In 2017, a group of researchers at Google published a paper called “Attention Is All You Need.” It introduced the Transformer architecture, kicked off the era of large language models (LLMs), and changed everything we know about software, work, and productivity. Nine years later, I find the title almost funny. The technology born from “attention” now demands something we have neglected for years: knowing how to read.
I spend most of my workday reading. Not books, not articles. AI output. I open ClaudCode, and it generates a 200-line execution plan for a feature I described in two sentences. I ask ChatGPT to research a topic, and it returns a full document with sources, comparisons, and analysis. Every interaction follows the same loop: I read, I interpret, I decide what matters, and I ask again. The faster I read without losing information, the better my next question becomes. Most of my value comes not from what I type, but from how well I process what comes back.