... sparked an interesting thought experiment: how likely is it that we ll see AGI (AI that thinks and learns like a human) within the next five years? The report highlights a fascinating divergence: the view from money vs. the view from science. Money : the probability inferred from trillions poured into data centers, Nvidia chips, and servers. Investors seem to be betting that AGI is inevitable. Science : the probability inferred from research papers and AI development models. Experts are far more ... ... might be ahead of reality. Expect volatility, overpromised outcomes, and valuable lessons along the way. Meanwhile, AI continues reshaping work, attention, and human behavior. I d love to hear the community s perspective: Are you seeing this money vs

... still alien to them. After digging deep, I realized low adoption probably isn t because agents suck. I ve tried a lot of open-source agents that are actually useful. The real issue is understanding, delivery, and the reliability vs. complexity paradox. First, the vast majority of agentic apps require you to deploy or set things up, of course including preparing your API keys. With requirements like that, you can basically say bye-bye to normal users. Sure ... ... manifest. Run a few CLI commands. Done in ~10 mins. Your agent is live and interactive. Even if you don t have an agent, feel free to browse and try out the creative apps others have built. You might unexpectedly

... While testing Alpie Core beyond benchmarks, we noticed something unexpected. On tasks like step-by-step reasoning, reflective questions, and simple planning ( help me unwind after work , break this problem down calmly ), the model tends to stay unusually structured and neutral. Less fluff, less bias, more explicit reasoning. It made us wonder if training and serving entirely at low precision changes how a model reasons, not just how fast it runs. Sometimes the chain of thought itself is something ... ... understand the reasoning behind the final answer. Curious if others have seen this: Do quantized models fail or reason differently than FP16/FP32? Have you noticed differences in bias, verbosity, or clarity? Any workloads where low-precision models behave unexpectedly

... most of our time talking directly to users and potential customers, trying to understand how social media operations actually work in practice what s broken, what s tedious, and what truly needs automation. From marketing teams to influencers an unexpected signal Digitalog Social was initially designed for in-house marketing teams and marketing agencies . But a few weeks in, something unexpected

... actually tracks : renewal dates payment terms auto-renew clauses notice periods risky legal terms expiration windows Everything ends up buried in PDFs or email threads until something important is missed. And missing a renewal or deadline = lost revenue or unexpected penalties. The solution I built: ContractSight Upload any contract (PDF/DOCX) In seconds, the AI extracts: Key clauses Payment terms Deliverables Expiry & renewal dates Auto-renew flags Notice periods Legal risk indicators Parties involved You also get: A renewals dashboard ... ... Track what s expiring, needs action, or is auto-renewing. Assign owners (Useful for agencies and teams) Internal notes, comments, action items All saved per contract. Document version comparison Upload v1 vs

... meant: We couldn t update our website None of our apps could be updated Everything broke at the worst possible time So we made a fast decision to move everything to GitLab . Not ideal, but that s startup life: unexpected disruptions at the worst moments. How we got featured (another question everyone kept asking) We didn t use any tricks. We simply followed the PH team s own guidelines: Clean, simple graphics A thoughtful Maker comment A short, friendly intro ... ... through Linkedin, X...)? Was it right after submitting your project or did you wait until closer to launch day to build momentum? Thank you for sharing. Comment from Mark Frain(@mark_nosho): @chilarai  Thank you, It's really unexpected

... page. Step 2: AI Expands and Drafts Hand your outline to AI. Within seconds, you'll have a complete first draft. This initial draft is usually surprisingly good: Detailed outlines Results closer to your vision Rough outlines Unexpected creative directions you hadn't considered Step 3: You Refine to Perfection Now comes your editorial control: Edit the AI-generated content directly Adjust sections that don't feel right Add your personal voice and style Ask AI to refine specific paragraphs ... ... help you develop them. Better Writing Quality AI helps with structure, clarity, and polish while you focus on core ideas and messaging. More Creative Freedom Explore different angles and approaches quickly, letting AI handle the execution. Vibe Writing vs

... powerful it is to be different from your cofounder, yet highly complementary! (You'll notice that in this interview)  . Let me know what you think about this interview, and if you've also had some unexpected learnings through your journey! Comment from Sanskar Yadav(@sanskarix): That Slack lockout story is classic startup rush - things escalate quickly when you re building something people actually want. Big fan of teams that embrace real, honest growth (even the wild surprises) Comment from ... ... Uttam Kumar(@deleted-9029454): The interview was brilliant! Loved hearing how TikTok unexpectedly

... perfectly put it under my post: it s like having a crystal ball for your data, but way, way more reliable. The Scenario Node is a game-changer for Datastripes, created to help you navigate a world full of unexpected turns and overcome any obstacle. It lets you test a ton of possible futures before they even happen! What you can do: Seriously stress-test your business! Automatically train a powerful LSTM model with your data. Unlike linear models ... ... scenarios. It was a huge request from you, the Datastripes community here on Product Hunt. Here some examples: Simulate a sales collapse by applying a multiplier of 0.5. It's perfect for quickly understanding the impact of a new competitor

... seen (or used) to grab attention? Examples that come to mind: Sending a pizza to every journalist in your industry with a QR code on the box leading to your launch page. Renting a billboard in front of your competitor s HQ with a cheeky message . Openly challenging an industry leader to a product duel in public . Your turn: what s the boldest, craziest, or most unexpected

... this your first product? If not, what else have you built, or are currently working on? This is my second product. I realized the need to build YoinkUI while building my first product actually. It was a competitor marketing analysis tool, but I abandoned the project. What s your secret weapon or go-to when you get stuck while building? Going for a walk or taking a shower always helps me clear my mind and oftentimes the solution comes ... ... hindsight I wish I had set up a teaser page for a few days, and promoted my launch on my site and told some friends. That's exactly what I recommend people do. What's the most surprising or unexpected

... everyone, I m Joe software developer by trade, softball dad by title, and now, unexpectedly, an app creator. After too many weekends spent trying to analyze my daughter s pitching and hitting with nothing but my phone camera and wild hand gestures, I decided to build the tool I couldn t find: PitchGrid a free app that lets you sync and compare sports videos side-by-side. I use it constantly sometimes to break down a swing, sometimes just ...

... draft surprised - surprisingly automated: Turned technical jargon into visual flowcharts Matched tech blue gradient template But business scenario pages had duplicate content Iterative tweaking (6 minutes) Optimize with built-in instructions: "Compress scenario pages to 3 typical examples, add competitor comparison dimension" Replaced 5 redundant pages after second generation Visualization of time-saving effects Traditional operation: estimated 6 hours (2h for logic construction + 3h for design + 1h for modification) EasySlides actual test: 12 minutes core framework + 35 minutes detail optimization ... ... turn it off manually. Personal Evaluation Suitable for: sudden demand/logical framework construction/technical translation Limitations: need to manually adjust the visual details, complex data need to be double-checked. Last Soul Question What tools are people using to cope with unexpected

... knowledge in the projects that didn't work out, especially in the rapidly evolving world of AI agents. I'm currently in the trenches building an AI agent, and while the potential is exciting, the path is riddled with unexpected challenges . I'm sure many of you have been here before. I'm not looking for success stories today. Instead, I want to create a space for us to share the nitty-gritty of our "failed" attempts at building ... ... experiences to avoid similar pitfalls. Specifically, I'd love to hear about: Misjudged User Needs: Did you build an agent that solved a problem nobody actually had? Technical Black Holes: What unforeseen technical hurdles completely derailed your project? (e.g., unexpected

... anyone here tried this model? Does open-sourcing drive deeper trust and usage, or just more passive browsing? How do you balance giving enough in the free tier while preserving value in the paid ones? Are there any unexpected downsides we should watch for? We re not trying to monetize everyone just want to make sure the value and motivation to upgrade are aligned. Any lessons from others who ve done this (or considered it) would be hugely appreciated ... ... features. Also, once it's open-source, your GitHub might slowly become your support inbox something to be prepared for Would we do it again? Yes but only if it s really clear which features are helpful and free vs

... Product Hunt community! I m currently working on a product designed for users around the world, and as exciting as it sounds, building something truly global comes with a lot of unexpected challenges. Here are a few that I ve encountered so far: 1.Localization Translating text is just the beginning. Cultural context, tone, and even color choices can affect how users perceive your product. 2.AI prefers English One specific issue I ve noticed: even when users interact in their native ... ... payment regulations, and data hosting rules vary greatly between countries. I m curious to hear from others building global or multilingual AI products: How do you handle language fallback or preference issues with AI? What s been your biggest unexpected

... Tired of algorithm-driven playlists? With RandomSong, you can break free from recommendation bubbles and discover hidden musical gems across 40+ genres and six decades (1960s to 2020s). Play RandomSong Now Ready to hear the unheard and expect the unexpected? Try RandomSong now and let us know what unique tracks you discover ...

... everyone! I'm thrilled to share RandomSong with you all your new gateway to unexpected music discovery! Tired of algorithms feeding you the same old tunes? Craving that spark of genuine music serendipity, where you stumble upon a track that instantly becomes a new favorite? That's exactly why we built RandomSong. RandomSong can help you "Hear the unheard. Expect the unexpected

... collaborative and productive environment. It offers participants the freedom to move around the meeting space (designed as various maps, some inspired by games and some based off of actual office blueprints). Nonilion is a distraction free google s meet alternative, with perplexity ai, multi participant screen share, interactive multi participant games, file sharing, custom characters and more. Nonilion is free to use for all the users and also offers a pro plan for meetings that required custom room names ... ... writers, video editors and front-end developers to focus and work in collaboration. Two or more groups talking over each other or sharing screens at the same time resulted in other groups to sit and just watch. As an alternative

... immediately confirm their direct ties to the product team itself. This isn't the first time a maker team has discovered I've hunted their product. Usually, the reaction is surprise and excitement especially if the product was unexpectedly featured! My immediate instinct in those cases is always to connect with the makers, add them to the launch page, and make sure they receive the spotlight and recognition. That's a core principle for me. Those past interactions have always ... ... excellent something good enough to attract a hunter's attention and achieve success organically. But the interaction left me feeling a bit disappointed and reflecting on the situation. Perhaps the true Product Hunt spirit should be about genuine sharing, unexpected

... live, but that s not why I m posting. I m more curious to hear from other devs and indie makers: Have you tried tools like v0.dev or similar AI-based builders? What were the gotchas or unexpected wins? Would you actually ship something production-ready this way? I still did a lot of work to stitch everything together, but it saved me a ton of time. I m super curious how others are approaching this - especially solo builders trying ... ... Making it easy for early developers to launch their own small e-commerce apps. I have been using Cursor lately, and it's context awareness is awesome, but I couldn't find some basic shortcuts that were available in VSCode

... What problem were you trying to solve when you built it? Has that evolved? Subscription Day began quite spontaneously. Initially, I created it just to solve a personal issue I kept forgetting about my own subscriptions until charges appeared unexpectedly. I shared it with friends, who encouraged me to post it on Reddit. The huge positive response convinced me this problem affects many others too. Most services don't remind users before charging, leading to frustration, especially with annual subscriptions ... ... advance, and thoughtfully writing the launch materials. My main advice is to leverage the numerous excellent guides available for launching on Product Hunt I'm surprised more makers don t utilize them. What's the most surprising or unexpected

... Curious what s the most unexpected way someone s used your product? Looking for fun, weird, or totally unintended use cases. Comment from Aaron O'Leary(@aaronoleary): @kevin_mcdonagh1  You know after reading this I immediately thought to myself "yeah i would do this" ahaha Comment from Ben(@moonlite_money): Abusing promotions Users would sign up and collect a promotion, then cancel their subscription and use the bonus we gave for signup. This took ... ... told us they used the app not just to track groceries but to prove to their partner that they were the more economical shopper Turns out graphs of spending and category breakdowns are now part of their domestic debates. Unexpected

... every tool has its hidden traps and secret advantages only daily users know about. I'd love your experience on these points: Which automation tool are you actually using right now, and why? What's best for newbies vs. advanced users? Have you discovered any hidden limitations or unexpected

... project, I sought to identify the problem I wanted to solve. With the Babel project (github*com/eonist/babel), I aimed to use AI to translate localization strings for iPhone apps. I needed to localize my app soon, and the only alternative was to pay $150+ to services like Localise*com. How hard could it be? Famous last words (But not this time. ) Identifying the Problem: - High Cost: Existing solutions like Localise*com are priced at $150+ per month. - Dependency on Third ... ... Parties: Relying on external providers can be risky they may increase prices, shut down, or change their services unexpectedly