... card, they bounce not because they wouldn't have paid, but because the ask came before the trust. I know because I do it myself. If a product asks for my card before I've seen anything, I close the tab and forget it existed. No card means more signups, more feedback, more people who fall in love and then pay. It also means a flood of free users who never convert, a support load from people who will never ... ... spend a cent, and a trial that drags on for six months because nobody had to commit to anything. I've seen

... features I win. It also puts rivals' names on my page, which invites them to return the favor, and it ages badly the moment they ship something I don't have and my table becomes a lie. I've seen comparison pages that were honest and genuinely helpful, and I've seen

... sessions. Homepage: 43% Feature page: 22% Blog post: 14% Comparison page: 9% Docs page: 7% Integration page: 5% 57% of new users entered somewhere other than the homepage. They arrived on a page about a specific feature, a specific competitor comparison, or a specific integration. The homepage was not the front door. It was one of six doors, and the one most likely to be seen

... post-page surveys. Highest-rated page: 4.8 / 5. It was a status page that showed system health and recent incidents. Views per month: 1,400 Total monthly page views: 2.8M The best-loved page in our product was seen by 0.05% of sessions. It was rated highly because the only people who saw it were the ones who needed it at a moment of anxiety, and it gave them exactly what they needed. We tried to promote ...

... 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

... that s core. Slow process, but no more surprises. Has anyone else formed a similar practice or is there a way to automatically do this testing? Comment from Dim Neocleous(@dimneo): Do they follow your request? Or have you seen them go out of line sometimes ...

... 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 ...

... reading this is the piece I would build first. The thing I would genuinely like to know from your side: what happens in clinical paging when the ladder runs out? Someone has to be last, and I have never seen a good account of what that person's silence is supposed to mean. Comment from Aadil Ghani(@aadilghani): @jernej_jan_kocica   "No gate plus extra steps" is a failure mode I have never had a name for, and your ... ... despite being nothing alike. One caveat, since otherwise this flatters my side of it too much: a tired person will ack a plausible, confidently wrong reply and approve it. Ack proves it was looked at, not that it was seen

... 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

... time to finish the gallery. Does the day of the week still matter much in your experience, or is that mostly a myth now? Comment from (@new_user___26020267b63ea4605738cbb): Launching BillFast today has reinforced the ready enough vs. finished distinction for me: the core flow (create an invoice, preview it, download a client-ready PDF) is narrow and usable, while feedback is now surfacing the edges currencies, taxes, templates, and payment instructions. For a small product, that feels ... ... proper side-by-side view because the old one made you compare two things it wouldn't show you at once. Realistically: mid-September. Does a month of showing up first sound about right to you, or have you 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

... 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

... your project" feature is perfection. no notes. Comment from Dmitry Zhlobo(@dzhlobo): @Kagi -- search, translate, and AI assistant Amp & Claude Code @Reflect @LM Studio Discord Comment from Hans Desjarlais(@ismaelyws): Gmail Calendly Claude Code Google Docs & Sheets VS Code Comment from Bill Davis(@billspaced): @nolan_vu  Slack, not because I love it but because everything dies without it. YESSSSSSSSSSSSS Comment from Bill Davis(@billspaced): @riya_pariyar   @benfleming   @asapx  same question... never heard ... ... solo founder, these are the five tools I use almost every day: ChatGPT VS

... actual insight, and it's bigger than it looks: making the notification say why it's waiting is what turns a ping into a triage. "Done" makes you tab back to find out what "done" means. "Needs approval vs finished vs

... feel way more transformative than just text/image generation because they actually change how people work day to day Comment from Felicite Moorman(@felicitemoorman): LOVE this question! Lurking! ;-) Comment from Samir Asadov(@samir_asadov): The most useful AI I've seen is the boring kind applied inside specific structured analytical workflows where it eats hours of mechanical work that humans don't do well anyway. In financial modeling: ingesting a 200-page offering memorandum and pulling out the deal terms (capacity ... ... adds up to about twenty percent of someone's week back which is the productivity gain that actually shows up in deliverables. Where it still falls down: the judgment calls. DSCR target for a merchant wind project versus

... 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

... nika): @vaibhav_singh53  The best combo imo is when you know how to merge those two into one :) Comment from Nika(@busmark_w_nika): @justinlee020617  that is build in public but I have seen how many people stopped doing it because competitors

... 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 ... ... data lives than what the AI could actually do. Data sovereignty, not model capability, was the #1 thing. That one insight basically forced us to rethink our entire architecture. Anyone else been surprised by what enterprise buyers actually prioritize 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