Deal Fight
A transparent sponsored leaderboard for software deals
What it does
Deal Fight is a live leaderboard for software offers. Brands bid for visibility, and the public bid determines rank. The shopper discount remains a separate, clearly labeled offer. Every paid placement is labeled, every deal is manually reviewed before publication, and founding sponsored positions start at $5.
Exclusive software deals on a transparent sponsored leaderboard. Brands compete for visibility; shoppers get the savings.
Discover useful products with discounts you won't find on their public pricing pages. Why #1? Notedrop has the highest visibility bid. That decides placement—not the discount. Rank shows what a brand paid for visibility. The large green offer shows exactly what you receive. Brands choose how much to commit for placement. Highest total gets #1. A separate discount of at least 10% gives you a reason to click. Clear paid rankings without pretending the highest bidder has the best discount. Your listing contains two separate levers. Make shoppers a compelling offer, then choose how visible you want it to be. $5 gets listed. Higher lifetime totals move your sponsored rank up. See exactly what…from dealfight.lol
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kickbid.lol — The paid leaderboard. 12d ago · kickbid.lol · ▲1Rank is the bid — nothing else. No ads, no algorithm.




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 · 10d 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