SuperIntern
Your email and meeting assistant, inside your chat apps
What it does
SuperIntern 2.0 is built for client-facing professionals who spend too much time on emails, meetings, and follow-ups. It learns how you write and automatically drafts replies in your voice, helps schedule and summarise meetings, and keeps follow-ups from slipping through the cracks. Scale your client capacity 10x without losing control. You approve every message before it sends.
Stop being your own assistant. SuperIntern runs your email, meetings, scheduling, and social media. So you can focus.
SuperIntern drafts emails in your voice, schedules and summarises meetings, and keeps follow-ups on track, wherever you are. I auto-draft replies, but never send without your approval. In your tone, with no prompting, and trained by your feedback. SuperIntern learns your tone, style, and habits from your preferences and edits, then keeps improving over time. SuperIntern works through the messaging apps already on your phone, so you never need to wait until you are back at your desk. I can join your meetings, remember what was decided, and run the recurring tasks you set. No complex setup. Connect, teach, and start delegating your inbox. Independently audited against AICPA's Trust Services…from superintern.ai
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More growth this month
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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