My System for Deep Learning from Books

I believe in transparency about my content creation process, so I wanted to share how these book-based essays come together using a combination of personal reading, note-taking, and AI assistance.

Content Development Process

1. Complete Reading and Highlighting

I start by reading the entire book (primarily on my Kindle), highlighting passages that contain valuable insights, actionable advice, or concepts along with some of my thoughts I read the book. This frees me to engage with the book without worrying if I can recall this later on or not. I prefer Kindle as I can transfer all these at a later stage easily. If i am reading a physical book, I write down my thoughts in a notebook along with page no to serve as reference at a later stage

2. Refinement of Highlights

Once I've finished reading, I review all my highlights and make adjustments. I remove highlights that seem less valuable or repetitive. At this stage, I add my personal thoughts to existing highlights, while adding new ones where I feel the need for more context or supporting information. My goal is to ensure that I capture anything and everything that I find important.

3. Personal Knowledge Management

All my refined highlights get transferred into my personal knowledge base in Obsidian via Kindle Highlights Plugin. This allows me to refer to any insight at a later stage if needed rather than opening the book. For physical books, the notes are already in my obsidian vault.

4. AI-Assisted Synthesis

I use a series of custom AI prompt that I've developed over time that is aimed to compile learning from books I read. The goal is to translate raw highlights and notes into a structured, actionable essays. I currently use Claude as my AI model of choice for all written content generation.

5. Personal Review and Editing

Once AI drafts the essay, I review it, making changes where needed. As the primary goal of the essay to help me recollect more of what I have read, I focus to ensure the content truly reflects what I want to remember while being useful to me in the future.

6. Publishing as a Quality Enhancement Tool

Over time I have realised that when I write with a clear intent publish the same, my quality of the final essay is much better. I take more time to see if I can further info or context so that anyone who reads it can understand it easily.

AI's Role

In my prompt I instruct AI to analyze the highlights, identify major themes, and generate structured, practical content that emphasizes application over theory.

The prompt specifies a clear structure for each segment (introduction, body with actionability focus, key takeaways, action plan, and reflection questions). I instruct AI to write essays that avoid referencing complex words or sentence structure. The goal is to ensure its easy to read and understand. I instruct in my Prompt that AI needs to limits only to content shared and avoid adding any external information.

This process allows me to retain my perspective in the final essay, while letting AI to develop the initial draft. In most cases, the result does reflect what I found valuable in the book, presenting it in a format I can refer to when needed

Why This Approach Is Better Than AI Book Summaries

I've found this approach much better than simply asking AI to summarize an entire book. Most AI book summaries adopt a one-size-fits-all approach, which personally feels off to me. However, I do use such summaries as a filter to decide whether its worth the effort to read the book or not. Do bear in mind that AI summaries can never be a substitute for actually reading the book.

In simple terms, I use AI as an organizational tool working with my notes and highlights, rather than deciding what's important in the book.

This process will always be a work in progress as my personal priorities and learning goals evolve with the passage of time.

Please note that I won't be able to share the raw highlights themselves to avoid copyright infringement.