THE VIDEO SHELF · interview preparation
Nardwuar vs. N.E.R.D - The Extended Version
Nardwuar interviews Pharrell and Shay of N.E.R.D. in Vancouver, using his trademark deep research and gifts. The extended version runs about ten minutes.
Why HN readers recommended it
HN holds it up as a model of interview preparation, where thorough research on the guest impresses the interviewee.
This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.
Video & recommendation details
- Creator / channel
- NardwuarServiette
- Topic
- interview preparation
- Format
- interview
- Level
- general
- HN recommenders in dataset
- 3
- HN mentions in dataset
- 3
- Recommendation years in dataset
- 2019–2023
These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.
From the original HN conversations
Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.
Narduar is my favorite example of a master interviewer. Watch him leave Pharrell speechless multiple times (starting around the 5:15 mark is a good example). This guy does his homework better than anyone. [VIDEO]
hanklazard on Hacker News · 2019-10
In Edward Snowden on The Joe Rogan Experience [video]There's a Canadian interviewer named "Nardwuar the Human Serviette" who mainly does interviews with rappers/musicians. Before each interview, he conducts the most in-depth research on them that anyone has ever conducted, mentioning people, places, early inspirations from their childhood and musical career, things that only …
7373737373 on Hacker News · 2020-10
In Chris Lattner: The Future of Computing and Programming Languages [audio]If you're into interviewers who go the extra mile to give the interviewee and the viewer a good experience, I also recommend a Canadian named John Ruskin, who also goes by the name Nardwuar the Human Serviette. He's a music geek (in the best way) …
toomanyrichies on Hacker News · 2023-04
In ‘Hot Ones’ Was a Slow Burn All Along
Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.