... that. The problem is that the timeline in an editor is too complicated. Some scenes need subtitles, some layers are related to each other, and some parts need an extra image, for example. Each addition has a purpose. As tracks accumulate, the timeline starts demanding more attention: scrolling vertically, finding the right clip, checking what sits above what. I was also a content creator, so I found these processes really annoying. And when I decided to build an NLE interface ... ... Then you need to rearrange the clips stacking order and positions. That s it. That s the basic process of making any video, and it became the starting point for A/B Roll mode. The timeline keeps the core A/B-roll tracks

... everyone! First update since the launch, and it's one a bunch of you asked about in the launch thread. Scribble now tracks Claude alongside ChatGPT, Gemini, Perplexity, Copilot and Grok, so that's six engines, every tracked

... YouTube Shorts for musicians on our roster, we hit the same wall everyone else does: great audio, no video. Traditional shoots cost $3K to $8K and take three weeks to deliver. A typical indie artist ships one or two tracks a month the math collapsed immediately. So we looked for a way to generate a YouTube Shorts-ready 9:16 video from a finished audio track

... video, and making one used to mean hiring a motion designer, buying a stock-footage subscription, or learning a video editor. So we built a way to generate a Spotify Canvas from your audio directly: upload your track, describe a visual mood, and receive a canvas-ready 9:16 video in minutes. That's the core of Echonos. Here's what we built, why we built it, and what surprised us along the way. What Was Broken About the Canvas ... ... Workflow Spotify Canvas has been live since 2019. The engagement case for it is solid according to the Spotify for Artists Canvas documentation , tracks

... 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

... just exposure, but the degree to which AI treats your brand as a 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 when answering a topic-related question. Sentiment: Captures the emotional tone of AI mentions positive, neutral, or negative showing how AI portrays your brand. Together, these four metrics answer the two most fundamental GEO questions: How frequently does AI mention ... ... brand? and In what tone and context is the brand represented? 1.2 Trends and 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 ... ... looking. The Dataset Parameter Value SaaS products analyzed 1,024 Total AI answers collected 75,382 Total citations recorded 316,604 Platforms tracked

... 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

... everyone, Sam here. Tomorrow I m launching nodal on Product Hunt. nodal is a macOS menu bar app that automatically tracks the time you spend working based on the Git branch you re active on. I built it because I ve always hated manual time tracking

... 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

... 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 ... ... understand why LLMs were not citing Product Hunt and whether we could change that. The most recent Orbit Awards provided a clean test case, and a new tool called @Gauge made the impact measurable. Gauge tracks

... Netflix uses for recommendations). Here's the flow: USER FEEDBACK LOOP Write AI Suggests Accept/Deny/Retry System Learns Model Stats DB Model A: 85% Success rates Model B: 72% Model C: 91% Use this one! Thompson Sampling Algorithm Balances exploration vs exploitation Try new models Use proven models (10% of time) (90% of time) What's Thompson Sampling? Think of it like this: The Casino Analogy: You walk into a casino with 5 slot machines. Some pay out more than others ... ... better it gets at serving you. It's like having a personal assistant who learns your style. 3. Automatic Optimization Works silently in the background. No settings to configure. No choices to make. Just write. 4. Privacy First SourcePilot track

... that look more like car payments than development expenses. That being said, personally, I've been jumping between 10+ different billing portals just to figure out where my money's going, and honestly, it's become a nightmare to track. Have you had this problem as well? If yes, how do you tackle it? What tools are you using for cost tracking

... ProductHunt Companies are hemorrhaging money on inefficient AI usage without even realizing it. After watching countless teams, and myself, struggle to manage ballooning AI costs across multiple platforms (juggling between billing portals, losing track of spending, getting surprised by bills), I decided to build. After ~1 week, I launched (first launch) an MVP for AIBillingDashboard.com . What I built: A unified dashboard that tracks