The Complete AI Reading Guide for 2025

I'm the guy with books in every single video.

Look behind me in any frame—there they are, spine after spine, because reading is how I metabolize the world. So when people started flooding my inbox asking "What should I read about AI?" and "Is reading even worth it when ChatGPT can summarize everything?"—I couldn't just send them a list.

The more I listened, the more I realized I was hearing from completely different audiences. The C-suite executive trying to make AI strategy decisions doesn't need the same books as the engineer building models. The product manager working with AI teams needs different foundations than the policy maker writing regulations. Everyone was drowning in the same overwhelming flood of AI content, but they needed different lifelines.

There’s been a pandemic of various sources claiming we’re experiencing "knowledge rot"—that AI is destroying human knowledge by endlessly recycling and regurgitating information. The panic is palpable. People are either abandoning books entirely ("why read when AI can summarize?") or mindlessly parroting claims that you can read War and Peace in 10 minutes with AI (yes I saw someone claiming that on TikTok, she said she read 40 books a day and I wanted to scream.)

I think we’re approaching this completely wrong.

The problem isn't that AI is rotting knowledge. Making knowledge rot the object paralyzes us. It’s an incorrect frame.

The problem is we're using old mental models for a new information landscape. This is a skill issue, and it’s absolutely solvable. We don't have a knowledge crisis—we have a filtering crisis. And nobody's teaching us how to read strategically when we have an AI companion literally in our pocket.

What's in this guide:

• 34 carefully curated AI books organized into five distinct learning pathways (Executive Strategist, Technical Practitioner, Informed Professional, Policy Maker, Startup Founder)

• Three types of reading decoded: Awareness reading (scanning), retrieval reading (hunting facts), and connectome reading (deep rewiring)—plus exactly when to use each

• The Quick Guide: Strategic shortcuts for identifying which 20% of any book deserves deep attention

• The Complete Guide: Comprehensive prompt library, workflows for different content types, and a 90-day implementation plan

• Interactive Claude artifact: Personalized pathway matcher that shows how to use AI to save 40-60% reading time while improving comprehension

• My actual reading methods: How I read "hungrily" between writing and videos, using AI as reconnaissance before diving deep

• Time estimates and prerequisites for every book, so you know exactly what you're committing to

• The anti-knowledge-rot thesis: Why we need better filters, not less AI

I've spent months building this because I believe we can read more effectively with AI, not despite it. Once you understand which type of reading you need for which book, and how to use AI as a reading companion rather than a replacement, everything changes. You read more, not less. You comprehend better, not worse. You save your deep reading energy for what actually matters.

This isn't about reading less, or reading less carefully. It's about matching your reading approach to what you're actually trying to achieve.