LVL Up Performance
Goals, reviews & feedback — flat rate, no per-seat fees
What it does
Goals & OKRs, 360° reviews, structured 1:1s, peer recognition, eNPS pulse surveys, PTO, and a drag-and-drop org chart — the whole performance loop in one workspace instead of five subscriptions. What's different is the pricing: flat monthly rates, never per seat. Free up to 10 people, $29 for 25, $79 for 100, $299 unlimited. Your bill doesn't move when you hire. Plus AI coaching insights across goals, feedback and engagement, and LVL Proof™ career portfolios employees keep.
Does the same job
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Hey HN! We're launching Founderpath today to help saas founders raise cash without diluting their company Instead of a merchant cash advance needing to be paid back within 6-12 months, our standard deal is 15% interest, 4 year payback, $200k check We get no equity, no warrants, no weird covenants, and don't require personal guarantees This cash is way cheaper than if you were to raise from a VC (normally diluting your equity pool by 20%+ and losing a lot of control via a board seat and veto powers) We're around all day today showing demos & answering questions over at…
DailyOutbid.lol14d ago · dailyoutbid.lol · ▲12Another outbid.lol copycat, but leaderboard resets EVERY 24h
More work this month
the category →
The app store for voice native apps that lives in your notch
Work · 28d ago · voiceos.com
The New Calendly▲211Handle all of the work before, during, and after meetings
Work · 17d ago · calendly.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