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Jenn Herrarte
Jenn Herrarte

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How to Read Technical Books ๐Ÿ“š

Hello! Happy 2024! THIS is the year where we're picking up the stack of software engineering books that are collecting dust and cracking them open.

Last year, I started reading Designing Data-Intensive Applications by Martin Kleppmann. One page in, and I realized reading it was going to be a doozy. Getting through the material taught me that reading technical books requires a level of effort that goes beyond reading your average book. Here are my top tips for reading technical material.

TIP #1 - Draw it out โœ๐Ÿฝ

For example, if the text lists out the pros and cons of using a specific technology, draw it out in an actual chart. So many of these books don't have pictures (can we please change this)so drawing goes a long way. If thereโ€™s an analogy that comes to mind when reading about a concept, draw it out! I enjoy using Figma to create slides containing all my visuals.

figma

TIP #2 - Use ChatGPT ๐Ÿ’ป

Use ChatGPT to look up any keywords or phrases you donโ€™t understand, especially if the text doesnโ€™t explain what it is. For example, if thereโ€™s a paragraph talking about how nodes communicate through routing packets and youโ€™re like what is a route packet???, just look it up.

pro tip: use the voice feature in the chaptgpt mobile app for quick answers on the go.

chatgpt

TIP #3 - Read Blogs ๐Ÿ’ก

Read engineering blogs that show real-life examples or case studies that help solidify the concepts you are reading about. For example, this blog post from Educative covers the Ticketmaster meltdown from a system design perspective and this might have affected you personally if youโ€™re a swiftie!

Tip #4 - Teach the material ๐ŸŽ

My last tip is to teach the material! You can do this via blog posts, YouTube, LinkedIn, etc. I started a book club recently that covers one chapter of Designing Data-Intensive Applications a month, which adds a level of positive pressure to study and understand the material. Teaching the material solidifies it in your brain.

github

I hope this helps! Let me know in the comments what you're all reading.

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