I've been spending the past few weeks diving deep into several areas of interest. It is easy to be overwhelmed by the amount of information that exists and to become stuck in consuming without actually learning. Here are some principles that I try to stick to when learning a completely new and unfamiliar topic:
Build a map of the territory first
It may seem counter-intuitive to do this first. Why would you build a map of the area you're looking to learn before knowing anything about it? I've found it important to do at the beginning for a few reasons:
- It forces you to focus on the high level before getting lost in the low level.
- It's easier to update an existing model of how things relate to each other than do this sequentially as you feel you have a clear understanding of each unit of knowledge.
- It's easier to skim over an article about a topic and extract the key concepts discussed than do this while you're reading it for understanding.
The critical part is that you constantly refer back to this and update it based on your new knowledge.
Once you have your map, set about starting with one of the nodes - an excellent place to start is often the one with the most connections to other nodes.
Be precise in the objective of your learning.
I like to have a concrete objective in mind when learning - what am I planning to do to put this new knowledge to use? This approach isn't necessary, but I find that it focuses the mind and ensures you're separating signal from noise.
Even if I'm learning something for its enjoyment, I want to have a concrete objective; a blog post, YouTube video, or launching a product to apply the knowledge.
In doing this, you also set the boundaries for what your map should or shouldn't include - for me, curiosity can lead me down tangents that are only sometimes useful.
Applying this to Crypto
Taking the example of my recent research of Crypto and web3, I initially sought out good content curators within the space. Twitter is fantastic for both following prominent voices in the space, as well as finding good articles to use as a launchpad.
From this, here are a few of the posts that I landed on:
- Crypto Canon: https://a16z.com/2018/02/10/crypto-readings-resources/
- NFT Canon: https://future.a16z.com/nft-canon/
- DAOs Canon: https://future.a16z.com/dao-canon/
- Gaby Goldberg's Reading List: https://gabygoldberg.notion.site/f7050e62461143d49345e7b46eb5576b?v=c02511c4230c44ce9a1a03c9757da524
- Gaby Goldberg's Podcast List: https://gabygoldberg.notion.site/8d124b6139ad41ef84c11b0a32cedc49?v=040c8d87221e466e98ffea726bf649eb
Each of these links provides many more links to specific topics, which helped update and adjust the map as I read through each one. Having a clear objective for your learning in mind throughout the process enables you to filter down these lists if not all of it is necessary.
Testing proper understanding as you read within the topic
An excellent way to evaluate your proper understanding of a topic within your map is to apply the Feynmann technique, which is explained clearly here.
Applying thought on top of learning.
Reading posts and listening to podcasts is a good start, but it is important to apply your own thinking to the content you're consuming simultaneously. This is particularly true in fields such as Crypto which are very nascent, and therefore it would be unwise to take anything beyond the technical details as a consensus view.
I write down a list of questions that I want to answer and add to this as I am learning. As I become more knowledgeable, this expands to a few core hypotheses that I want to test.
The process can be time-consuming, but I've found that following the above principles improves efficiency considerably.