Writing my third AI book taught me something I didn't expect: teaching AI is significantly…
harder than building AI.
When you build a system, you can rely on intuition. You make choices that "feel right" based on experience. When you write about it, you have to articulate WHY every choice was made. And sometimes you realize... you don't actually know why. You just did what worked.
That's humbling. And incredibly valuable.
Every ML engineer should write, even if it's just blog posts. Not for the followers or the personal brand (though those help). Because the act of explaining forces you to understand more deeply.
How I started: technical blog posts on Medium. Then tutorials on YouTube. Then I contributed to documentation for open source projects. Eventually I pitched a book to a publisher, using my blog as my portfolio.
Three published books later, here's what I know: writing about AI has made me a better engineer than any course or certification. When you can explain something clearly to a beginner, you truly understand it.
And if you can't explain it simply? That's a sign you need to study it more, not less.