
Tracetify
Trace how any competitor got its first users
What it does
SEO tools tell you where a competitor stands today. Tracetify shows how it got there. Paste any URL and get a dated origin story: when the domain was registered, where it was first mentioned publicly, what followed, plus traffic mix, revenue signals, ad spend and AI visibility — 12 sources in about 45 seconds. Every line links to a dated public source you can open and check yourself. Anything we could not verify stayed out. Each report ends with three moves you could start this week.
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Visitor profiles and timeline by CroctMay 2026 · ▲142Uncover the story behind every click to optimize your site

- CFCompetitor Finder – Paste your domain, get your top competitors2025 · champsignal.com · ▲5
I built a simple tool to help founders figure out who their actual competitors are! You know... the ones your potential customers already know and compare you to. Just paste your domain, and we generate a focused list of 10 competitors with names, sites, and a quick positioning note for each. Why I built it: I run a competitor monitoring tool (https://champsignal.com), and I realized that before people can monitor competitors… they first need to find them. This is harder than you think for people that have not been around for years aha (It's free and doesn't require signup) Would…
More growth this month
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AstraPixels▲267A pixel-art solar system at its real current positions.
Growth · 29d ago · astrapixels.com

Launched alongside, August 2026
the whole month →- TL
Life & fun · 9d ago · louisabraham.github.io


- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io


I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 16d ago · simedw.com