In a talk for DataTalksClub, Eugene Yan discusses why he started writing, the process he uses, and the role writing plays at Amazon. While the talk is framed around tech careers generally, it carries particular weight for AI and ML engineers, who must explain models, trade-offs, and results to mixed audiences.
Yan describes writing as a way to think more clearly. The act of putting ideas into words forces the writer to confront gaps in understanding. For machine learning work, where decisions are often subtle, this kind of clarity is valuable.
He also outlines a practical process built on consistency, and he highlights Amazon's culture of using written documents for proposals and decisions. That culture treats writing as a core engineering skill, not a side activity. The talk suggests that writing is less about self-promotion and more about improving the quality of technical work.