... Ross Hancher ex Lead Developer with 25+ years in enterprise software, now semi-retired and building full-stack products solo using AI-augmented workflows (mainly Cursor + Python/JS). I spent most of my career leading end-to-end delivery at a global market research firm legacy VB/C#/Oracle/SQL Server systems, migrations, AWS, DevOps, and CI/CD. These days I focus on turning ideas into deployed apps in days or weeks, not months. I'm not here just to generate code with ...

... built a tool that watches Reddit for competitor mentions and texts you here's why Last year I kept seeing posts like "looking for a Notion alternative

... 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

... Most AI visibility tools show you a dashboard. They tell you where you're invisible. They show you competitors winning. Then what? You stare at the screen, knowing there's a gap, but no idea how to close it. RAIVE 2.2 (Rankfender AI Visibility Engine) fixes that. It's not just a tracking engine. It's a prescription engine. It analyzes where competitors

... community I want to share something I've been building - Upvotics, a competitive intelligence platform for founders, marketers, and product teams who are tired of finding out what their competitors changed way too late. The problem I kept running into was simple. A competitor

... 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 Outdated pricing.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

... 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

... 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

... Average monthly retainer for AI visibility audits 1,200 2,500 Average monthly retainer for ongoing AI visibility + content 2,500 5,000 First-mover advantage is real. The agencies offering this now are locking in clients before competitors even know the category exists. Service Model #1: The One-Time AI Visibility Audit What it is: A comprehensive audit showing where the client appears (or doesn't) across ChatGPT, Google SGE, Perplexity, and Gemini. Deliverables: 20 50 keywords analyzed Screenshots ... ... actual AI answers Competitor

... 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

... 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 ... ... margin of error. Result: This block was cited verbatim by Perplexity within two weeks. Step 5: The 90-Day Update Cycle We analyzed citation decay across 500 pages. The drop-off is steep: Months Since Update Citations (vs

... connects directly to GSC and runs real-time analysis across 50+ SEO aspects: Top Page and Query Performance Top Mover Delta Analysis Growth and Decay Analysis Performance Trends Rank Disparity Analysis CTR Uplift Analysis Impression and CTR Segmentation Brand vs. Non-Brand Performance Cannibalization Analysis Topical Cluster Performance Device Parity Analysis Device Distribution Country Performance Long Tail Performance Trust and Authority Analysis Then it doesn't just report it. It moves from Performance Opportunity Analyze Fix Apply. Automatically. Comes with ... ... audits. Then: AI Brand Visibility Brand Analysis Prompt Run Prompt Tracking Competition Tracking Citation Tracking Monitored across Gemini, ChatGPT, Claude, Perplexity, Grok, and LLaMA. It surfaces missing semantic anchors, authority gaps, structural issues, knowledge reinforcement weaknesses, and citation loss 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

... sparked an interesting thought experiment: how likely is it that we ll see AGI (AI that thinks and learns like a human) within the next five years? The report highlights a fascinating divergence: the view from money vs. the view from science. Money : the probability inferred from trillions poured into data centers, Nvidia chips, and servers. Investors seem to be betting that AGI is inevitable. Science : the probability inferred from research papers and AI development models. Experts are far more ... ... might be ahead of reality. Expect volatility, overpromised outcomes, and valuable lessons along the way. Meanwhile, AI continues reshaping work, attention, and human behavior. I d love to hear the community s perspective: Are you seeing this money vs

... Merry Christmas Jonathan Ross (Groq s Founder)! $20B will buy a lot of holiday cheer! Today, Groq announced that it has entered into a non-exclusive licensing agreement with Nvidia for Groq s inference technology. The agreement reflects a shared focus on expanding access to high-performance, low cost inference. As part of this agreement, Jonathan Ross

... time updates on app downloads and revenue Real-time ranking and position changes across all app categories In-depth analysis of top market apps with similar app recommendations Advanced Search Multi-tag and multi-dimensional filtering to identify benchmark competitors Discover emerging niche markets and uncover growth & investment opportunities Competitor

... brand mentions across these models in real time, analyses sentiment and provides prompts showing how and where the brand is being referenced. It also sends real time alerts when a brand is cited by an AI model and offers competitor monitoring to identify positioning gaps. Thirdeye as one of the most-advanced AI analytics and recommendation platform that helps brands get discovered not just on Google but inside ChatGPT, Claude, Gemini and Perplexity, emphasising that if you aren t cited ... ... platforms such as ChatGPT, Claude and Gemini are becoming the new homepage for information, so brands must optimise for visibility across these models. This shift is supported by wider industry data: according to Nowspeed s guide on AEO vs

... word Job is now a slur for gen Z lol WW3 memes- these are trending with my friends a lot considering we'd be drafted first. Anything with political figures names/ images attached (Trump, Iran, Zohran, Adams) Comment from Ross Danowitz(@ross

... scratch yours exchange actually take place/help? Are you just here to scroll? If you come here looking for an answer, how much time do you spend looking for it before you go to the next platform? Is reddit the alternative? If you have any good strategies, let me know!! Would love to learn more. Comment from Ross