Who am I serving? + my alternative YouTube algorithm and an experiment

Hey everyone,

Happy Tuesday! (Update: I now send this email out on Tuesdays…)

This past week I:

  • Trended on HackerNews for my alternative YouTube algorithm

  • Reflected on my strategy for content creation

  • Decided to try an experiment: digital office hours


🎥 I coded my own YouTube algorithm (to stop me wasting time)

I love watching YouTube videos that improve my life in some tangible way. Unfortunately, the YouTube algorithm doesn’t agree. It likes to feed me clickbait and other garbage.

This isn’t all that surprising. The algorithm prioritises clicks and watch time.

So I set out on a mission: Can I write code that will automatically find me valuable videos, eliminating my dependence on the YouTube algorithm?

Here’s how it went.

This project ended up trending on HackerNews, spending several hours in the top 10 articles. So far more than 30,000 people have read it, which has led to loads of great feedback and ideas for future projects.

For me, this is strong evidence of the value of sharing projects in public - I’ll be writing some thoughts on this in the coming weeks.


🍛 Who am I serving?

My approach to ‘content creation’ so far has been to just make and write about things that interest me, and share them with others.

But I’m re-thinking this after being introduced to the idea of a “Content Thesis” (on this course).

The idea is to define your approach to content creation with the ‘WHO-WHAT-WHERE-WHEN-WHY’ framework:

  • Who are you making content for?

  • What will you make (YouTube videos, blogs, podcasts, etc)

  • Where will you share it (Substack? Personal website?)

  • When will you share it (once a week? twice a month?)

  • Why do you want to? And why will consumers benefit?

The answer should fit into the following sentence:

I will make [quantity] [content type] every [frequency] about [quality] [topic] for [audience].

When I tried to define my content for the last half of the framework I ended up with two different topics and audiences:

  1. Accelerated skill and career development for part-time coders

  2. Distilled cutting-edge insights for the healthtech-inclined

It’s interesting to me that I have two distinct audiences (albeit with some overlap). I don’t know whether this is good or bad.

I’d love to hear: Do you think I’ve captured the essence of my content well? Would you consider yourself in the first group, second or neither? (What would you be interested in seeing instead?)


🧪 An experiment: Digital office hours

I really miss bumping into people in real-life and discussing ideas. Also, I want to help people build their programming and data science skills.

So I came up with an idea: A ‘digital office hour’. If you’d be interested in having a group discussion/coaching session about building coding and data science skills, hit ‘reply’ to this email and we’ll schedule a time.

I’m particularly keen on designing and learning through projects, so I’m hoping discussion will centre around that. I’m thinking a group of 4 or 5 would be best, so will have to prioritise the first to reply if there’s a lot of interest.


🤩 My favourite internet things this week:

I’m a big fan of Mr Money Moustache and this conversation with Tim Ferriss didn’t disappoint. Insightful and practical advice on money management that provides new angles to consider your finances. One idea: “you can’t afford to buy anything you can’t afford to lose”.

The Out-Of-Pocket newsletter is great: it’s the bigger picture of healthcare, with comedy. I loved this article about how we could ‘gamify’ healthcare, to improve health outcomes.

One of the problems with supporting mental health is the difficulty measuring something like depression or anxiety. Google’s moonshot ‘X’ have tried to do just that using AI.


That’s everything for this week!

Until next time,

Chris

YouTube / Twitter / Website


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About Me

Hi! I’m Chris Lovejoy, a Junior Doctor and Data Scientist based in London.

I’m on a mission to improve healthcare through technology (particularly AI / machine learning), and share what I learn along the way.

In this weekly newsletter, I share my top thoughts and learnings from each week, as well as links to the best things on the internet that I come across.