The Future of the Book: Text as a Knowledge Technology — Will It Survive?
For five thousand years, books have done something no other technology has managed: let you enter another person’s mind and reconstruct their thinking in your own. In 2026, the most powerful technology we’ve ever built communicates the same way — as a chain of words on a screen. But in a world racing toward interfaces that bypass text entirely, will the book survive?
The Index Card, the Map, the Researcher, and the Scholar: How AI Finds What Matters in Your Books
There are two ways to know a book. One changes how you think. The other gives you answers to concrete problems. Most people drift toward one or the other. Combining the two is where you stop consuming knowledge — and start creating it.
The Book You Read vs. The Book You Query
There are two ways to know a book. One changes how you think. The other gives you answers to concrete problems. Most people drift toward one or the other. Combining the two is where you stop consuming knowledge — and start creating it.
OpenClaw: The AI Agent That Gives You Time Back Instead of Stealing It
A new AI tool exploded this week – 100,000 GitHub stars, Mac Minis selling out, three name changes in seven days. But unlike most tech hype, OpenClaw might actually deliver on a promise we’ve been waiting for: AI that gives you time back instead of stealing it.
How I Bring My Reading To Life with Claude Code
My books should work for me. Not sit passively in highlights waiting to be searched, but actively remind me of what I’ve read in the right moment, suggest connections I haven’t seen, and help me apply what I’ve learned to real problems. Here’s how I built that system with Claude Code.
Claude Code + Kindle Highlights: How I’m Teaching an LLM to Navigate My Library
What if an AI could search every book you’ve ever read and find the exact insight you need — condense years of reading on a topic, or compare how different authors approach the same question? I’m experimenting with Claude Code to make this real: teaching an LLM to navigate my entire Kindle highlight collection and become an intellectual sparring partner.
Topic Memos Across All Your Books: New Cross-Library AI Features in Development
Your reading history contains years of insights, but they’re scattered across dozens of books. When you need to pull together everything you know about a topic, those highlights feel unreachable.
We’re building new cross-library AI workflows for DeepRead that transform this scattered knowledge into structured outputs. Through guided conversations, the AI helps you generate topic memos or mind maps that synthesize insights from across your entire library. The key difference from traditional AI chat: the system has persistent access to your complete reading history, not just what you upload. Every interaction creates something tangible and makes your knowledge system more valuable.
We’re developing these workflows now and looking for early users to test features and share ideas.
Kindle Highlights for AI: Transform Reading into Knowledge
Systematic highlighting is hard work—but it unlocks four powerful ways to engage with books through AI.
Each workflow creates a tangible artifact—not just another chat that disappears. This article shows you these workflows: building mind maps, generating meaningful flashcards, challenging the author’s arguments, and capturing insights with visual connections. I’ll explain why comprehensive highlighting—the Composer strategy from my previous article—makes all of this possible. We’re also exploring how to bring these workflows into DeepRead.
Kindle Highlights Done Right: Choose Your Strategy Before You Start Reading
Most readers highlight reactively—marking whatever seems important as they read. But effective highlighting starts before you open the book: by choosing your strategy and defining your desired outcome. The difference between collecting treasures and composing arguments determines everything that follows.
Design Elements That Turn Books from Content Delivery into Learning Systems
Some books function as learning systems rather than mere content delivery vehicles. They do this by using design elements such as quotes at the start of chapters, highlighted questions within the text, or chapter summaries at the end. These elements create a reading architecture that guides you through three phases: preparation, exploration, and synthesis. The real power lies in actively using these elements to transform any book into your personal learning laboratory. This way every book becomes an expedition where you decide what to discover and take home.