Interview Assist
Personalized, real-time AI guidance during live interviews
What it does
InterviewAssist is a real-time AI interview copilot that listens to conversations and provides personalized, structured guidance based on your resume and target role. It works alongside Zoom, Meet, Teams, HackerRank, LeetCode, and CoderPad, supporting behavioral questions, coding, technical discussions, system design, diagrams, and follow-ups. Get fast talking points that help you organize your thoughts and answer confidently.
Get clear, contextual AI guidance for behavioral, technical, coding, system design, case, and other remote interviews across roles and industries.
InterviewAssist listens to your interview, understands the context, and gives you useful guidance in real time—so you can answer with confidence. Practical tools that help you listen carefully, organize ideas, and communicate with intent. Invisible during screen sharing, with no distracting dock or taskbar presence. Capture spoken questions in real time and keep follow-ups connected. Transform a broad question into talking points grounded in your experience. Captures coding problems, diagrams, and shared slides directly from your screen. Uses your background and target role to produce more relevant interview guidance. Works seamlessly with every major meeting app, coding platform, and audio…from interviewassist.in
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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 · 17d ago · simedw.com