... mine launched there a few years ago, and they were really happy with the results. At some point, they even considered AppSumo one of their main growth engines. So now I m wondering how it looks today. I ve seen people talk about getting a huge number of users through AppSumo, but I m curious what happens during and after the initial spike. I ve seen

... nobody covered, which is worse, because it changes a line of code a lot of us shipped this year without thinking about it. If your product has a "paste a URL" box, a link unfurler, an enrichment step, a competitor-monitoring job, or anything that fetches a page and hands it to a model, this is about you. What was actually measured. The paper is "Indirect Prompt Injection in the Wild" by Khodayari, Zhang, Acharya and Pellegrino, out of CISPA ... ... validated prompt injections on 11,700 pages. Prior work on this has almost all been proof-of-concept - here is an attack we built, here is a model that fell for it. This is the first attempt I've seen

... between the marketing copy and actual proof. Most case studies talk about "improved visibility scores," not real outcomes like traffic, leads, or revenue tied back to an AI mention. So I'm genuinely curious what this community has actually seen, not just what the vendors claim: Has an AI Overview or ChatGPT mention ever driven traceable traffic or a lead for you or your clients? Are you (or your team) actively optimizing content for AI citability right now, or still ...

... That means I need to learn from the best. I ll be using the website for my Product Hunt launch and to get the verification badge in the Chrome Web Store. What are the best product pages you ve seen on Product Hunt so far? Ideally, I d love to see examples for Chrome extensions. Comment from Askim Stucki (@askim_stucki): @busmark_w_nika No, not really, to be fair. And if I did, then without knowing that they used ...

... real improvement. Irreversibility over-fires on writing a log line and under-fires on a migration you can only roll back with downtime. Reach is the better axis. But every gate in that conversation, and every gate I have seen shipped, evaluates a single action in isolation. Sending one email to one person is low reach. It passes. Four hundred of them inside twenty minutes is a mass email to your entire list, assembled one approved step at a time ...

... blast radius, not because it's dumb, but because the radius is determined by capabilities it isn't even looking at. That's the strongest version of the "worst judge of its own reach" point I've seen. And your authority-armed-versus

... looking through the newly released benchmark comparison, and one thing stood out immediately. Opus 5 outperforms Fable 5 on many of the benchmarks that matter to me: * Agentic terminal coding: 43.3% vs 33.7% * Knowledge work: 1861 vs

... 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 ... ... ranking rewards early comment/upvote velocity, so a genuinely rough product with 10 people lined up to engage in the first hour will out-rank a more polished one that launches cold and picks up steam slowly. I've seen

... make AI invisible. The user just notices the product works better. Loading times feel shorter because the app predicted what they'd need next. Search results are weirdly accurate. The interface adapts without them noticing. Three patterns I've seen work: Solve the friction, not the feature request. When users say "add AI to X," what they usually mean is "X is too slow / too hard / too confusing." Dig into why. Let users pull, don't push. The most successful ... ... features I've seen

... trying to solve are: Getting attention in an overcrowded marketing environment Increasing customer engagement instead of just generating impressions Encouraging repeat visits Making promotions more memorable Generating word-of-mouth and referrals Giving small businesses an affordable alternative to constantly buying ads The simplest way I'd describe it: Playistry helps small businesses turn ordinary promotions into interactive customer experiences without adding another advertising expense. https://Playistry.com Comment from Anurag sarkar(@angsak6): My tool makes it easy to deploy ... ... Meetings, Email, and more into a single platform with AI built in from the start, so startups can spend less time stitching tools together and more time building their business. In terms of launches on Product Hunt, I've seen

... flows more efficiently: https://www.producthunt.com/prod... Comment from Nolan Vu(@nolan_vu): @abhayraghuwanshi  Thanks for breaking this down, man, it's genuinely helpful to see the raw process. The local model vs cloud model tradeoff you mentioned is such a real pain point, I've seen

... that really caught my attention. Many great Indian businesses were spending heavily on SEO and marketing. When I asked ChatGPT for recommendations, most of these brands weren't even listed. The AI would recommend global companies, old websites, or competitors instead of Indian businesses. This really bothered me. As people start using AI to find products and services not being seen

... both content and   product work.   2. Google Search Console I basically live in it. For anything SEO, it's the only honest source of truth   about what's actually happening vs. what I assume is happening.   3. Ahrefs keyword and competitor

... that was really useful and innovative? We could start with one noble thing, like using AI to find a cure for cancer a specific article here . Comment from Nolan Vu(@nolan_vu): Honestly the most underrated use I've seen isn't flashy at all. We had a client in logistics spending 3-4 hours a day manually triaging support queries, most of them the exact same "where's my order" questions. Set up an AI agent to handle ... ... recreating tools: AI didn't just save me time, it acted as the activation energy to turn a fleeting "what if" into a fully functional, deployed tool. Comment from Samir Asadov(@samir_asadov): The most useful AI I've seen

... this feature? Why this customer? Why this way? When the questions stop, the thinking stops. The team is just executing. Execution without direction is just busy work. 5. The demo always works. The real product never does. You have seen this one. The demo environment is perfect. The production environment is a mess. The team knows how to make it look good. They do not know how to make it work. That gap only grows. 6. The churned customers ... ... this company? Those are not plans. They are hopes. The project is failing when you spend more time imagining the future than fixing the present. What I am curious about What is the quietest, most subtle sign you have seen

... ethical line. I sometimes worry they can seriously damage a company s reputation. There are also other practices, such as: Fake purchase counters on websites Buying followers and likes Exploiting a brand s reputation Spreading misinformation Clicking on competitors Google ads to drain their budget And the list could go on. What do you consider dishonest marketing practices? Have you ever had personal experience with them? On the other hand, have you ever seen

... mentioned, sharing your personal keys, from the account where you built your whole empire, creates real security concerns over time. Comment from Nelli Orlova(@nelly_orlova): the 'can't hand over personal accounts' part is underrated, i've seen 2 web3 founders kill acquisition talks bcz the twitter was tied to their face. brand-first works if you treat it like a separate asset from day one, not a side effect. curious if anyone here has actually pulled ... ... want to sell later, or hand off completely then you need it to exist independently from you. "Giving someone the keys problem you mentioned is dead-on and, honestly, founders don t talk about it enough. I've seen

... 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 ... ... that assumptions are incredibly expensive. Building for the customer you want instead of the customer you have can drain months of focus and budget. What really stands out is the contrast between 47 real requests for API limits 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

... Four Core Metrics The Overview page focuses on four key metrics: Visibility , Citation , Share of Voice , and Sentiment . Visibility: Indicates the proportion of relevant AI responses that actually mention your brand. A higher value means your brand is seen more frequently by AI within this domain. Citation: Measures, among all responses mentioning brands, how many include a link pointing to your official website or domain. This reflects not just exposure, but the degree to which AI treats your brand ... ... 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

... 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. Why give them free airtime? Wrong move. Every AI answer about your category includes comparisons. Always. If you don't provide the comparison, AI finds someone who does and that someone might be your competitor

... busmark_w_nika  That s a great point. I do think bootstrapped vs. VC-backed companies often approach this differently. If you re bootstrapped, revenue usually becomes important much earlier, so the free part tends to be shorter or more limited. VC-backed companies sometimes have the luxury to optimize longer for growth, data, and distribution before pushing monetization. That said, I ve also seen

... schema 71% 19% Cite data sources 68% 27% Part 3: What content wins AI citations? This is the question everyone asks. Here's the data: Top 5 content types by citation rate: Comparison pages (X vs Y) 3.2x average Structured FAQs 2.8x average Data-driven articles (with stats, tables, studies) 2.4x average "How to" guides (step-by-step) 1.9x average Original research 1.7x average What performs poorly: Short opinion pieces Thin content (<500 words ... ... great for blue links. But none of them show you how you appear in AI answers. Here's what we track: Actual AI-generated answers mentioning your brand Citation rates across ChatGPT, Google SGE, Perplexity, Gemini Share of voice vs

... plays a significant role in how products appear in Google search results. What surprised us was that AI assistants like ChatGPT were rarely citing Product Hunt in product recommendations. AI assistants such as ChatGPT and Gemini rely on reviews, alternative lists, and structured product information gathered across the web. Product Hunt is strong across all three. In theory, this should make Product Hunt a natural source for AI-driven product recommendations and comparisons. In practice, it was not happening ... ... many tools which systematically run prompts against several AI models daily, and measure visibility of a product within prompts. We're using a new tool called @Gauge . We chose because a) their citation tracking is more useful than the alternatives