... been working on something called Sochely, and I d love to get some real feedback from this community. The idea came from a simple frustration event discovery is still broken. You have platforms like Eventbrite and Ticketmaster, but they only show some events. A lot of great events never get seen because they re scattered across different platforms or hard to promote. So we built Sochely to fix that. It s a platform where anyone can create events completely free ... ... give them built-in tools to actually promote those events. At the same time, we re aggregating events from everywhere so users can discover

... slightly uncomfortable question: Are we still doing product discovery - or mostly validating decisions we already made? As teams grow, processes get heavier, but it sometimes feels like real exploration gets lost. We ve been thinking about how Athena could push teams back toward actual discovery

... measure delivery. We measure usage. We measure outcomes. But what do we measure for good discovery ? Fewer failed features? Faster decisions? Better alignment? As we build Athena, defining this has been surprisingly hard. So curious - what does good product discovery

... Domain Packs: Teach DecisionBox Your Industry in Minutes Create, edit, import, and share AI discovery templates entirely from the dashboard. Cross-posting from our blog for anyone who hasn't seen it. Original post: https://decisionbox.io/blog/doma... TL;DR Domain packs are how DecisionBox knows what to look for in your data. From the dashboard, you can create a domain pack, edit it with a built-in markdown editor, export it as JSON to share with others, or import ... ... someone else made. No restarts, no deploys just save and run a discovery

... been looking a lot at how product discovery changes as teams grow. At small scale it s fast and intuitive, but at larger scale it often becomes fragmented, slow, or disconnected from the actual system. From your experience-what s the first thing that breaks in discovery

... took hours. That s why I built ProblemPulse AI. --- **What it does:** It analyzes Reddit discussions and app reviews to: * Identify real user pain points * Detect patterns across conversations * Suggest actionable product directions --- **New Feature (just added): Keyword-based discovery + user insights** Now you can: * Track specific keywords in Reddit discussions * Discover

... building an AI-first way to search and discover flights focused on simplifying decisions, not overwhelming you with options. But here s the truth: This is still early. Instead of waiting for a perfect launch, we re opening access to a small group of early users who want to help shape how this product evolves . If you ve ever: Spent hours comparing flights across tabs Felt unsure if you re actually getting the best option Wanted a smarter, more intuitive ... ... definitely the direction: Short term gives better interpretation of what users ask for Longer term gives learning from patterns, repeat behavior, and preferences over time One thing we re actively exploring is: How much automation users actually want vs

... took hours. That s why I built ProblemPulse AI. --- **What it does:** It analyzes Reddit discussions and app reviews to: * Identify real user pain points * Detect patterns across conversations * Suggest actionable product directions --- **New Feature (just added): Keyword-based discovery + user insights** Now you can: * Track specific keywords in Reddit discussions * Discover

... later than we should have. For me, it was a simple log monitoring tool that saved hours of debugging at 2 am. What's yours? Could be for design, code, analytics, user research, or even project management. Trying to discover some hidden gems the community actually uses (not just the popular ones). Comment from Wasil Abdal(@wasil_abdal): @alpertayfurr  Sentry at 2 am is painful but real. PostHog keeps popping up. Does it replace Mixpanel + FullStory cleanly? Comment from ... ... grunt work" that let us stay in the creative flow much longer. Once you find your hidden gem, you ll honestly wonder how you ever survived the manual struggle! Comment from Ruxandra Mazilu(@ruxandra_mazilu): Ohh, definitely @Clueso ! Discovered

... leave with something that didn't feel like 'me', and finding the perfect layering perfumes would consume even more time and not sure whether they compliment each other or not. we decided to build a tool that sloves the discovery problem. A few things we focused on to make scent discovery

... requests Prioritize now ROSE (on-site optimization) 45% 31% 9 requests Keep, enhance later Social/Community Engine 14% 4% 19 requests Delay, needs more validation RASE (app store tracking) 11% 3% 22 requests Delay, low retention signal Ranklink (backlink discovery) 9% 2% 24 requests Delay, not sticky yet The features people asked for most (RASE, Ranklink, Social Engine) were used by less than 15% of users. The features they barely mentioned (Workflow Engine, RAIVE, RCGE) had adoption rates above 68%. What ... ... every day? We tracked the top 10% of accounts by engagement. Their most-used feature was the Workflow Engine. Not because they requested it. Because it saved them time. They built automation for content publishing, citation alerts, and competitor

... every single day. Yet when you ask developers where they can properly showcase their work to real users, most of them struggle to name more than one or two places. When you ask regular users where they go to discover quality apps beyond the top charts, the answer is usually nowhere. That gap has been growing for years and nobody was filling it. At AVALW, we experienced this problem directly. When we launched our own applications, we went looking ... ... modern platform where we could present our work to real people. What we found were a handful of directories that were built over a decade ago, designed for a different era of software distribution. The experience felt outdated, the discovery

... Planning a wedding in Pakistan sounds exciting until you actually start looking for a venue. There s no single place to discover venues. No transparent pricing. No easy comparison. And most decisions still depend on WhatsApp forwards, phone calls, and personal references. We realized something strange: People can book flights, hotels, and taxis online in seconds. But booking a wedding venue one of the biggest life events is still offline chaos. Without WedX, couples face: Endless calls to venues Hidden ... ... options based on personal networks Time wasted visiting places physically And venues face: Empty dates Poor online visibility Dependence on agents No structured demand generation The market isn t small it s simply unorganized. Currently in Pakistan, wedding venue discovery

... promote our Product Hunt launch of Vibe Check today, we are offering free evaluations. We are looking for Vibe Coded prototypes to promote and discover their time to value. To take part, just share the link and what journey you'd like to test and we'll provide a link and report on your UX performance analytics. Here's an example for Vibe Tickets A thinking simulation like this and a UX performance report like this . Share your early vibes ... ... lets discover

... building TicketBridge, a workflow for early-stage B2B partner discovery. The problem I m trying to solve: a lot of partnership outreach fails because the ask is vague, the partner type is unclear, or too much context gets revealed too early. The current workflow is: describe what you have describe what you need describe what you can exchange define what should stay private get a more structured request instead of messy cold outreach only reveal stronger details if there ... ... real reason to continue Use cases I m targeting: co-marketing partners channel / referral partners sponsor or event partners resource exchange / collaboration discovery

... just exposure, but the degree to which AI treats your brand as a credible source . Share of Voice (SOV): Represents your brand s voice share within AI narratives the probability that AI mentions your brand rather than a competitor when answering a topic-related question. Sentiment: Captures the emotional tone of AI mentions positive, neutral, or negative showing how AI portrays your brand. Together, these four metrics answer the two most fundamental GEO questions: How frequently does AI mention ... ... brand? and In what tone and context is the brand represented? 1.2 Trends and Competitor

... Dataset Parameter Value Launches analyzed 1,000 Time period 2025 2026 Platforms tracked ChatGPT, Perplexity, Gemini Metrics measured AI citations, share of voice, content structure, launch day performance Sample Top 500 + random 500 from leaderboard Finding #1: The Discovery Gap Is Real Academic research confirms what we found: when users search for products by name, LLMs recognize them almost perfectly 99.4% for ChatGPT, 94.3% for Perplexity . But when users ask discovery

... acquirers? proof of market validation in a single day a real user base with documented reactions social proof that's already indexed and visible a community that already knows the product exists Product Hunt is often seen as a discovery platform for users. But is it also where serious buyers are quietly watching? So I'm curious: Have you ever acquired or seriously considered acquiring a product you first discovered

... what I learned. What I Built The product was solid. Nothing revolutionary, but genuinely useful: Solved a real problem 4.8 stars on reviews 20% MoM growth Customers who found us, loved us But "found us" was the problem. Organic discovery had flatlined. Referrals carried us. New users from search? Zero. Then someone asked ChatGPT about our category. Screenshotted it. Sent it to me. We weren't there. Not #1. Not #2. Not #10. Nowhere. What I Thought Mattered (It Didn ... ... project management tool for remote design teams. Here's exactly how we work." Feature lists Problem-solution paragraphs Vague benefits Specific outcomes Lesson #2: AI Loves Comparisons Even If You Lose This one hurt. I avoided mentioning competitors

... Hello everyone, My name is Brian, and I m currently building Happening, a platform designed to help people discover events happening around them and share experiences with others. The idea came from a simple problem: many great events happen around us, but people often don t hear about them in time or they get buried in social media feeds. So I started building a space focused purely on events and real-life experiences - where people can easily see what ... ... Also curious to hear from other founders here - what was the hardest part of launching your first product? Comment from Andrei Tudor(@andreitudor14): The problem is real; great events do get buried! Curious how you're thinking about the discovery

... Problem I m an engineer with a library of 5,000+ songs. I realized the best music I discover doesn t come from Spotify algorithms it comes from friends, DMs, and random Reddit comments. The problem is those recommendations get buried and lost. The Solution: I built shoutout to turn these hidden recommendations into a high-signal, live feed. It's a universal archive for your 'Social Capital' in music. Key Features: Universal Credit: Acknowledge the ' Tastemakers ' in your life ... ... shoutouts to the person who showed you your new favorite song. 24h Live Feed: Drop a Spotify/YouTube link or just the song and artist combo . It stays in the feed for 24 hours like a story (IG style), so discoveries

... founder told me: "We added a FAQ section with real customer questions. Within 3 weeks, ChatGPT started quoting us verbatim. We'd been invisible for 2 years." Thing #2: You Must Build Comparison Bridges The mistake: Hoping people will discover you in a vacuum. The reality: Every AI answer about your category includes comparisons. Always. When someone asks "best CRM for agencies," AI doesn't list one tool. It lists 3-5. And it compares them. The data: Content Type ... ... Citation Rate Pages with comparison tables +470% vs

... many found they were invisible. But here's what scared me more: Of those who WERE visible, 43% had incorrect information in AI answers. Not "suboptimal." Not "could be better." Wrong. Outdated pricing. Missing features. Wrong founder bios. Competitors credited for your work. And the average error sticks around for 4 6 months . Today, I'm sharing the full dataset: 1,000+ SaaS products, 75,000+ AI answers, and the hard truth about what's being said about you when ... ... lost a 200k deal because ChatGPT said we didn't have SOC2. We've had it for 18 months. The AI learned from an old Reddit thread and never updated." The Cost of Errors We analyzed 50 brands that discovered

... Real examples from our data: Example A: SaaS pricing A B2B company updated their pricing in January. In March, ChatGPT was still citing their 2024 prices. Users thought they were hiding costs. Three enterprise deals fell through before they discovered the issue. Example B: Founder background A fintech founder's Wikipedia was updated to remove an old affiliation. Perplexity still cites the old version. Investors researching the founder see incorrect information. No way to flag it. Example C: Feature comparison ... ... answer may still reflect 2023 reality even if you fixed it. The problem compounds: AI learns from outdated sources Users trust AI answers as "truth" You can't see it happening (no alert, no dashboard) By the time you discover

... Build a CV. Apply for jobs. Wait for a response.   But the world has changed.   AI agents are now searching the internet, scanning profiles, analysing skills and recommending candidates before a human recruiter even opens a spreadsheet. Discovery is no longer manual. It is algorithmic.   The question is simple. Will you be visible when the machines start looking?   We believe the future of work will be shaped by collaboration between humans and AI agents. Humans will ... ... focus on creativity, taste, intuition and niche judgement. AI agents will handle the heavy lifting of discovery