... figured this was the right place to actually show it. It's a free, no-signup, browser-based Pokemon TCG booster pack opening simulator. 47 sets, ~5,475 cards, every era from Base Set 1999 through HeartGold/SoulSilver 2011. The pull rates match the originals (64% rare / 28% holo / 5% secret / 2% shining / 1% crystal), and I went deeper than I probably needed to on the rarity-specific visual effects Crystal ... ... cards have a refractive shader, Gold Stars get the gold gradient, Lv.X has the holo-foil sweep. Stack: React 19 + TypeScript + Vite + Tailwind 4 + Zustand, Cloudflare Pages, Pokemon TCG API. Programmatic SEO build step generates ~6,800 prerendered card / pokemon / pull

... Wednesday and I'm still slightly wide-eyed about it. The why: I read Ready Player Two and there's a moment where music kicks in the second a character arrives somewhere meaningful. That sat with me. It pulled up a load of memories Sunday afternoons pulling

... lost 2,400. That mistake was 100% preventable. Three previous tenants had posted about it on Reddit. I just never thought to search. I've spent the last month building BeforeYouMove , a tool that enters any address worldwide and pulls: Street-level safety records (not city averages) Hour-by-hour noise patterns from public + crowdsourced data Real Reddit posts from people who actually live nearby Walkability, amenities, transit Sun exposure on each side of the building Demographics + price comparisons block ... ... useful or bloated? Anything you'd cut? Pricing , 4.99 per report, 14.99/mo for 15 reports. Too much? Too little? Wrong model entirely? Data sources , anyone in real estate or proptech who can poke holes in what I'm pulling

... users said they wanted. Feature requests. Sales calls. "It would be great if you added X." We built X. Nobody used it. So we stopped trusting what people said and started tracking what they actually did. The dataset We pulled 12 months of usage data from Rankfender. 1,247 active users. 27 distinct features across 8 modules. We looked at three metrics for each feature: Adoption rate % of users who tried it at least once Retention rate % who used ... ... 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

... 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

... Memory Studio. With the Plurality MCP, I don't have to use the AI Context Flow browser extension and can instead use the MCP server directly on Claude Desktop. This helps me in three ways:   I can pull in my context on Claude Desktop, Claude Code, and even with Cowork   I don't have to keep pressing the optimize button to pull

... with Platform X." Estimated: eight weeks. Claude's analysis: "What outcome does this drive? No stated goal. No success metric. No evidence customers are asking for this. Without these, this is a cost center disguised as a feature." We pulled our customer call transcripts from the past six months. 147 calls. Not one mention of Platform X. We pulled

... Maybe more. Here's the painful truth: Your site is translated. Your AI visibility isn't. When a German user asks ChatGPT in German about your category, you're invisible. When a French prospect searches Perplexity in French, your competitor shows up. Translation AI visibility. And it's costing you. The Data We tracked 200 SaaS companies with multilingual sites at Rankfender. Market % Visible in Local AI Answers US (English) 64% UK (English) 58% Germany (German) 22% France (French ... ... Founder: B2B SaaS, 8M ARR "We spent 40k translating our site into German and French. Beautiful work. Native speakers. Perfect messaging. Six months later, we checked German AI answers about our category. We weren't there. Not once. Our competitor

... make things that would have been much harder before. We made a homage to the classic tech keynote before we launched and it helped us create something much bigger-feeling than a small team would usually be able to pull off: That s where AI is brilliant. It gets me so excited about the future of content. 6. Newsletters We also worked with some of the AI-focused newsletters to create content that raised awareness of the product. These were ... ... need a simple way to watch what s happening. Social followers. Website traffic. Traffic quality. Where we re getting mentioned. Where we re not getting mentioned. Whether answer engines are picking us up. I use Dojo AI to pull

... founder of Munch. I built this because I kept watching creators spend hours turning one video into posts. You paste a YouTube or Vimeo URL Munch extracts the transcript using 5 fallback strategies (so it actually works on videos competitors choke on) Claude AI writes 8 complete, platform-ready pieces in ~60 seconds. No file uploads. No per-action credits. One munch = everything. PH exclusive: Your first munch is completely free, no card needed. Just sign up at munch.video ... ... podcast RSS feed, or paste a transcript directly. Munch extracts the content and Claude AI generates 8 pieces of content simultaneously: 1. LinkedIn Post 2. X Thread 3. Newsletter Section 4. Carousel Slide Guide 5. YouTube Description + Tags 6. Pull

... 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 ... ... analyzed 50 brands that discovered errors and tracked the impact. Error Type Average Revenue Impact Pricing error (higher than actual) 47,000 Pricing error (lower than actual) 23,000 (leakage) Missing critical feature 38,000 Wrong positioning (enterprise vs

... Minute Audit Step 1: Keyword Selection (5 minutes) Choose 20 keywords to audit: 10 branded keywords: Your company name Your product names Your founder/CEO name Your flagship features 10 non-branded keywords: "[Your category] best tools" "[Your category] alternatives" "How to [solve problem you solve]" "[Your category] vs

... founder. So I built PackLeads( @Packleads )to automate the entire reconnaissance-to-close pipeline that agencies hate doing manually. How it works You type in a niche and a location (e.g., "Plumbers in Austin"). PackLeads scans the market and pulls back businesses, but instead of just giving you a list of names, every single business gets scored across 20+ real signals. The system checks if their Google Business Profile is claimed, when the owner last responded to a review, whether ... ... they have an optimized website, and if they are showing up in AI search results like ChatGPT, Google AI Overview, and Perplexity. Each business gets a Need Score (0-100) so you instantly see who's desperate for help vs

... problem we kept running into Every founder and growth person I talked to was doing some version of the same thing: Manually scrolling Reddit and Slack to find relevant conversations Running half-broken n8n workflows with keyword alerts Checking competitor mentions once a week (if that) Looking at their LinkedIn feed and seeing posts that were 10 days old And the frustrating part? The conversations that actually mattered like buyers switching tools, people asking for alternatives

... Rankfender , we've identified clear patterns. Certain content types get cited 3x more often than others. Here are the 7 content types that win AI citations with real examples you can steal. First, the data: Content Type Citation Rate (vs. average) Best For Comparison pages 3.2x higher "X vs

... Theatres, a major American corporation, actually chose real creators OVER AI slop. Pulling the award-winning AI short, "Thanksgiving Day" by Igor Alferov from its Screenvision Media preshow wasn't a small move. It was a recommitment to audiences who's outcry was heard. As a filmmaker, that's a signal that renews my confidence in physical production. Hollywood isn't afraid of new tools. It's refusing to lose consent. Studios can chase billion dollar video models ...

... 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 ... ... Pages without structure or headers Content that doesn't cite sources Why? AI engines love pulling

... been experimenting with different ways to build outbound lists recently. The usual tools show up quickly. Clay. Apollo. A bunch of automations promising endless leads. And they are useful. @Apollo.io is great when you want to quickly pull a list of founders or CTOs. @Clay is powerful when you want to enrich data and filter companies in smarter ways. But after a few weeks of testing, one thing became obvious. Tools help you move faster. They don t automatically make ...

... answer first. If they find it immediately, they cite it. The structure makes extraction easy. Step 2: The Comparison Page Template Comparison pages drove 40% of our citation growth. Here's our exact template: Title: [Brand X] vs [Brand Y]: Which is better for [use case]? Quick verdict (100 words) Who wins and why One sentence summary Feature comparison table Feature Brand X Brand Y Feature A Feature B Feature C Price XX YY Detailed breakdown (by feature) How each ... ... months. Why it works: The second version answers the question completely in one paragraph. AI can quote it without needing additional context. Formatting rule: Each Q&A block must be self-contained. Assume the AI will only pull

... workflow-specific state from internal systems What I like about the integrations model is that it gives this a clean runtime contract instead of turning every app into a one-off orchestration layer. A few things that stand out: Pull, webhook, or both Some systems are better fetched on demand. Others should push updates when events happen. Supporting both makes the feature much more practical for real products. Scoped data Project-, subject-, and chat-level scoping. Not all external data ... ... give you a clean way to combine memory, live external data, and prompt runtime in one system. Would love to hear how other teams are thinking about integrations: What external systems are you connecting first? Are you mostly using pull

... 4SEO.ai, and I wanted to share it here and get feedback from fellow builders. The first SEO automation platform built specifically for React, Next.js, and modern JavaScript frameworks. 4SEO connects to your GitHub, detects SEO opportunities, and automatically creates Pull Requests with safe, optimized fixes. I wanted to see if this entire process could be automated. So I started building 4SEO.ai an autonomous SEO optimization tool. Right now, it connects to Google Search Console and GitHub, analyzes real performance data ... ... detects pages with opportunities (for example, pages with high impressions but low CTR). Then it generates optimized titles and content improvements and applies them safely through GitHub pull

... data base combines layers of data all to create features and signals to train the model on predictable gov outcomes and compare it to the user input for a pool, or a ADU, a fence etc. 1. We pull Zoning. Both the zoning for the requested address & its regulations 2. We pull

... GEOScore, we've noticed a lot of discussion lately about how difficult it s becoming to decode why certain pages dominate search results while others, which seem just as good, get buried.   We built the Competitors feature in GEOScore specifically to take the guesswork out of that process, changing how you approach competitor

... your idea of what actually matters. This is the kind of problem that s hard to even describe without sounding vague. But you feel it instantly when you use the tool. You can tell when the AI is pulling on the thread you would pull

... What's New: Just shipped major improvements to Norte based on feedback from power users managing complex wallets: Smarter AI assistant - Now pulls full document context instead of keyword matches. Reads across multiple policy sections to catch exclusions and limits. Redesigned perk tracker - Built for people with redundant benefits (2 Priority Pass memberships, overlapping coverage). Shows what you're actually using vs