally local-only?

I feel like every few years I convince myself I don't need a clipboard manager, and then spend the next week re-copying the same links, snippets, screenshots, and prompts 😅

Love the visual-first approach. Congrats on the launch.

Beautifully designed product! Well done : )

How does it compare to the now native macOS Tahoe clipboard history? Nicely done!

@soltwagner Thanks for sharing what you've been creating! I'm looking forward to trying this app in my design work.

I'm curious about temporary storage and memory usage. If video files or sets of large images are copied to the clipboard using this app, does the summed size of the files put strain on available memory that would normally not keep more than a single item on the clipboard?

This is one of those tools I can immediately imagine using during a messy building day. When I’m working on product copy, small design details, support replies, screenshots, links, colors, and random snippets, I constantly copy things that I know I’ll need again… and then somehow lose them five minutes later.

I like that Supaste treats clipboard history more visually, not just as a long technical list. The local-first part also matters a lot for this kind of app, because clipboard history can easily include private product stuff, emails, credentials, or unfinished drafts.

The one-time purchase is refreshing too. :))

Curious how you think about search: is it mostly exact text search, or can it also help find things more loosely, like “that screenshot from the dashboard” or “the blue color I copied yesterday”?

Local-first with a timeline that spans text, images, code, colors, and files in one searchable store is the hard part. Most clipboard managers pick one content type and add the others as an afterthought. I've hit the same mixed-type indexing tradeoffs when handling diverse data in a unified store. Do you use Core Data, SQLite, or something else for the local persistence layer?

Hi everyone!

Andrew spent over 20 years collecting and configuring more than 1,700 operating system installations, from 1948’s Manchester Baby to early mobile OSes, and packaged them into one ready-to-run VM.

It’s genuinely impressive how much obscure and historically important software is made runnable here. At a time when a lot of what we interact with is generated and smoothed over, there’s a certain appeal in being able to touch these older, rougher systems directly :)

I am missing the Painter software by Windows :D

This is one of those projects I would open “for five minutes” and then lose the rest of the afternoon.

The best part is that it is not just screenshots or nostalgia content. Being able to actually poke around old operating systems makes the history feel real: weird menus, slow workflows, forgotten UI ideas, all of it.

I’d love to see some guided paths too, like “early GUIs,” “forgotten mobile OSes,” or “systems that influenced modern desktop design.”

This is such a fun idea. I like that it's not just screenshots or nostalgia but actually running the old systems and seeing how they felt to use. A browser version would be amazing later but even as a VM it feels like a real archive people can explore instead of just read abt

Are these full emulated environments where you can actually install software and poke around, or more curated snapshots that show the UI without real interactivity?

Anyway that's awesome! Congrats!

Funny timing. I was wanting to put this to actual use. We've got a track coming out called Nostalgi (I make music) and I wanted that degraded VHS look for the Instagram Reels, without it feeling like the same one-click filter everyone's already scrolled past. This models the signal instead of faking it, so it should hold up. Bookmarking the browser version.

This is a great idea! I never had the chance to try the old OS (born too late for that ahah), so this is a great opportunity!

This immediately caught my attention because I also own a dog. Though I only have a dog myself, I also curious about that are you planning to expand the experience beyond dogs in the future, for example to cats or other pets? I can imagine many pet owners would love this kind of app.

This is very interesting. It seems positioned at a consumer app, but have you considered running a pilot program with vets, dog sitters, dog walkers, or doggy daycares? This could be an exceptionally useful and cute way for all of these businesses to give updates to their dog owners.

Congrats. Was curious if this is just for dogs or other pets as well?

Most pet apps stop at cute photo storage, so the AI-insights layer, which turns daily entries into actual patterns, is the harder, more useful half. Congrats on shipping. What kinds of insights can a new owner expect to get back, and how soon do they start showing up?

Hey Sorin, congrats on shipping this!

Went through the website after seeing it here and I really think the Crib concept is a warm feature.

One thing that stuck with me, though, is the origin story (allergic staffie, growing paper stack) might be a more compelling hook than "beautifully kept". That specific chaos is exactly what your buyer recognizes. I write landing pages for a living so this stuff jumps out.

Curious to see how this one takes off!

The monthly “warm letter” is a lovely touch. It makes logging feel rewarding and helps pet owners reflect on the month.

Congrats on the launch! A warm, story-driven approach to pet tracking is such a refreshing alternative to cold, clinical apps.

Love the philosophy behind this ❤️ Congrats on the launch! 🚀 I'm curious to see how the monthly recaps evolve, those sound like they could become something pet owners really look forward to reading and keeping over the years.

Congrats on shipping, Sorin! I love that you went journal first rather than tracker first for this.

I'm a solo founder building something architecturally similar in a different domain: AI-powered couples journal, where the AI's tone is similarly load-bearing (has to challenge without preaching, facilitate without taking sides). Two questions where I think your decisions might actually transfer to my work:

1. The "gentle AI that never nags or diagnoses" constraint is the most thoughtful part of Tamadoggo, and probably the hardest to get right. How is it actually encoded, is it primarily prompt-based, structural (the AI is given tools that only let it surface, never recommend), or a separate review layer that filters output before it reaches the user?

2. You mentioned the AI is built on Claude's tool-use through an MCP server. I'm currently on streaming Claude API and have been wondering whether tool-use is the better fit for the kind of pattern-surfacing-across-events work both our products do. What pushed you toward MCP + tool-use over prompt-based generation?

Hey Sorin, love the Tamagotchi throwback. Congrats on the launch!

On first look, It looks good. Do you have plans to allow for multiple pet owners to view the same pet profile? My partner usually feeds my dog breakfast while I usually take care of dinner. It would be great if we could both track which vitamins and toppers we each gave him or any big treats we each gave (my dog won't like this.. he definitely tries to shake us both down for maximum treat dispensing!).

Quick note - I created a profile and it took me about 3 tries to add a profile image. On first try, after I selected the photo, nothing happened. On second try, it took me to the image cropping page, then nothing happened. For context I am using an iPhone 12.

Hi everyone!

ntsc-rs is the kind of retro tool I actually love.

Most VHS filters fake the vibe from the outside. ntsc-rs goes lower-level and simulates the NTSC/VHS signal path itself, so the artifacts feel less like a preset and more like the real mess.

You can use it as a standalone app, in the browser, or as a plugin inside Premiere, After Effects, DaVinci Resolve, and other OpenFX editors.

There is something funny about this category. The artifacts people once tried so hard to avoid are now becoming the look people want back.

Maybe every medium eventually turns its failure modes into aesthetics..!

I dig this.. Especially that last line about every medium turning its failure modes into aesthetics. That's gonna stick with me. Happens in music too, tape hiss and distortion were problems people spent decades engineering out, now we pay for plugins to put them back. Funny world we live in. Cool project.

what a cool PH find for me. i love retro stuff. i remember cleaning VHS tapes for my grandparents. 😆

Modeling the actual signal path instead of slapping noise on top is exactly why tape-saturation plugins beat a "hiss" preset in music — the artifacts come from the chain, not a layer on top. Are they seedable so you can match the same look across shots?

this is awesome! reflection about the name - I thought NTSC and PAL were equivalent in Europe/US! Is there any actual difference of formats or is it just a nice name? :- D

It's funny how entire generations of engineers worked to remove these artifacts, and now creators are trying to bring them back 😄 Congrats on the launch!

This is exactly the kind of “VHS effect” tool I’d want to use.

A lot of retro filters just throw noise, scanlines, and a color overlay on top, and it looks fake pretty quickly. ntsc-rs seems more interesting because it actually tries to model the signal and tape artifacts behind the look.

The plugin support is also a big deal. If I can use it inside Premiere, After Effects, or Resolve instead of exporting through a separate toy app, it becomes part of a real editing workflow.

I really like this idea. Dont know why maybe becouse I was back then a teenager I used to use VHS casettes to record tv programms and rent movies on that formats. your solution gives me back that nostalgia feeling that is pretty rewarding. I added similar effect to my app, like monochromatic cinematoskope on which I watched VHS cassettes, So I pretty understand your concept. It is really really Great!

Hey guys 👋

I'm building modern open-source file manager that aims to be the best at everything.
Created with real skills, before the vibecoding slop.

Here's some of its major features:

- Smart global search: Finds files and folders in seconds (searches full `1TB` drive in under 2 seconds on average). Its typo correction system handles typos, wrong case, wrong word order, missing words, missing symbols, and missing file extension.
- Tabs: Keep multiple directories open and switch between them instantly.
- Split view: Any tab can be split into 2 panes which you can navigate independently and transfer files between them easily.
- Extensions and marketplace: Install extensions from the built-in marketplace or local folders. Extensions can add commands, pages, shortcuts, settings, and more.
- Default file manager: On Windows, Sigma can replace File Explorer for most everyday file actions.
- LAN file sharing: Share or stream files and folders over your local network, with browser access, QR codes, and FTP support.
- Network locations (Alpha stage): Connect to remote locations such as SSHFS, NFS, SMB, and CIFS.
- Address bar: Navigate with the keyboard, autocomplete paths, and quickly jump to parent folders.
- Item filter: Narrow large folders with glob patterns and property filters for size, dates, MIME type, and more.
- Smart drag and drop: Move or copy local files more comfortably, and handle web drops more smoothly.
- Shortcuts and command palette: Most actions are keyboard-friendly, with global shortcuts and a fast command palette for app and extension commands.
- Home banner and visual effects: Personalize the UI with custom images, videos, built-in artwork, transparency, blend modes, and other style controls.
- Dashboard and quick access: Reach favorites, tagged files, most visited locations, and history data from one central area.
- Tags: Organize your files and folders with tags.
- Zip archives: Compress files into `.zip` archives and extract them without leaving the app.
- In-app updates: Download and install updates directly from update notifications.
- Quick view: Instantly preview images, videos, audio, PDFs, and text files with `Space`, then move through files without opening external apps.
- WSL drives: On Windows, browse detected WSL distributions directly in the navigator.
- Localization: The app has translations for all most used languages.
- And more. Extensions provide additional features like video downloading (1000+ sites supported, including YouTube, Twitch, etc.), media converter, image size optimizer, etc.

Huge congratulations, Aleksey! I’ve been following the development of your SFM pretty much from the start and I’m thrilled to see how far you’ve come! It’s a pleasure to work with SFM and I hope you’ll keep delighting us with updates for a long time to come! The Extensions Marketplace, in particular, could do with a few more ideas!

As someone who moved from Windows to macOS about 15 years ago, I still occasionally miss Total Commander 😄

I’ve never fully gotten used to Finder. For me, file management is one of those core workflows where small UX improvements save a surprising amount of time.

A few features immediately caught my eye:

• ZIP archives without leaving the app

• Split view

• Fast search

• Keyboard-first navigation

One question: how far have you gone with hotkeys and folder navigation?

For example, can I assign shortcuts to jump directly to specific folders, favorites, projects, or frequently used locations? Fast navigation is probably one of the biggest productivity multipliers in a file manager.

Congrats on the launch and good luck today 🚀

Great idea, I hope there will be a macOS version as well. I know many users who have to work on at least two operating systems and then it would be nice to have the same UI no matter where you currently juggle your files.

File managers are one of those categories where the defaults (Finder, Windows Explorer) are good enough that most people don't switch unless something specific annoys them. Curious what the core workflow improvements are here, whether it's around things like batch renaming, directory diffing, or something more opinionated about how tabs and panes work. Also wondering how the cross-platform support holds up in practice, specifically whether the Linux build gets the same attention as the Mac and Windows ones or tends to lag on fixes.

Congrats for the launch!

@alsarem I have a question that , how are you handling compatibility as Claude's artifact formats evolve over time , especially for more complex React or TSX based artifacts ?

This fixes a very specific Claude workflow problem.

Artifacts are great while they’re inside the chat, but once I want to save one, tweak it, reopen it later, or show it like a normal little app, the flow gets awkward.

The folder watching and local reload are the details I’d probably use most. It turns artifacts from “cool thing Claude made once” into something I can keep editing on my Mac.

Claude Artifact Player lets you open and run the interactive files that Claude's Artifacts feature generates — HTML pages, React JSX components, and TypeScript TSX files — directly on your Mac, without a browser and without uploading anything anywhere.

WHAT IT DOES

Claude (Anthropic's AI) can generate standalone interactive files: data visualisations, UI prototypes, dashboards, calculators, mini-apps, and more. Claude Artifact Player is the fastest way to run those files locally.

KEY FEATURES

• Open any .html, .jsx, or .tsx artifact file in one click

• Watch a folder — the app auto-discovers artifacts as you add files and lists them in a sidebar

• Persistent folder memory — your folder is remembered across relaunches

• Fully offline — React 18 and Babel are bundled inside the app, no internet required for rendering

• Reload with ⌘R while you edit files externally

• Reveal any artifact in Finder with a right-click

PRIVACY FIRST

Claude Artifact Player never connects to the internet to render your artifacts. All JSX/TSX transpilation happens inside a sandboxed WebView on your Mac. Your files never leave your machine.

WHO IT'S FOR

• Developers and designers exploring Claude-generated UI prototypes

• Data analysts running Claude-built visualisations and dashboards

• Prompt engineers iterating on artifact outputs without copy-pasting into a browser

• Anyone who wants to keep a local library of AI-generated interactive tools

REQUIREMENTS

macOS 15 Sequoia or later.

Developed by Creative AI Studio — your partner for Generative AI.

Running artifacts locally solves a reproducibility problem that browser-sandboxed execution doesn't. We've built pipelines that generate Claude artifacts as outputs and realized testing them required the browser sandbox, adding friction. How do you handle artifact dependencies locally? Is there a containerized runtime, or does it rely on the host environment's installed packages?

Interesting use case. Does it handle artifacts that make API calls, or doesn't offline mode allow that?

One thing we've noticed with AI workflows is that artifacts often outlive the conversation that created them.

Do users mostly revisit artifacts for reference, or are they becoming reusable building blocks that get incorporated into future workflows?

Bundling React 18 and Babel inside a sandboxed WebView to handle JSX/TSX transpilation locally is a smart call. You skip shipping a separate runtime layer while keeping execution fully offline. I've run into the same tradeoff between isolation and dependency freshness. Do you plan to support ESM imports, or do all dependencies need to be bundled at the app level?

That folder-watch + ⌘R reload loop is the dream — I build little audio tool prototypes as Claude artifacts and the browser round-trip kills my flow. Does the offline player handle artifacts that use the Web Audio API / Tone.js for sound, or is it mostly visual right now?

Running interactive TSX/JSX components completely offline is a massive win for privacy. Are these rendered inside an isolated local sandbox like an Electron instance, or how are you handling secure execution locally? Congrats on the launch!

Hello, Product Hunt! 👋

After years of being a designer and developer, AI came into my life and changed everything. It gave me the confidence to go after my most ambitious products. But chat boxes and fragmented contexts across many apps aren't built for complex work.

As a founder, developer, and marketer, I'm a generalist. I work on many things that don't fit into single sessions. I needed a new kind of interface that works along with my brain, not against it.

Slashspace is a canvas-first interface for AI. It's a desktop app that stores everything locally. For each complex problem, you create a new space. Add all your documents to this space, connect to all the MCP tools you want, and run many agents.

All the agents see everything in the space. Run multiple agents in parallel, ask them to derive context from one another, and direct them to solve problems that you wouldn't have been able to do in a linear app.

Slashspace is the 10x generalist's interface AI interface. It can write, delegate, plan, code, create, and do many things. If ChatGPT raised the floor on who can build things, Slashspace is meant to raise the ceiling on what's possible for ambitious people and teams to build in the AI-era.

Previously, we were known as RabbitHoles AI – a node-based chat workflow. Slashspace is a result of everything we've learnt over the last 1.5 years.

Hope you all enjoy using the app, and share your feedback.

Best
Praneeth

Love the name and product, as a visual person this is my favorite way to use LLMs. The canvas approach just makes sense. Congrats on the launch!!

The “context space” framing is strong. For founder/marketer workflows, the hard part is usually not a single prompt — it’s keeping positioning notes, audience assumptions, research snippets, and draft messaging in view without turning the whole thing into one giant undifferentiated chat history.

I’m curious how you handle provenance inside the canvas: when one agent pulls from another node or attached document, can users trace which notes actually shaped the output? That feels especially important for marketing/strategy work where a confident sentence can sound good but drift away from the evidence.

Such a nice design and product overall! Great job!

I love how this is different, love the UX

Hey PH fam 👋

If you’re a power AI user, you already know the pain. You’re copy-pasting between Claude, ChatGPT, Cursor, Notion, and five browser tabs, playing telephone with your own ideas. Every context switch costs you focus AND costs the AI the context it needs to actually help you. Your best thinking keeps getting lost in disconnected threads. Slashspace fixes this at the root.

Slashspace is a canvas-first desktop AI interface where everything lives in one space. Your PDFs, websites, Slack, email, spreadsheets, YouTube videos. Connect your MCP tools, run multiple AI models in parallel, and let every agent see the full picture. No copy-pasting. No context collapse. Just deep, sustained, complex work the way your brain actually operates.

My friend @praneethpike and his team have been locked in on this problem for 2 years, first through RabbitHoles AI and now with Slashspace as the result of everything they’ve learned. That kind of earned conviction shows in the product. They’re all here today so drop your questions below 👇

Try it free for 3 days and see what becomes possible when your AI interface finally keeps up with you. 🚀

Local-first seems to solve more than just privacy.

Have you found users mainly care about ownership of their environment, or about having a workspace that naturally accumulates context over long periods of time?

I have been using the app, and Praneeth keeps improving it,
so I'm pleased to explore this new era of SlashSpace AI!
Congratas @praneethpike

The agentic web might just need this workflow. I'm looking at it. 👍🚀

A lot of men want to dress better but don't want to spend hours researching fashion advice. Making style guidance more personal and accessible is a great idea. Congrats on the launch!

Does Olo work off photos of your actual wardrobe, or is it mostly recommendations from a generic catalog?

The “what do I wear?” problem is very real for a lot of guys. I like that Olo seems focused on practical confidence, not just fashion inspiration. The most useful part would be getting advice based on what someone already owns instead of only suggesting new things to buy.

What kind of info or trends does Olo look at when giving outfit suggestions for guys?

It reminds me of when people were sharing videos using AI tools for outfit advice, and the results were often more funny than actually wearable😂

A really interesting idea, and definitely a relatable problem.

One thing I’m curious about: how does Olo actually learn my style?

From the screenshots, I don’t see an onboarding step with photos, wardrobe uploads, or body type analysis. So how does it determine what suits me personally versus giving more generic recommendations?

Would love to understand how the personalization works under the hood. 👀

The origin story is the strongest part of this for me, the fact that it came from conversations rather than a fashion background. That's usually the difference between a tool that solves a real frustration and one that solves an imagined one. "I never know what to wear" is a genuinely under-served pain for guys, most fashion advice assumes you already have taste and just need options.

The detail I like: letting someone upload what they already own and styling from that, instead of just pushing them to buy new things. That's the trust-builder, it signals you're optimizing for the user looking good, not for affiliate clicks. Curious how you're handling the cold-start problem, when a new user hasn't uploaded a wardrobe yet, does Olo lean on a few questions to bootstrap recommendations, or does it need the photos first to feel useful?

Also, Olo as a Finnish word for a sense of well-being, that's a quietly perfect name for what you're actually selling, which isn't clothes, it's presence. Congrats on the launch.

Interesting concept! Men's style can vary wildly depending on regional trends—does Olo take the user's location into account for weather and local fashion vibes when recommending an outfit? Congrats on launching!

Thank you to the 300+ devs who played the last challenge.

The results were insanely close. First and second place were only 13 seconds apart.

Your feedback helped us improve, add features, and make the challenge better.

What's new:

• Public leaderboard

• Enhanced challenge UI

• Added Terminal & SQL shortcuts

• Private Challenge Circle (beta) - compete against friends!!

• A special challenge (live now for 24hrs - check out the vid): Final Boss

Players defeat the boss.
K.O. plays.
Staging accepts the win.
Production rejects the ranked result under load.

Beautiful bug. Terrible day in prod.

Go play, test your engineering skills and compete globally!

The idea behind the challenge:
AI made writing code easier. But when production breaks, can it actually understand the system?
The Incident Challenge drops engineers into realistic production failures. You investigate logs, code, runtime, docs, and architecture, then ship the fix and race the leaderboard.

Agents are allowed. Encouraged, actually.

But the challenge is built around the messy parts of engineering that don’t fit neatly into a prompt: dependencies, runtime behavior, race conditions, misleading logs, and staging behaving nothing like prod.

Would love feedback from engineers, founders, devtools people, and anyone thinking about how engineering skills should be tested in the age of AI.

Hey hunters! 👋 Maker here.

Just shipped our hardest incident yet!

The setup: it's a retro arcade ranked mode. Staging confirms the win. Production rejects it. Same fight, same replay - and it only breaks during leaderboard rushes.

Here's the twist that's been wrecking playtesters: ranked combat got moved off a single synchronous path onto regional shards, each with its own worker pool. So now you get this:

A region that looks clean in one capture is not safe under load. The validator tells you how many regions are still wrong - never which ones. So you can't whack-a-mole it.

And the cheap fixes are all traps:

• Trust the client? The UI is lying - it's the whole point.

• Add a delay knob? Not a fix.

• Collapse back to synchronous? You just deleted the feature.

To win you have to make ranked finalization deterministic in every region under real concurrency - no stale canonical reads, no client authority, no synchronous cop-out. It's a genuine distributed-systems race condition dressed up as a boss fight.

Curious who can actually clear it without nuking the architecture. Post your region count when you're stuck 😏 we're reading every one.

This is super helpful actually, i'm a SWE and this tool helps me in local development, thanks.

Hey Product Hunt! 👋

I built FixtureKit because I kept wasting the first 20 minutes of

every project writing the same mock objects by hand. mockUser,

mockProduct, mockOrder -- all manually typed, all instantly outdated

the moment I changed the interface.

Every TypeScript dev knows this pain. Your types are perfect, but

your test data is a mess of "string", "string", 123.

The thing that bothered me most was that other tools either require

installation, send your schema to a server, or just fill everything

with meaningless placeholders. I wanted something that runs in the

browser, understands what field names mean, and gives you something

that actually looks real.

So FixtureKit infers from the field name -- email gets a real email,

price gets a real number, createdAt gets an ISO date. It's

deterministic so the output is safe to commit. And it supports MSW

and Playwright output so it plugs into the testing stack most

TypeScript teams already use.

Would love to hear what schema patterns break it -- that's the most

useful feedback I can get right now.

Update: schemas are now shareable as links.

Here's an Order fixture you can open directly:

https://fixture-kit.vercel.app/#JTdCJTIy...

Click "Copy link" on any fixture to share yours.

This solves one of those small dev chores that somehow eats half an afternoon.

I like that it starts from the schema I already have, instead of making me set up Faker rules from scratch. The Playwright and MSW exports are probably where I’d use it most, because mock data is much more useful when it can drop straight into tests or local dev.

Adversarial Mode is a nice idea too. Tables, forms, and profile screens always look fine until one weird string, empty value, or unsafe input shows up.

Is this tracking gotten locally from my git history, or do I have to connect accounts and upload data?

That's a great idea, but my problem is keeping up with regular data entry.

The Treckme.pro has reminders, but some extra motivation would be helpful (like in mobile games). Every time you enter data regularly, a plant grows, you level up a pet, or something like that. Gamification would definitely help motivate people to keep entering data.

I’d trust a skill timeline more than a polished CV, but only if it stays close to real work.

A resume line like “experienced with AWS” is too easy to stretch. Showing when someone used it, how often, and in what kind of project gives a much better signal.

The privacy controls would matter a lot though. Developers should be able to prove depth without exposing company details, private repos, or client work.

better than recruitment tasks created by LLM and solved by another LLM, or questions prepared and answered the same way

Hey Hunters 👋
I built Vox because I type a lot (AI prompts, emails, Slack, etc.) and every good dictation app I tried wanted me to send my voice to their servers, create yet another account, and pay for one more subscription. For something that hears everything I say all day, that felt backwards.

So Vox does the opposite: everything runs on your own device. You hold a hotkey, talk normally (the "ums", self-corrections, and lists are fine – it cleans them up), and the polished text lands on your clipboard ready to paste.

Whisper or NVIDIA's Parakeet do the transcription;
Superb local Gemma 4 model or Apple Intelligence do the cleanup.

No audio, no transcripts, no telemetry ever leaves your machine – you can verify it yourself with Little Snitch or GlassWire. It even works on a plane.

A few things that make it nice to actually live with:
1. No account. Download, hold the key, start dictating. Nothing to sign up for.
2. Voice modes. It picks a cleanup style based on the app you're in (formal for email, terse for Slack, present-tense for code comments, etc.) or you can write your own.
3. Free for personal use. Your own writing, side projects, hobby work – free, forever. (If you want to roll it out to the multi-person company, there's a commercial license.)

It runs on Apple Silicon Macs (M1+, macOS 14+) and Windows 10/11.

What I'd love feedback on: the cleanup quality across different apps, and whether the voice modes match how you actually write. If there's a mode you wish existed, tell me – custom modes are a core feature and I want to see what people build.

You can see everything I'm planning to work on at rizenhq.com
Say hi on X.

Report issues in Github.

Join the Discord community.

Thanks for taking a look 🙏

P.S. macOS version is already live for almost a month, was used by 300+ people and polished according to the feedback.
Windows is more fresh. While it has all the features, some bugs may be present.

– Serhii Klymenko

This is an amazing product. I have always wanted a tool that allows me to use dictation everywhere, but the issue was that every single app has their own dictation capability and they all differed in quality. On top of that you almost always have to manually clean it up afterward. This meant that it always felt more cumbersome to dictate rather than to type.

Building Vox as a Mac app changes things completely and the AI layer on top of it makes it feel absolutely seamless. I still have to remind myself to stop typing and start dictating but I can see this app changing how I work completely. Well done.

I’ve been using Vox for a little over a week and am very impressed by it so far. Good luck with your launch!

The app-aware cleanup modes are the detail that stands out to me. Switching tone for email vs Slack vs code comments is exactly the context most dictation tools ignore. I build voice AI for older adults, where transcription has to survive slower speech, long pauses, and heavy disfluency, so I'm curious whether running Whisper/Parakeet fully on-device forces a smaller model that trades off accuracy on non-standard speech, or whether the local Gemma cleanup pass recovers most of that. Privacy-first dictation is a real gap. Nice work.

This feels like a pocket journal for whatever is on your mind. One small idea: have you considered adding a draw or doodle option in the future app version?

I like that StepMello does not try to turn rest into another task.

A lot of “calm” apps still end up asking you to build a habit, keep a streak, follow a structure, or measure your mood. Sometimes you just need somewhere to land for a minute, write one messy thought, breathe, and leave.

The best thing about this is the restraint. I hope it stays light.

Congrats on the launch Emily. How do you deal with the last minute chaos that turns up minutes before a match?

This solves a very practical match-day problem. Equal playing time sounds simple until you’re managing substitutions, rotations, and parent expectations from the sideline on one phone.

Any plans to support other sports too, or are you staying focused on soccer rotations?

I want to work on something that's a full coaching system reliant on AI. Something that would only require professional clubs to hire player managers. Seeing your product gave me so much hope.

The reproduced findings part is what stands out. A lot of security tools create more work by reporting “possible” issues, so confirmed bugs with clear reproduction steps feels much more useful for small teams that don’t have security people to triage everything.

Hey everyone. I’m launching a series of free data APIs for developers this week.

Today is the Financial Data API: a free, hosted API that unifies 26 financial data sources behind one interface. It covers much of what developers typically use libraries like yfinance for (real-time and historical market data, company fundamentals, filings, options, ETFs, commodities, rates, FX, indices, etc), without having to host your own infra. This and a lot more data that popular finance libraries do not cover.

It also includes a free inference endpoint, so you can ask finance questions and get source-backed answers in real-time.

If you have any questions about usage, rate limits, or anything else, let me know!

Read docs here: https://bluedoor.sh/apis/financial-data

How are you guys managing Yahoo Finances' Rate Limits? Cool product tho, I already have an use case - one of the most requested offerings on Cohesivity right now is Financial data

That's a pretty cool concept. I was actually looking for something like this for one of my projects, I will definitely give it a try! One question tho, you said it's free but I can imagine the infrastructure it will require, so how are you managing that?

Amazing product!!!
Have used this myself to cover topics of system design and dsa.
And honestly love the mock interview tool as well, helped me practice interviews so I could perform better in the real one!!!

Just started using the platform and honestly, I am amazed by how native the experience feels to me. I completely relate to the problem of managing stuff at multiple places during interview preparation and most of the times I end up keeping multiple tabs open which is definitely a clutter-filled way of doing things.

Good luck to the team building it and super excited to keep following this to see it going higher-further-faster :D

@swatiahuja Tried a quick look - the experience feels smoother than I expected. Curious to see where this goes

Maker here. Built this with Swati over the last year.

The voice interviewer took the longest to get right. Early versions felt like reading off a script. We rebuilt the turn-taking so it interrupts you, pushes on weak answers, and picks the next question based on what you just said. It finally feels like a real loop.

The feature I keep coming back to is the Feynman coach. You explain the core insight out loud before writing any code, and a judge scores your articulation. People who do this before mocks explain cleaner under pressure. That gap between solving a problem and explaining it is where most onsites get lost.

We ship daily. If the voice lags, a pattern is missing, or you want a track we don't have, drop it here. We read every comment and fix fast.

Best way to judge it: start a mock cold and see how far the interviewer pushes you.

What’s the one feature people stick around for the most, patterns, the coach, or the voice interviews?