... apps? To help solve this workflow headache for my own launches, I built elov8: it lets you publish once across LinkedIn, X, and Threads, while automatically generating a single "table of contents" page to aggregate all your live posts (similar to a Linktree, but specifically built for posts). If anyone wants to test it out while sharing their workflow, we launched on Product Hunt today: https://www.producthunt.com/prod... Curious to hear how others approach their social distribution stack during ...

... growing. None of it felt unnecessary in the moment each piece solved a real problem I noticed while testing. But looking back, the "simple tool" idea and the finished thing are pretty different. For those who've built something similar: did your project scope creep in a similar

... like with copywriting or design, product concepts are starting to feel homogeneous. It s as if we re all feeding the same prompts to ChatGPT or Claude, resulting in ideas that seem original at first glance, but are terribly similar once you look under the hood. So my question is:  i f building has become so easy, what makes the real difference? Building a loyal base of believers who stick with you regardless of clones? Out-shipping everyone else ... ... with updates and new features? Having the most polished , beautiful product that wins on pure vibes and perception? Creating an interface and UX so frictionless that similar

... limited testers. They gave us the first feedbacks for us to make the app better. After we didn't succeeded with a try on LinkedIn, where the feedback was nearly zero, we are on our way to find good alternatives. Hopefully Producthunt will help us and I'am pleased to help you, if you like. Maybe we will make the world of apps a little bit better. Is my first day on this page and we are very excited what ... ... built this. I actually wouldn't make payments mandatory, though. For some products, a free or early-access version can make more sense at launch. I d optimize for real usage and useful feedback first. I m taking a similar

... internal thumbnail resolution so they're sharper even before the CSS fix. Search won't leave you with a blank page anymore if your search returns zero results, it now shows the 3 next-closest items with their similarity scores so you can click directly to them instead of staring at nothing. Search results were showing the wrong scores the merge algorithm was accidentally overwriting the actual similarity

... backlinks are still one of the strongest signals Google uses to judge whether a page deserves to rank. For competitive commercial queries, they remain one of the clearest ways to separate two pages with similar content. But the math changed. In the age of AI search, backlinks influence visibility differently. They act on the retrieval layer the live search index that grounds AI answers rather than the model's frozen training weights. That split explains why studies measuring pure ChatGPT ... ... look good on a report. 2. Lost link tracking with impact scoring. When a link drops, you see it immediately. More importantly, you see what it cost you in visibility not just in rankings, but in AI citations. 3. Competitor

... median points needed to break the top 5 and top 10 on each day. Check the full report here: https://app.databox.com/shared/a... The short version: Saturday is the easiest day. Only 266 median points to crack top 5, vs 360 on Wednesday. That's a 35% harder climb on the worst day vs

... Problem Dropshippers and e-commerce sellers spend hours manually researching competitors checking their ads, estimating revenue, tracking SEO, and collecting winning creatives. It's time-consuming, fragmented, and takes away from actually growing their business. What I'm building Paste your store URL (or a competitor

... drill into finding the right investors. And that s where Metal comes in. 1A: AI Search Our 25+ filters allow founders to identify very specific types of investors (based on our proprietary data and intelligence): https://kite.video/share/fZIuX3V... 1B: Similar Companies With <5 mins of work, founders can surface investors that: (a) Have invested in similar

... shows you your visibility, share of voice, and citation rates across each platform individually . This allows you to see exactly where you win and where you are invisible, with the granularity required to understand each platform's editorial identity. Competitor Intelligence: The platform automatically detects competitors

... time posting in p/introduce-yourself. I'm Lisa, co-founder of a cycle tracking app we built in Amsterdam. Wanted to introduce myself and share the harder lessons from the last six months, in case anyone here is wrestling with similar problems. Quick context. In 2021 the FTC fined Flo Health for sharing user period data with Facebook and Google. Millions of women learned, after the fact, that their cycle data when they bled, when they were trying to conceive, when ... ... still has 77 million users. Clue still raised millions. The category just moved on. We couldn't. The question we kept asking was the obvious one: why does cycle tracking have to be ad-funded? So we built the alternative

... study from UNSW Sydney tracked content similarity across 388 keywords in 2019 and again in 2024. Content has become significantly more homogeneous. AI-generated pages now dominate the top rankings, but they all look and sound alike "If the humans are not involved anymore, what does this mean for the industry in the future?" asked Professor Thomas Reutterer, who led the research. A Graphite/Common Crawl analysis found that 86% of articles ranking high on Google Search are human-written ... ... about adding the things AI cannot generate. Real examples. Hard-earned insights. A point of view that is not just a remix of the top 10 results. What I am curious about Have you noticed your content becoming more similar

... breaking, and so on. - Vaizle - I work with Vaizle, but it has very easily emerged as my fav platform. Not even lying. I can keep track of ad performance, check what competitors are posting on social. And best part is that I can feed it my own website + competitors

... writes faster. AI analyzes data. AI can even mimic your brand voice. But AI also makes everything sound the same. It pulls from the same top 10 results. It rephrases the same arguments. It optimizes for similarity, not distinctiveness. Here is what the research says. The similarity

... galdayan): our setup ended up being a Slack webhook per agent session, posted to a channel only that agent writes to. sounds basic but the key part was making the notification say WHY it's waiting (needs approval vs finished vs

... structures. Different wording. Different ways of presenting projects. Different positioning. I wanted to understand whether systems interpreted candidates differently depending on how information was communicated. And eventually I noticed something that felt almost unfair. Two people could have very similar skills. Very similar

... right film for a specific mood without making the user do an hour of curation. So I tried the inverse. Hand-build a semantic taxonomy of film moods, classify the entire corpus against it, match user queries via cosine similarity. No collaborative filter, no training set, no user data. The stack Next.js / Vercel, stateless PWA. No native app. 75-register mood taxonomy I hand-curated over months. Each one has an editorial definition + canonical exemplar films. Stuff like warm ... ... neon nights, anxious dread, intellectual puzzle, melancholy beauty. Defining "wistful" vs

... experiment for my startup, @Pretty Prompt : Remove the monthly tier; offer only Free or Yearly (basically no monthly plan available). We decided to do this after doing some simple maths and seeing that 42% of users today choose annual vs our monthly plan. So what if I can take out the monthly option entirely? Has anyone here done something similar

... spec Resolve ambiguity via multi-agent debate Train a task-specific small model (SLM) on that data Paper: https://huggingface.co/papers/26... What we re seeing: SLMs outperform GPT-5 on boundary decisions More consistent (less flip-flopping on similar inputs) Fast enough for real-time, per-interaction evaluation This leads to a different stack: GPT-5 generation SLMs evaluation + guardrails Curious if others are seeing similar

... contradictory. 1) When we re so flooded with AI-generated content, do you have any methods to recognise it? For example, I keep noticing the same patterns: long dashes, phrases like It s not X, it s Y, and similar structures. 2) But what about beyond text, like images or video? Comment from Nika(@busmark_w_nika): @suzychase  Probably those stories would look the same with AI. Comment from Jonathan Gorczyca(@watch84): Personal brand combined with video is huge ... ... upvote for the comment size :( Comment from Bengeekly(@bengeekly): For the ones coming from bots , I recognize more the profiles than the texts itself. Recently some comments felts real, but interactions between them, photo profiles were special in a similar

... massive datasets, they can be expensive, complex to query, and act as complete black boxes. If a search returns a weird chunk, diagnosing it is often a nightmare. Lately, I've been experimenting with a dead-simple alternative for smaller projects, and I'd love to know if anyone else is doing this: Dump raw data into a local folder. Use a strict markdown schema (like a CLAUDE.md or similar

... thought we knew We assumed enterprise customers wanted the same things as our small business users, just more of it. More security. More control. More features. We never talked to them. We read blog posts. We looked at competitor pricing pages. We guessed. Here's what we missed: Procurement cycles. Enterprise deals take 6-12 months. We had 30-day sales cycles. We weren't built for that. Security reviews. We needed SOC2. We didn't have it. Customers asked ... ... lessons. What stands out is how common this pattern is. Teams assume enterprise is just more features, but it s actually a completely different motion: longer sales cycles, compliance, onboarding, and trust layers. Also love the point about data vs

... months ago, we ran an experiment with our own data. At Rankfender, we tracked 5 of our own competitors across 8 AI systems. We log their share of voice, citation velocity, content gaps, platform variance. Months of raw numbers sitting in a dashboard. I pulled 6 months of data and fed it into Claude. One question: "Based on this, who is most likely to overtake us in the next 6 months? Show your work. Use the data. Don't summarize ... ... Give me the numbers." The answer changed how I think about competition. The dataset: 5 competitors

... Last month, I did something that felt slightly insane. I took our product description, fed it into ChatGPT, and asked it to build a competitor. Not a parody. A real competitor

... minutes, is this broken?" Yes, it was. We rebuilt it completely. Now it runs 3x/day, 3 quality matches per agent. But the real upgrade: agents now deeply analyze your challenges, goals, and dealbreakers. Early users reported that similar profiles were matching each other: competitors