HabitPivot
The daily habit copilot that adapts when life gets busy
What it does
Most habit trackers treat routines as static, all-or-nothing checklists that cause guilt when life gets busy. HabitPivot is an adaptive AI health companion that flexes with your real day. What makes it stand out: 1. 1-Tap "Friction Pivot": Instantly scales 15-min tasks down to 30-sec micro-resets on low-energy days to protect your streak. 2. Adaptive 3-Block System: Morning, Midday, and Evening routines calibrated to your schedule. 3. Safeaty-First Coaching: Educates without diagnosing.
The daily habit copilot that adapts when life gets busy. Flexible circadian routines, 1-tap friction pivots, and non-diagnostic safety-first wellness coaching.
Rigid 15-step checklists collapse when energy drops. HabitPivot flexes with your real schedule using 1-tap friction pivots, circadian timing, and safety-first health coaching. Every habit generated by HabitPivot comes pre-equipped with 3 calibrated energy variants so your consistency never breaks on low-energy days. Designed to support your full health context without prescribing, diagnosing, or imposing rigid rules. A 13-question conversational baseline captures your schedule, screen exposure, BMI context, and fatigue zones. No generic one-size templates. Habits are intelligently placed across Morning Ignition, Midday Reset, and Evening Wind-Down to match your biological energy curve. Swap…from habitpivot.netlify.app
Does the same job
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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.
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Launched alongside, August 2026
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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.
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