{ "captured_at": "2026-08-27T13:00:00Z", "selection_rule": "Maker responses longer than 160 characters; manual editorial review remains required before briefing.", "comments": [ { "comment_id": "5810995", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "Hey Product Hunt 👋X1 is an AI app builder that takes you from an idea to an iPhone app ready for the App Store.Most AI app builders try to generate the entire app from one prompt. X1 guides you through it step by step. It asks focused questions, creates a plan for the whole app, designs each screen for you to review and edit, then builds the app in stages so you can test it on your iPhone as you go.X1 also remembers the decisions behind your app. If you change something later, it updates the screens, flows, and features that depend on it instead of treating every request like a brand-new prompt.When you’re ready to ship, X1 prepares your App Store listing, screenshots, and submission through your Apple Developer account.I built X1 because AI could generate an impressive first demo, but I still had no clear path to something I trusted enough to ship. The first version was easy. Keeping the whole app coherent as it evolved was the hard part.You can build a working prototype free at x1.new. No coding or credit card required.If you try it, tell me what you’re building and where X1 gets confused, makes a bad assumption, or slows you down. Brutal feedback is more useful than polite feedback. I’ll be here all day." }, { "comment_id": "5815822", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@rohanrecommends Honestly, because we care a lot more about whether someone can build a successful app than whether X1 can technically support every platform.iPhone is just a much better place to start if the goal is helping people actually make money. App Store users spend dramatically more than Android users, despite Android having way more downloads.We also wanted to do one thing and do it really well. Building for iOS lets us obsess over the design quality, subscriptions, testing, App Store submission, etc. instead of being mediocre across 5 different platforms.Android will come, but iPhone first is very intentional :)" }, { "comment_id": "5815829", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@jurgen_pergega Appreciate it 🙏 that was honestly the biggest pain for me too.You’d get the app 80% there, make one “small” change, and suddenly 3 other parts would stop making sense because the model forgot why they were built that way in the first place.We’re definitely not perfect yet, but getting that right is a huge part of what we’re trying to solve." }, { "comment_id": "5816026", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@mogabr Yeah totally fair question. I think the easiest way to explain it is with the house analogy.Lovable/Replit/Claude/Codex are all getting insanely good at being the construction crew. You tell them what to build and they can execute extremely fast.X1 is more opinionated about what happens before and around that execution. We ask the questions, create the blueprint, break the app into smaller scoped pieces, design each part, then build + test against the same plan.That mattered a lot to me personally because I got pretty far with Cursor/Claude and eventually had hundreds of files, conflicting plans, and no idea what was actually finished or what would break if I changed something.So the bet with X1 isn’t “our model writes better code.” It’s that AI works best when you give it a well-defined problem, the right context, and a way to verify the result. We’re trying to productize that whole process for people who don’t already know how to do it themselves." }, { "comment_id": "5814813", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@angelo_bram That's exactly what x1 is built for! You bring the idea, X1 plans it out, designs the screens, builds each part and lets you test it on your iPhone as you go. Once your happy with your MVP, it preps the App Store listing, creates glamorous screenshots and submits the app to the app store through your Apple Developer account. No code needed on your end. The more thoughtful you are answering its questions along the way, the better the MVP comes out. It's less \"type one prompt and walk away\" and more you steering while it does the heavy lifting." }, { "comment_id": "5815831", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@angelo_bram  @maksym_shcherbakov1 Codex and Claude Code are insanely good. The problem I ran into wasn’t code generation.I used Cursor + coding agents for months and eventually had hundreds of files, half-built features, conflicting Markdown docs, and genuinely no idea what was finished or what I should build next lol.I was generating software faster than I could keep track of it.That’s the gap X1 is trying to solve. We give the models smaller, well-defined jobs, but also keep the product decisions, designs, milestones, and what’s already been built in one living plan.So Codex / Claude Code are incredible tools for writing code. X1 is trying to give you the path from “I have an idea” to “this is actually in the App Store.”" }, { "comment_id": "5816127", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@techterra Appreciate it 🙏 would love to see what you build.We’re actually beta testing Figma MCP right now. The idea is to let people bring Figma into the workflow without losing the product context / plan X1 is already building around.Not fully rolled out yet, but definitely coming." }, { "comment_id": "5815965", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@salte37 Yep, payments are part of the build.The important part for us is not just slapping a paywall on at the end. X1 treats payments/subscriptions like any other product decision, so it thinks through who pays, when they pay, what gets unlocked, what happens on cancel/downgrade, and how the rest of the app should react.Basically: monetization is part of the blueprint, not a bolt-on." }, { "comment_id": "5814429", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@essam_sleiman Yeah, Replit is probably the closest comparison.The main difference is that X1 is built around how a strong engineer would actually use AI: on well-defined, scoped problems with the right context.So instead of asking the model to build your whole app and then iterating through chat, X1 breaks the app down, works through the important decisions for each part, designs it, then builds and tests that piece before moving on.Replit gives you a very capable AI builder. X1 is more opinionated about the process around that builder." }, { "comment_id": "5814901", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@flora_kendall 3rd party integrations are a must have for any production level app, so X1 connects out to whatever your app needs, and this is actually one of my favorite parts. X1 has an integration studio built around just this. Some things come preconfigured so you don't lift a finger, like the database and auth through Supabase and AI services through OpenAI, all managed by us. For popular third party services X1 has an agent that literally signs up and sets them up for you, grabs the keys and wires them into your app. You don't even need to know the name of the integration, if you just ask for a capability outside the usual list, it'll go discover a real provider for it and set it up the same way. So no, you're not boxed into only what lives inside X1, you can pull in the services your product actually calls for." }, { "comment_id": "5814464", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@boris_skurikhin This would actually be a sick test case lol.For something like Restaurant City, I’d estimate around a week to go from the first prompt to a genuinely playable version on your phone. You’d probably have something basic much sooner, but a week feels realistic once you include the actual game logic + iteration.If you build it, please send it to me lol. I want to see this." }, { "comment_id": "5815020", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@rivendell_chorro Thanks! 🙏 The ones that really push it are the apps doing heavy lifting on the device itself, like a sports app that takes an uploaded video and runs detection on it, tracking every joint frame by frame to break down someone's mechanics.\n\nOr the live ones, think a fleet platform pulling real time GPS off a bunch of drivers, optimizing routes across dozens of stops and firing geofence alerts as vehicles move. That stuff stacks a lot of hard problems into one app, on device vision or live data, a real processing pipeline, and a web of integrations behind it that all has to stay in sync and still feel seamless to the user.\n\nGetting those to come together through the step by step build instead of one giant prompt has been easily the most satisfying part so far đŸ’Ș" }, { "comment_id": "5814380", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@boyuan_deng1 Yeah, surface level the promise is similar. The biggest difference is how X1 thinks about building the app.\n\n\nWe try to emulate how a strong product team actually works: figure out what should happen, make the product decisions, design the screens, build that piece, test it, then move on.\n\n\nAI accelerates each of those steps instead of pretending they can disappear.\n\n\nSo rather than “describe your whole app and hope the model gets it right,” X1 works through it with you piece by piece and keeps those decisions connected as the product evolves.\n\n\nThat’s really the bet: AI should compress the product development process, not remove it." }, { "comment_id": "5814989", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@james_carter35 Well there hasn't been much pushback on this new way of building an AI builder, most people are genuinely intrigued by the more controlled approach.\n\nBut honestly, during early development the thing that surprised me most was how much people pivot mid build. I kind of assumed folks would come in with a fixed idea and follow it through, but what actually happens is they get a few milestones in, see it running on their phone, and go \"actually, no, let me change this core thing.\" and at one point it was frustrating to see people start with building an e-commerce system and pivot to a live streaming app for some reason (it still triggers a form of PTSD when I remember dealing with that lol) At first that felt like worst case.\n\nBut it's really a byproduct of the thing X1 is actually built around, which is keeping all the context of your app present without it eating up or plaguing your future decisions. Once that context holds, a pivot stops being scary, because changing one core thing updates what depends on it instead of quietly breaking the rest of the app. So it reframed how much that foundation matters." }, { "comment_id": "5815842", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@conduit_design Glaze is a bit different since it’s focused on Mac apps. Rork is the closer comparison.\n\n\nThe easiest analogy is building a house.\n\n\nRork is more like telling a really fast construction crew, “Build me a 6-bedroom house,” and they start building.\n\nX1 first asks who’s living there, where the bedrooms should go, what matters to you, etc. Then it makes one blueprint and builds the house piece by piece against that blueprint.\n\n\nBoth can build the house. Our bet is that the blueprint + process matter a lot once you start changing things.\n\n\nIf you move a bedroom later, X1 should understand that the plumbing, hallway, electrical, etc. might need to change too instead of just moving one wall." }, { "comment_id": "5816710", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@barnaby_lloyd If something is unclear, it asks a narrower question. If two requirements conflict, it surfaces the conflict and makes you choose before it keeps building.\n\n\nThe rule we’re trying to follow is basically: assume the cheap/reversible stuff, ask about the decisions that can break the app later." }, { "comment_id": "5814803", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@olivia_bennett7 Yeah it does. Auth and per user data are core to most real apps so X1 handles that path directly, supporting apple sign in right off the bat. It sets up user accounts on the backend so each user gets their own data, then wires the screens to that instead of faking it with placeholder content. It also treats those as real product decisions, so it'll ask how people should sign in and what data belongs to a user, then build the flows around it. You end up with something that actually persists and personalizes, not just a demo that looks logged in lol" }, { "comment_id": "5815844", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@samsc Appreciate it 🙏 and yeah the AI comments are getting so out of hand I genuinely can’t tell who’s real anymore lmao\n\n\nThe guided structure is really the whole bet though. We’re trying to make it feel less like staring at a blank prompt and more like having someone who knows what questions to ask, what to build next, and when something is actually ready to move on." }, { "comment_id": "5814555", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@alan_dweck man this means a lot. honestly the best part of building X1 has been seeing someone actually get all the way to a finished app instead of getting stuck at the “almost there” stage lol. appreciate you taking the bet on us early đŸ«Ą" }, { "comment_id": "5815983", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@raunaks_99 means a ton man 🙏 we spent an honestly unhealthy amount of time obsessing over the UI lol\n\nreally appreciate you trying it this early. still so much we want to improve but very excited about where this goes" }, { "comment_id": "5814311", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "Finally something that doesn't glaze the whole one-shot-your-app thing. I'm sure people will find it refreshing to see a tool that walks you through each milestone of your product, keeps everything coherent as it grows, and lets you see it on your iPhone every step of the way." }, { "comment_id": "5814964", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@colton_drake Good question. The way I think about it, the two aren't in tension. X1 automates the build process, the actual work of getting the app made, but it never builds anything you haven't already approved. We don't quietly assume the important factors, we surface them for you to decide, just in a way that isn't a lengthy back and forth or a form, and it's not a one prompt to publish thing either.\n\nThe big control moments, reviewing the plan and every screen before it's built, are always yours. So X1 does the heavy lifting while you stay the one steering what actually gets built. However, we also cater to your everyday exploration mode where you are testing apps to see what sticks, so you even control how much control you want. You can absolutely let X1 take the wheel and roll with all the recommended routes without ever getting into a debate about it.\n\nSo if we talk about balance, it's up to you, you can take 100% of control, or none of it (I would advise against the latter tho lol)" }, { "comment_id": "5814489", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@ristan_nakko Yeah, I had the exact same experience and it was infuriating because you could taste how close you were.\n\n\nThe app would be 80% there, then a few edits later the model would forget why something was built a certain way and start breaking other parts.\n\n\nWe’re definitely not perfect yet, but that’s really the mission with X1: keep enough context and structure around the product that every new change builds on what came before instead of slowly undoing it." }, { "comment_id": "5814319", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@abod_rehman Definitely more back-and-forth. We try to only ask when the answer would meaningfully change the app or create downstream decisions. If something is obvious or easy to change later, X1 just makes a reasonable call and keeps moving.\n\n\nThe questions are also based on your app and previous answers, so it shouldn’t feel like filling out the same form every time. The goal is basically to catch ambiguity before X1 turns it into a bunch of assumptions you discover 20 changes later." }, { "comment_id": "5814351", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@justin2025 That’s exactly the failure mode we’re trying to avoid.If you pivot, X1 treats the old decisions as things to re-evaluate, not sacred memory. It updates the plan/underlying decisions, figures out what actually needs to change, and keeps the parts that are still valid instead of rebuilding everything from scratch.The goal is for memory to preserve context, not trap you in it." }, { "comment_id": "5816063", "product_id": "x1-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@hareesh_vemasani Appreciate it 🙏 that’s exactly the bet.AI is already insanely good at the individual pieces. We just think the missing part is giving people a clear path through all of them without having to figure out the whole product/dev process themselves." }, { "comment_id": "5807321", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "Hey Product Hunt! Hao here, founder of Expertise AI.\n\nHuman expertise is the most valuable asset in the world, and it's the only one with no infrastructure. Money has banks. Content has platforms. Code has repos. But the way the best GTM people share what they know hasn't changed in decades: you give it away as content, spend hours explaining it on calls, or hand over a file and lose control of it forever. The moment your playbook leaves your hands, it stops being yours.\n\nSo we built the missing infrastructure. On Expertise AI, you publish your playbooks as AI skills on a storefront of your own. Businesses demo them for free, install them in one click, and the skill personalizes itself to their business, their ICP, their stack, without you running a single setup call. You choose whether your playbook stays locked so nobody can ever see inside it, or goes open-source for the world. Either way, your name is on it, and you get paid while it runs. We think this is the start of the AI skills economy, and GTM is just where it begins.\n\nThe thought we kept coming back to while building: you built it, you own it. Everything in the product flows from that one idea.\n\nWe're launching today with our founding experts, and founding spots are open. If you're sitting on playbooks that work, we'll build your first skills with you and migrate your existing files free.\n\nI'll be here all day. I'd especially love your hardest questions about how we protect what experts publish, because that's the part we built first. And if you've ever tried to productize your own expertise, tell me where it broke down. That's the exact problem we're working on.\n\nLearn more: https://www.expertise.ai/" }, { "comment_id": "5815595", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@haozhe_sheng Adding one from inside the team: on the expert calls I've sat on, productizing never failed at the creation stage. The frameworks were already written. It failed at the selling stage, where every option either sold their hours or handed over the file. That gap is the whole company. Proud of this one, Hao." }, { "comment_id": "5815619", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@haozhe_sheng Watching Hao lead this from an idea into a product has been pretty special. He’s been so intentional about the problem we’re solving and the kind of company we want to build around it. A lot of work goes into getting to a day like today, and I’m really glad I got to be part of that journey. Big day for the team đŸ€" }, { "comment_id": "5814846", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@1251912798Well said. Building an agent is getting easier, but the real value is often in the experience and decision-making behind it. That’s the part we want experts to be able to share, protect, and get paid for." }, { "comment_id": "5815145", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@1251912798 Well said. Building an agent is becoming easier, but capturing and distributing the expert judgment behind a great one is still largely unsolved. That’s the layer we want Expertise AI to unlock. 🙌" }, { "comment_id": "5815577", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@1251912798 The hard part isn’t just building the agent, it’s capturing all the little decisions and context that make it actually good. That’s usually the part that lives in someone’s head and is hardest to share. Really excited about making that easier for experts to pass on 🙌" }, { "comment_id": "5814633", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@chilarai Thanks! Each skill has a shareable link, so your teammates can open it and run the same workflow without setting anything up. If you publish as an expert, it can also live on your storefront for others to try and install.\n\nThe range is pretty broad. Campaign diagnostics, pipeline reviews, account research, deal coaching, follow-ups, and deliverability audits are all good examples. If it’s a repeatable process that relies on your judgment, it can probably become a skill. Happy to help with your first one!" }, { "comment_id": "5815507", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "Really excited to see this launch come to life! So much knowledge lives in people’s heads, gets buried in docs, or disappears after a one-off call. Expertise helps turn that hard-earned judgment into something teams can actually use, while keeping it protected and owned by the people who created it.\n\nProud to be part of the team behind this." }, { "comment_id": "5815584", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@bee_sayabo Bee!! Couldn't have gotten here without you. All those hours you spent testing skills before anyone else touched them is a big part of why launch day worked. đŸ€" }, { "comment_id": "5815887", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@bee_sayabo Couldn’t have said it better. Turning hard-earned judgment into something useful, reusable, and still owned by the expert is why we built this. So grateful to be bringing it to life with you and the rest of the team ❀" }, { "comment_id": "5815365", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "Marketing at Expertise here. I spent the last few months sitting on calls with GTM experts, and almost every call had the same moment. They'd light up describing a playbook they'd refined over years, then catch themselves with some version of \"but I can't just hand that out.\" These are people who teach for a living, and even they had a drawer of stuff they'd never share because sharing meant losing it.\n\nFor most of them, the thing that sold it wasn't the monetization pitch, it was seeing the lock on their own skill for the first time. If you're browsing the launch, open a couple of the expert storefronts, that's where the whole idea clicks." }, { "comment_id": "5815564", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@riddhima_agarwal Exactly. The GTM experts have performed these workflows manually for years, have seen the other side, and know what will work and what won’t. They have the 3‑D picture.\n\nThe sad part is that, for all these years, they have shared these learnings for free as an MD file or Claude skills. They sit untouched, collecting dust in people’s download folders. We are ensuring the GTM experts’ skills are respected, used, and that they are rightfully rewarded. Now anybody can run these skills, but the experts don't lose the IP. They own the thinking behind it, and the users can experience the outcome. It's a good win-win, right?" }, { "comment_id": "5815591", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@vinayraj_1988 Right, and the 3-D picture is the part no doc ever captured. Once experts see that getting used more doesn't mean getting copied more, they stop holding back their best stuff. That's the unlock." }, { "comment_id": "5815933", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@itskevinma Yes exactly. One person getting a great result is a demo, the whole team reproducing it is a system. That's the entire reason skills carry the expert's setup with them instead of a prompt someone has to reinterpret." }, { "comment_id": "5815960", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@itskevinma 100%. I think that’s where it gets really interesting too. If something only works when one person knows all the context, it’s hard for the rest of the team to actually use it. Making that knowledge easier to pick up and run with is a huge part of the value." }, { "comment_id": "5815830", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "I joined Expertise because the best AI shouldn’t come from better prompts. It should come from better people. Excited to help build a world where experts can turn what they know into skills they own, protect, and get paid for." }, { "comment_id": "5815207", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "GTM experts who've run workflows manually every day are giving that away those skills as free MD files sitting in someone's downloads folder, never opened. The moment something's free, its perceived value drops to zero.\n\nSo we went the other way. The IP can't be copied or owned, only run. Expert gets paid. Buyer actually uses it." }, { "comment_id": "5815360", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@vinayraj_1988 The downloads folder part is so true, we saw it play out with one of our first experts. He'd been giving his playbooks away as free MD files for years, and when he uploaded them as skills, people started running the exact same content he could never get anyone to open before. Kind of proves your point that free wasn't helping anyone, not even the people getting it for free." }, { "comment_id": "5815075", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@sandy_liusyThanks for following! There are so many great GTM playbooks buried in docs and people’s heads. We want to give them a place where others can actually find and use them." }, { "comment_id": "5815178", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@sandy_liusy Glad the idea clicks. We’re working toward a place where you can discover proven GTM workflows, try them, and install the ones that fit your team. More coming soon 👀" }, { "comment_id": "5815076", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@seantiffonnet Would love to see what you come up with! If you already have a playbook you use repeatedly, that’s probably the best one to start with. Let us know how it goes." }, { "comment_id": "5814997", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "Exactly! the goal is to turn the “how-to” into something teammates can actually run, without needing to understand the whole setup behind it. Especially helpful for non-technical teams. Thanks for calling this out @cruise_chen !" }, { "comment_id": "5815068", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@cruise_chenFor sure. Most teammates don’t want to learn the prompts, tools, and setup behind a workflow. They just want to use what already works. That’s exactly what skills are meant to make possible." }, { "comment_id": "5815534", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@cruise_chen Absolutely. AI adoption across orgs is what we saw as a major blocker. This makes it easy for the champion in a particular company to create skills, share them, and elevate his/her peers." }, { "comment_id": "5815464", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@josh_hamburger1 The two-way part is what sells it on every expert call. Marketing gets to make the promise because you built the thing that keeps it. Thanks Josh!" }, { "comment_id": "5815587", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "Huge shoutout to Josh and the engineering team for all the work behind the scenes to make this possible. I got to see all the long nights and bug fights firsthand, so it’s extra special to finally be here today. So happy we made it here, and I’m excited to see what comes next đŸ«¶" }, { "comment_id": "5816798", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@zhangchen Really sharp point. Usage alone can be misleading if the cost of running each skill is different. Gross profit per run is the right lens, and it’s something we’re thinking about as we build out analytics for experts. Thanks for calling it out." }, { "comment_id": "5814343", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@axelkane That’s what we’re betting on. Experts spend years developing their judgment, but until now the main options were courses, consulting, or giving the playbook away. Skills create a new way to share that value while keeping ownership." }, { "comment_id": "5815158", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@axelkaneWe think so too. There are so many experts with valuable processes sitting in docs, calls, or their heads. Giving them a way to package that knowledge, protect it, and earn from it could create a whole new type of expert business." }, { "comment_id": "5815551", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@axelkane Absolutely. So far, the GTM experts have been creating all these skills they have learned from years of trial and error and giving them away for free. As you know, people who get things for free don't value them. We are just changing the game." }, { "comment_id": "5815555", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@axelkane The creator economy so far has rewarded people who are good on camera, and a lot of the sharpest GTM operators aren't creators at all, they have zero interest in posting daily or filming a course. Skills give them a way in with the work itself instead of content about the work. That's the shift I'm most curious to watch." }, { "comment_id": "5814364", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@boyso That’s the idea. When someone finds a better way to use AI, the rest of the team shouldn’t have to rediscover it from scratch. Skills make that knowledge reusable across the company." }, { "comment_id": "5815163", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@boyso AI becomes much more useful when the learning doesn’t stay with one person. We want teams to turn individual wins into shared workflows that get better over time." }, { "comment_id": "5815552", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@boyso Absolutely. AI adoption across orgs is what we saw as a major blocker. This makes it easy for the champion in a particular company to create skills, share them, and elevate his/her peers." }, { "comment_id": "5815563", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@boyso Inside most companies right now there's one person who's figured out something great with AI, and their distribution method is a Slack message that scrolls away by Friday. The knowledge was always shareable, it just had no shelf to live on. That's the gap we're trying to fill." }, { "comment_id": "5815969", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@boyso  @riddhima_agarwal This is so true. I’ve seen this happen so many times in ops. Someone figures out something really useful, drops it in Slack, and then a few days later nobody can find it 😂 Having a place for those learnings to actually live makes such a difference!!" }, { "comment_id": "5814383", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@jocky Weekly campaign reviews are a really good fit. The numbers change, but the way an experienced operator interprets them should stay consistent. A skill can apply that same thinking each week and give the team a clear next step." }, { "comment_id": "5815150", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@jocky That’s a strong use case. A skill can apply the same expert framework every week, spot meaningful changes, and turn the latest campaign data into consistent, actionable recommendations. 🙌" }, { "comment_id": "5815547", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@jocky There you go: imagination is what's stopping us. Anything you imagine with your laptop, internet, and tools, you can just create here and achieve with any kind of playbook." }, { "comment_id": "5815184", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@ll_wen Thanks for such a thoughtful comment. This is one of the hardest problems we’ve focused on from the start. Protected skills run like a black box. People can use the skill and see the results, but they don’t get access to the instructions, knowledge, or workflow behind it.\n\nWe also have safeguards for prompt extraction and repeated probing. At the same time, we want to be honest that no black-box system can make inference completely impossible. Our goal is to make the expertise very difficult to copy while keeping the skill genuinely useful. This marketplace only works if experts trust us with their best work, so we take that responsibility seriously. Really appreciate the support!" }, { "comment_id": "5815186", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@ll_wen Thank you! This gets to one of the most important challenges we’re solving. A protected skill exposes the outcome, not the playbook behind it: the instructions, knowledge, and decision logic remain hidden when someone runs it. We also account for extraction attempts and repeated probing, while being honest that no black-box system can eliminate inference entirely. The goal is to make expert workflows useful to customers without making them easy to copy. Earning that trust from experts is foundational to the marketplace we’re building." }, { "comment_id": "5815544", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@ll_wen  @avamorgan_ Absolutely. AI adoption across orgs is what we saw as a major blocker. This makes it easy for the champion in a particular company to create skills, share them, and elevate his/her peers." }, { "comment_id": "5815543", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@ll_wen Absolutely. AI adoption across orgs is what we saw as a major blocker. This makes it easy for the champion in a particular company to create skills, share them, and elevate his/her peers." }, { "comment_id": "5815089", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@abby_mao1 Thanks! It definitely feels like the category is still being defined. That makes it a little scary, but also a lot of fun. We’re excited to build it alongside the experts using the product early." }, { "comment_id": "5815172", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@abby_mao1 Appreciate that. Reusable expert workflows feel inevitable to us, but the right model for owning, sharing, and paying for them is still wide open. That’s the part we’re excited to explore." }, { "comment_id": "5815556", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@abby_mao1 More work remains. Our aim is to ensure everyone in your organization reaches the same level as its champion by making it easy to share workflows and adopt AI across the teams." }, { "comment_id": "5815578", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@abby_mao1 Thanks Abby! Our read is that the category stays unowned until someone wins the trust of the experts themselves, because the best playbooks never got listed anywhere they could be copied. Protection first, everything else after. That's our wedge, and we'll find out if it's the right one." }, { "comment_id": "5814350", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@sylvialane That distinction matters a lot to us. Knowing what to do is useful, but applying it inside the actual workflow is where the value really shows up. We want expertise to help people do the work, not just learn about it." }, { "comment_id": "5815160", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@sylvialane Courses and PDFs can explain the thinking, but someone still has to turn it into action. A skill brings that thinking directly into the task, so the expert’s process gets used when it actually matters." }, { "comment_id": "5815558", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@sylvialane \"Operational, not content\" is a great way to put it and funnily enough the experts feel that difference most. A few have told us that people who bought their course never finished it, but the same buyers run their skill every week because it does the task instead of teaching it. Usage turned out to be the compliment their content never got." }, { "comment_id": "5815170", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@shirley_mou Agents and models will keep changing, but a proven way of getting work done can stay valuable for years. That’s the layer we want experts to own and share." }, { "comment_id": "5815567", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@shirley_mou Exactly. Everyone's racing to build agents, but an agent with no expertise behind it is just a very confident intern. The workflow layer is also the part that survives, because when the next model generation lands, the agents get swapped out and the expert's process moves right over. Betting on the layer that outlives the tooling felt like the safer place to build." }, { "comment_id": "5814628", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@phoenixhu Five tabs and three tools sounds very familiar. If the process repeats often, a skill can handle the tool switching and let you focus on the decisions that actually matter." }, { "comment_id": "5815015", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@phoenixhu That’s a perfect first workflow to test. Anything that involves the same steps, the same tools, and constant copy-pasting is a strong candidate for turning into a skill." }, { "comment_id": "5815574", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@phoenixhu You've described the exact shape of task skills were built for. Browse the expert storefronts and there's likely already a skill covering your workflow, you can demo it before installing anything. And if your process is one nobody's covered yet, tell me what it is, I'd love to route it to one of our experts as a request." }, { "comment_id": "5815085", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@tiantian_liu1Glad that came through. Stalled deals rarely live in one system. You need both the CRM history and the actual conversation to understand what’s happening and decide what to do next." }, { "comment_id": "5815177", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@tiantian_liu1That was important to us. A useful skill needs real context from the tools where work happens, not just a polished prompt and a generic response. Combining CRM and email makes the recommendation something a rep can actually use." }, { "comment_id": "5815932", "product_id": "expertise-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@ben_kahan Such a good point. Not every great operator wants to become a content creator. They should be able to turn what they already do well into something others can use and pay for. Really appreciate the support today!" }, { "comment_id": "5814285", "product_id": "chatcut-ai-video-editor", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "Hi Product Hunt!\n\nLast month, we launched our ChatGPT/Codex plugin and received incredible support from this community.\n\n\nOne of the most consistent pieces of feedback was that you loved being able to connect your own agent, but wanted to work with larger files and have a faster, more reliable editing experience.\n\nSo we built ChatCut Desktop.\n\n\nIt includes everything you can do with our web app and plugin, but in a local environment. Your footage stays on your computer, and editing and exporting happen locally. You can use ChatCut’s built-in agent or connect your existing ChatGPT/Codex or Claude Code subscription and use the tokens you already pay for, making ChatCut’s core editing features free to use. A ChatCut subscription is only required for pro features such as Seedance and Kling video generation, XML export, AI voice generation, and voice cloning.\n\n\nToday, ChatCut is used by creators editing talking-head videos, tiktoks, reels and shorts, businesses producing ads and branded content, companies creating social content, internal videos and product updates, and AI filmmakers making films.\n\n\nGive ChatCut Desktop a try, and please send us any feedback, suggestions, or questions at team@chatcut.io.\n\n\nWe’d love to hear what you think. Go create something!" }, { "comment_id": "5815594", "product_id": "mcp-builder-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "Thanks @natalia_iankovych 🙏\n\nYes, generating is only the first part. Afterwards directly start a fully hosted and maintained instance with the click of a button. Add security (even if you donÂŽt have any oauth server on hands at the moment), check the logs and trace every call that is done from your AI Agent to the datasource." }, { "comment_id": "5814340", "product_id": "mcp-builder-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "Hi Product Hunt! I’m Michael, the technical co-founder of MCP-Builder.ai.\n\nOver the past few months, I received a lot of feedback from the developer community. One thing became clear: building an MCP Server with a builder shouldn’t feel like configuring infrastructure. It should feel more like building a custom piece of software that you can use in your favorite AI dev tools.\n\nSo we redesigned the experience around conversation. You describe what you want to connect and what you want your AI tool to do, and MCP-Builder.ai helps create it for you, while taking care of the work that comes after coding: hosting, maintaining and running the server.\n\nWe also simplified authentication and security configuration, making it easier to choose the right setup without getting buried in complexity.\n\nWould love to hear your experience and your feedback using MCP-Builder.ai!" }, { "comment_id": "5814538", "product_id": "mcp-builder-ai", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@priya_kushwaha1 Great question, Priya. The Reverse MCP Gateway establishes an outbound connection from the on-premise environment, so internal systems don’t need to expose inbound ports to the public internet.\n\nWithout a gateway, teams typically need to expose an endpoint, configure and maintain a VPN or private connection, or build their own secure bridge between the cloud and internal systems. That adds setup, security and operational overhead.\n\nThe gateway does add a network hop, but in most use cases the overhead is small compared with the response time of the connected system or AI model. For us, that’s a worthwhile trade-off for securely connecting internal systems without exposing them publicly." }, { "comment_id": "5810526", "product_id": "tellie-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "I hate teleprompters.\n\nNot the idea. The experience.\n\nThey make you follow them. Pause and it keeps scrolling. Go off-script and you’re suddenly lost on a screen. Worst of all, you end up sounding like you’re reading instead of speaking from the heart.\n\nI thought, why can’t the prompter follow you?\n\nSo I built Tellie.\n\nPeople don't want to read a script, they want to tell a story. They skip sentences. Rearrange things. Go off script. Say the same idea in completely different words.\n\nTellie listens (on-device) to the actual words you’re saying and follows you. Pause, skip, ad-lib, say it your way. Tellie keeps up. With 1.5's new Stagehand feature, it now understands what you’re trying to accomplish, even when you use your own words.\n\nTellie can tell you:\n\nYou’re missing an important point\n\nYou’re running long\n\nYou covered the things you needed to cover\n\nYou finished the take but skipped something\n\nYou went off script
 and that’s probably okay\n\nEvery teleprompter answers one question: where am I in the script? Tellie answers it by following the words you actually speak, and knows what you still need to say. That's why I call it an unprompter.\n\nIt's only 3 MB. Completely local. Your voice never leaves your Mac. Invisible to Zoom and screen recorders.\n\nTellie 1.5 is $19 today with code PRODHUNT10 (normally $29). One-time purchase, never a subscription. Each download comes with 10 days free.\n\nIf you make videos, pitch, teach, interview, or just need to sound like yourself instead of a script, try it.\n\nAnd if you need a feature I haven’t thought of yet, tell me. That’s how most of the good stuff got built." }, { "comment_id": "5815049", "product_id": "tellie-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@busmark_w_nika Thanks! It works just like a regular teleprompter for the less experienced too! It’s just a lot more forgiving AND it can coach you. I’ve heard from users who used to rely on paper - the fact that your notes float right by your camera helps maintain eye contact so you don’t have to glance away." }, { "comment_id": "5815372", "product_id": "tellie-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@jay_janarthanan1 Good point, Jay! The free version is a basic teleprompter and Pro has all the good stuff. And each download gives you Pro for 10 days so you can try everything. More here, about midway down the page: https://tellieapp.com/pro" }, { "comment_id": "5815375", "product_id": "tellie-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@shahriar_johari1 I'm working on a version that will work on any web browser, including Android. Just not ready yet. Thanks so much for the comment and upvote, Shahriar!" }, { "comment_id": "5815377", "product_id": "tellie-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@ankur_bolia Coming soon! Actually, it will run on any web browser, phone, etc. My idea is to have it run on your main computer and use your devices to control it when on camera. Love any feedback!" }, { "comment_id": "5815700", "product_id": "tellie-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@lilamoreau Thank you so much, Lila! That's exactly right! Tellie is the teleprompter that understands. No longer do you follow a script. Tellie follows you! Thanks again for your feedback!!" }, { "comment_id": "5815427", "product_id": "tellie-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@natalia_iankovych OMG thanks so much!! Glad Tellie helps - any feedback on features and I’ll build it for you! That’s how many of its features were designed - by early users. Thanks again!!" }, { "comment_id": "5815509", "product_id": "tellie-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@natalia_iankovych BTW, I'm building this in public so others can see how much they contribute simply by sending me an email asking for features: Feel free to ask here: https://tellieapp.com/#public" }, { "comment_id": "5815125", "product_id": "tellie-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@alexcloudstar thank you so much, Alex! One of the reasons I built it was for that exact problem. You’re almost done your take and you stumble. Tellie is like a companion that helps you hit your marks because you relax knowing it is checking your points and the clock for you." }, { "comment_id": "5814091", "product_id": "opencomputer", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "Hi PH - today we're launching OpenComputer.\n\nDeploy your agent as a function, get a computer for it.\n\nWhat you can expect:\n\n1. Write an agent as a TypeScript function. Deploy it. We run the loop, the sessions, streaming etc\n2. Every session runs on a real Linux machine.\n3. Your tools and MCP servers run on that machine - clone a repo, run ffmpeg, drive a browser, install anything.\n4. Sessions are durable: can be steered mid-run, hibernate when idle, resume where they left off.\n5. No model keys in your runtime. Bring your own or use our managed gateway.\n\nGive it a shot and let us know what you think, we're very keen on feedback!" }, { "comment_id": "5814213", "product_id": "ify-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "Hey Product Hunt 👋,\n\nWe built Ify because every AI support tool we looked at asked for the same trade: rip out your helpdesk, spend weeks migrating, then maybe get an AI agent that's actually useful.\n\nIfy skips that. It works directly on top of Freshdesk, Zendesk, Salesforce, or HubSpot — so you keep what you have and just add the part that resolves tickets. If you don't have a helpdesk yet, it can run standalone too.\n\nThe thing we spent the most time on isn't the chat widget or the automations — it's the knowledge base. Almost every team we talked to had messy or incomplete docs, and that's usually what kills an AI support rollout before it starts. So Ify builds its own: it scrapes your site and docs, turns release notes and past resolved tickets into SOPs, and keeps learning from what your team resolves manually.\n\nWe're in private beta right now, working closely with early SMB and mid-market support teams to get this right before we open it up further. If you're curious how it'd fit with your current stack, or you've hit the \"our docs aren't good enough for AI\" wall yourself, I'd love to hear about it in the comments.\n\nWould really appreciate any feedback, questions, or just tell us what you'd want an AI support agent to actually do.\n\nRegards,\n\nKarthik - Founder @ ify" }, { "comment_id": "5814515", "product_id": "ify-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@saurabh_p Thank you, means a lot coming from someone who's been in customer support for a decade+. Glad the documentation, up approach resonates, that's the part we're most proud of. 🙏" }, { "comment_id": "5815024", "product_id": "ify-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@nivasravi Great question! Ify connects to thousands of business apps, so it goes beyond answering questions it can issue refunds, change subscriptions, update accounts, and take other actions directly in the tools your team already uses.\n\nOn top of that, there’s no per-user licensing, so your whole team can log in without additional seat costs. This broad action layer, combined with learning from your existing support knowledge, is Ify’s core strength." }, { "comment_id": "5815505", "product_id": "ify-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@rahul_rajpal  Thanks Rahul, great questions!\n\nIfy doesn’t require you to replace Notion, Confluence, or your existing knowledge base. It works on top of them, combining that content with release notes and past ticket resolutions to build support ready SOPs.\n\nYour existing tools can remain the source of truth for product documentation, while ify becomes the operational knowledge layer for support continuously turning scattered information into reliable, actionable answers." }, { "comment_id": "5814664", "product_id": "ify-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@rramesh25 Thanks Ramesh\n\nThank you! And yes — spot on. To your question - the knowledge base pulls from past resolutions too, not just docs and release notes, so it's not starting from scratch. That's the part we focused on most, since that's usually where support AI falls down. Appreciate the sharp question and thanks once again" }, { "comment_id": "5814299", "product_id": "ify-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "Hey everyone! 👋\n\nSarnith here, CTO & Co-founder at @ify.\n\nAdding a quick note on the technical side of why we built ify this way:\n\nWhen we set out to build this, one thing became clear very quickly:\n\nAI is only as good as the context behind it — and support documentation is almost never perfect.\n\nA lot of a team’s real tribal knowledge doesn’t live in pristine docs. It’s buried inside resolved tickets, Slack threads, release notes, and agent workarounds.\n\nInstead of forcing support teams to clean up or rewrite their documentation before they can use AI, we built ify to continuously map, absorb, and turn that scattered historical context into usable SOPs.\n\nThe goal is for the AI to understand not just what the documentation says, but how the support team actually solves problems.\n\nI’d love to hear from the technical and support folks here:\n\nWhat’s the trickiest support query or workflow you’d still be hesitant to hand off to an AI agent today?" }, { "comment_id": "5814526", "product_id": "ify-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@hamsapriya_veluswamy Definitely “Actions.” Customers kept telling us, “An ideal response is good but can it actually fix the issue?” So we connected ify to hundreds of apps, letting it handle tasks like refunds, subscription changes, and account updates. The surprise was seeing where support ends and operations begin. Customers started using ify to focus on managing the required tools and actions, not just resolve queries." }, { "comment_id": "5816875", "product_id": "ify-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@zhangchen Really good point and this is exactly how we have done. Ify is priced per resolution, not per seat. Once AI is doing the resolving, seats stop being a meaningful proxy for value, like you said. Appreciate you laying out the logic so clearly." }, { "comment_id": "5815091", "product_id": "ify-2", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@storcube Appreciate that, thank you! You're right, the chat widget's the easy part, the real work is turning existing docs and past tickets into something usable. Glad that came through. Thanks for the support!" }, { "comment_id": "5793023", "product_id": "lore-machine", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "Hey Product Hunt 🖖\n\nI'm Thobes, founder of Lore Machine. I spent 17 years at VICE, where I founded Motherboard and ran digital publishing.\n\nLore Machine is Substack for World Builders. Build a story World with art, video and sound, serialize it, and get paid...no studio required.\n\nAnd you bet there's a backstory:\n\nAfter leaving VICE, I wrote a series of viral articles about an audio technology that can purportedly break your consciousness out of your body. It's a whole thing. The stories got optioned for a documentary adaptation. The problem was there was no video footage, and animation unit costs were unaffordable. The project got shelved. I was seeing the same roadblock all over LA. Amazing screenplays collecting dust because stories couldn't jump the gap into the visual realm.\n\nSo in 2022 - as diffusion models were getting usable - we built the first version of Lore Machine for screenwriters, turning scripts into storyboards.\n\nThen - through no design of our own - South Korean creators started using Lore Machine to make serialized manga with recurring characters. So we stopped being a storyboarding tool and invented the LORE: text, art, video, sound and reader choice in one scrollable story object. It's basically an animated graphic novel you can play! Creators serialize LOREs inside a World with a shared cast, canon and narrative physics.\n\nToday we're launching World Pass. Creators charge $5/month for their World, keep 90% of the revenue and own their IP outright. We just launched the first World Pass with Archive In Between and Marvel writer B. Earl. The teaser has already racked up 600k views here. The World is here.\n\nTikTok, Instagram and YouTube taught a generation to love lore, then gave them nowhere to keep it. No canon, no persistent cast, no episode one, no way to charge for a World. Creators have been building universes inside platforms designed to splinter them. Now they have a home.\n\nEvery AI tool right now is optimized for making commodity content fast. We're betting on craftsmanship instead.\n\nI'll be here all day. If you have a story World you've always wanted to bring to life, Let's get INTO it.\n\nProduct Hunt launch offer: 200 free visualization tokens if you sign up during our launch week!\n\nDive into Lore Machine here.\n\nHuge thanks to Chris Messina for huntermanship 🙏" }, { "comment_id": "5816194", "product_id": "lore-machine", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@chrismessina Thanks Chris. Our very first tagline back in the day was \"Get Lost.\" I loved it, but it proved...confusing. The tv series invocation though - gold." }, { "comment_id": "5633298", "product_id": "screenify-studio", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "Hey Product Hunt 👋\n\nI'm Brjan — solo founder shipping in public from Ho Chi Minh City đŸ‡»đŸ‡ł.\n\nThe honest reason I built Screenify Studio: my demos kept looking like shit. I'd spend weeks building features, then watch people barely notice them because my demo videos hid everything behind flat, static recordings.\n\nSo I built the tool I wanted. Record on your Mac, drop it into a photoreal 3D MacBook, iPhone, or iPad — or stage multiple devices together in one cinematic ecosystem shot — pick a cinematic camera motion, and ship a finished MP4. Or point it at any URL and let an AI drive a real browser to record the whole demo for you, then add the cinematic touches (3D moves, spotlights, callouts).\n\nPrefer full control? There's a deep editor with manual zoom keyframes. Live in the terminal? Screenify now speaks MCP — connect it once and Claude, Claude Code, or Cursor can record, style, and hand you the finished video — plus a JSON-speaking CLI if you'd rather script it yourself.\n\nEverything runs on-device on Apple Silicon — nothing uploaded. Free to start; you only upgrade when you genuinely need higher-quality exports and the more advanced features.\n\nWould love your feedback — what do you use for product demos today? Happy to nerd out about the 3D pipeline, the MCP server, or the AI web-record under the hood." }, { "comment_id": "5814326", "product_id": "screenify-studio", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@heyitsirenechan Thanks so much, Irene! 🙏 That \"still a bit of editing involved\" is the exact itch I built Screenify for — it auto-zooms, cleans up the cursor, and can even record the whole demo for you, so most of the manual editing just disappears. Since you're coming from Clueso, I'd love to just hand you a Pro code on me — DM me and it's yours, no strings, I only want your honest take (even the harsh bits). Around all day if you hit anything rough!" }, { "comment_id": "5815290", "product_id": "screenify-studio", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@yelyzaveta_kibets Straight answer: browser only, for now.\n\n\"screenify web record\" drives a real Chromium window through Playwright — either a\ndeterministic action script, or an agent loop that reads the page and decides one step\nat a time. Re-running that same script after a UI change is exactly the case it was\nbuilt for, so for web apps you're describing the thing it does.\n\nA native Mac app window can be recorded — ScreenCaptureKit, window-scoped, drivable\nfrom the CLI — but nothing inside Screenify clicks through its UI. That's honest: no\nnative automation today.\n\nThe half that might still be worth money to you: only the driving is missing. If you\nalready have something moving the app — AppleScript, XCUITest, cliclick — the CLI can\nrecord that window, and the zoom is synthesised from the real cursor and clicks, so you\nstill skip the hand-editing. You bring the driver, we take it from capture to export.\n\nNative UI driving is the obvious next step. If you tell me which app and which flows go\nstale most often, that's the kind of thing that decides what I build next." }, { "comment_id": "5815655", "product_id": "screenify-studio", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@yelyzaveta_kibets Region detection is safe — it never looks at travel. Smart Zoom keys off discrete events, clicks first, typing second. A teleport still lands, still clicks, so the regions come out the same.\n\nThe mechanism is the reassuring part: on macOS the click event carries no coordinates at all, so the position is taken from the nearest cursor sample in time, matched in both directions, sampled about every 10ms. A jump still produces a sample at the destination inside that window. The path between two points was never an input.\n\nYour instinct about tracking is the right instinct, but it points at a mode you won't be in. Auto-zoom is static by default — it parks on the click point and holds, and follow-cursor is something you turn on deliberately. Even with it on, two things damp a jump rather than amplify it: the camera doesn't pan at all while the cursor sits inside the middle of the frame, and past a speed threshold it holds its current framing instead of chasing. A teleport is the fastest possible flick, so it lands in both of those, not outside them.\n\nThe one real artifact is cosmetic: the cursor sprite itself will jump, because that's genuine recorded motion, and I won't pretend it reads like hand-moved travel. The only correctness edge I'd guard is a teleport and a click firing inside the same ~10ms with nothing sampled at the destination yet — a 50ms beat between move and click removes that entirely, and cliclick can chain intermediate points if you'd rather have real travel in frame.\n\nWorth trying on whichever flow goes stale most often — that's a smaller test than it sounds, since you already have the AppleScript half. If a zoom lands somewhere you didn't click, tell me and I'll chase it down." }, { "comment_id": "5815703", "product_id": "screenify-studio", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@galdayan Both, split at the right seam: you do the login once by hand, and the agent never sees it.\n\nscreenify web login --auth acme opens a browser and waits. You sign in however that site demands — password, 2FA, SSO, a captcha, whatever it throws — then press Enter. The session is saved into a named browser profile.\n\nFrom then on screenify web record --auth acme starts non-interactively, already inside. The agent picks up in the actual product, which is where you wanted it. It never touches your credentials, and there's nowhere to put them even if you wanted to.\n\nThe honest limit: sessions expire. When one does, you re-run web login — a few seconds, not a rebuild. Profiles are per name, so a staging account and a demo account are two names, not two setups.\n\nRecording behind a login was the first thing I wired after basic capture worked, for exactly the reason you're pointing at: almost nothing interesting happens on the logged-out page." }, { "comment_id": "5816745", "product_id": "screenify-studio", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@galdayan Honest answer: no, I haven't hit it — but my sample is small enough that I'd treat that as \"not tested much\" rather than \"doesn't happen.\"\n\nWhat I can tell you is mechanical rather than anecdotal. --auth isn't a saved cookie, it's a full persistent browser profile. So the \"trust this device for 30 days\" flag that push-2FA hands out after the first approval lives in that profile and survives. A session expiring and a 2FA challenge firing are two different events — the first is common and costs you a password, the second is the one that costs you a human, and device trust is what keeps them apart.\n\nThe case that genuinely breaks is a policy that re-challenges every session regardless of device trust. Nothing in a recording tool fixes that. It's an account problem — a dedicated demo account on TOTP instead of push, which is what I'd want anyway, since a demo account shouldn't be tied to one person's phone.\n\nIf you run it against something with push enforced and it does re-prompt, tell me. You're closer to that setup than I am, and I'd rather hear it from you than find out later." }, { "comment_id": "5805510", "product_id": "playcall", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "Hey Product Hunt 👋\n\n\nI've spent the last 5 years building GTM systems at AI companies like Sieve (YC W22), Ragie.ai, and Aviator (YC S21).\n\n\nMost call intelligence tools are good at summarizing what happened, but weak at judging whether a rep actually followed the team's sales motion based on the buyer context/stage.\n\n\nAnd context matters. A discovery call with a 50-person Series A startup buying a tool should not be scored the same way as a Fortune 500 vendor evaluation.\n\n\nHere's the tell: the founders I know don't even trust Gong. They rawdog their team's calls themselves, rewatching every AE call, because $30K+/year of call intelligence still can't answer their actual question: did my rep say the right thing for this specific buyer?\n\n\nSo I built Playcall.\n\n\nWhat Playcall does differently:\n\nBuyer-Aware Scoring: Company stage, contact role, and deal context dynamically shape every scorecard.\n\nYour Methodology, Not Ours: Score against MEDDPICC, BANT, SPIN, or your custom playbook. No framework? Upload your playbook and Playcall generates the rubric for you.\n\nOutcome-Tied Scoring: Every score links to deal stage, outcome, and pipeline impact, so managers can see which behaviors actually move deals.\n\nCoaching Drills, Not Just Feedback: Every score comes with a specific, actionable drill for the rep to run next.\n\nPlug & Play with any LLM: Use your favorite model (Claude, GPT, Gemini, or 15+ others). No vendor lock-in.\n\nSelf-Hostable: Open source. Deploy to your own infrastructure. Data stays with you. You can run it for under $50/month, with LLM and enrichment usage as the main variable costs.\n\nThe goal is simple: help reps improve against the playbook they're expected to follow, help managers see which behaviors move deals, and spot objection patterns before they compound.\n\n\nLive demo: playcall.dphenomenal.com\nRepo: github.com/Dphenomenal101/playcall\n\n\nWould love feedback from founders, GTM leaders, RevOps folks, and sales managers.\n\n\nTwo questions I'd love answers to:\n\nWhat's the biggest gap you've seen in existing call coaching/intelligence tools?\n\nFor automatic call ingestion, would you rather connect an existing notetaker like Granola, Fathom, or Fireflies or have Playcall ship its own Zoom/Meet/Teams bot?" }, { "comment_id": "5805862", "product_id": "easyswitch", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "Hi Product Hunt 👋 I’m Sharif, the solo founder behind EasySwitch.\n\nI built it because my desk had three computers and only one keyboard I actually liked.\n\nI wanted one simple setup: move my mouse between computers, copy/paste anything, transfer files, and use one computer as a second display.\n\nSo I built it.\n\nEasySwitch is:\n\n* One keyboard & mouse across Mac, Windows, and Linux\n* Universal copy/paste + file transfer\n* Use another computer as a virtual second monitor\n* End-to-end encrypted, LAN-only, no account or cloud\n* Wayland support on Linux\n* Native Rust — no Electron\n\nIt’s free for two computers. A one-time $49 license unlocks more machines and unlimited file transfers.\n\nI’ve been building this solo for a while, and I know there are still rough edges.\n\nSo if you have a Mac + Windows/Linux setup,\ntell me what breaks, what feels weird, or what you wish it could do.\n\nI’ll be here all day. ❀\nShow more" }, { "comment_id": "5815656", "product_id": "loupekit", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@yosun_negi Thanks, that was exactly the reasoning. A count with no address makes you go hunting, and half the time you end up arguing with a number you can't see. The finding carries the elements the collector saw while it was counting, and the total stays the rule's own count rather than the length of that sample list — otherwise six highlighted elements under a finding that fired on four hundred would read as \"fix six.\"" }, { "comment_id": "5815653", "product_id": "loupekit", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@yelyzaveta_kibets Thanks for the comment\n\nScoring is single-page. Nothing compares one URL against another and there's no crawl, so a family of near-identical pages never registers as a family. Your MKV-to-MP4 page is judged on what's inside it alone.\n\nWithin a page, the repetition rules have deliberately high floors. Repeated markup blocks doesn't start counting until 4, and long identical sibling rows not until 8, because lists and card grids are repetition by design. The sibling rule goes further and refuses to claim copy-paste over a loop — a rendered DOM genuinely cannot tell those apart, so the finding says \"this run is long, go look at the source\" instead of announcing a verdict it has no evidence for.\n\nThe one that could plausibly fire on a converter page is thin copy: 8 or more text blocks averaging under about 14 words each. That isn't a templating penalty, it's the wireframe-that-shipped shape, and it's the same thing a normal SEO audit would flag. If each format page carries real copy, it reads clean.\n\nEvery finding also names its own number and points at the elements it counted, so you can check what it actually hit rather than trust a colour." }, { "comment_id": "5815843", "product_id": "loupekit", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@yelyzaveta_kibets Thanks\n\nSitewide sameness is the real question and one tab genuinely cannot answer it. I'd rather say that than stretch what the score covers.\n\nThe constraint is deliberate: the extension holds activeTab and nothing else, and ships with empty host permissions. It reads a page only when you ask, and has no ability to reach a URL you aren't looking at. A crawler needs either broad host access or a server-side fetcher, and the first is a permission I don't want to ask for.\n\nThe shape that fits is the one that stays inside that: pages you actually open get audited and kept, and a compare view diffs the reports — heading sets, block structure, copy volume per format page. Sameness across the twelve pages you care about, without anything crawling the other three hundred. Less than Screaming Frog, honest about which pages it saw.\n\nA real crawl is a different product and belongs on the server, not in a tab. Worth doing, but not by quietly widening what the extension can reach." }, { "comment_id": "5814996", "product_id": "loupekit", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@asadmalik901 You're right, and Tailwind is the exact case that breaks it: utility density is evidence of a framework, not of an author. Sloppiness correlates with lazy prompting, and correlation is not what a number presented as a verdict implies.\n\nWhat I'd push back on is only the framing of the score as a classifier. Every finding names the signal that produced it and the rule behind it, and the Findings and Signals views exist so the score can be taken apart rather than trusted — that's the same \"walk me to the thing\" property you're crediting the markup findings with. Where you're right is the aggregate: one number on top is the only output in that tab nobody can falsify, and it's doing the most rhetorical work.\n\nTwo changes I'd rather make than defend it. A framework-aware baseline, so a page that fingerprints as Tailwind isn't charged for utility class density. And demoting the single number, because the defensible artefact is the list underneath it.\n\nWhich signals would you drop first? If they're the ones I suspect, that's a short list and a good afternoon's work." }, { "comment_id": "5815848", "product_id": "loupekit", "selection_reason": "Maker response with implementation, pricing, integration boundary, product differentiation, or operational constraint.", "body": "@asadmalik901 Sure, understand.\n\nYou picked the loudest one correctly, and the budget numbers make it worse than you'd guess. Utility class density is 35 points, the largest single rule in the engine, and the \"one div carrying forty classes\" rule is another 10. The whole CSS category is 55. So a Tailwind page starts the CSS half of its score down 45 points before anything about authorship has been measured. That isn't a signal with a weighting problem, it's a framework detector wearing a verdict.\n\nComment style and emoji in headings aren't in there, and can't be: the collector reads the rendered DOM, so source comments never reach it. The nearest thing to what you're describing is em dash density at 14 points, and I think you'd file it the same way. It's a habit, and a writer with a taste for dashes is charged for someone else's tell.\n\nWhat survives your test is smaller than the current scoring implies. Builder globals left in the bundle — a v0 or Lovable object still present at runtime — is direct evidence with no innocent explanation, and it's worth 20 against Tailwind's 35. That ratio is backwards.\n\nSo: utility rules zeroed when the stack fingerprint says Tailwind (the Tech tab already detects it, the audit just doesn't ask), em dash density demoted, and the weight moved onto the signals that can't be explained by a framework or a house style. That leaves a shorter list and a smaller number, which is the correct outcome." } ] }