Re:Ask HN: Do you have to read a lot as a programmer?
by samblr on Wednesday July 27, 2016 @05:55PM
(#12176795)
Yes. Over a career - one will learn lot of frameworks, languages, technologies, tools - before jumping to code - there is sometimes dense documentation to go through. At time this can be daunting as things might be poorly documented (eg mongoose documentation).
A handy trick is to make small diagrams of your readings - it can be as simple as writing a timing diagram of calls while reading documentation. This kinds of expands on what one reads - I found them really useful. Also, first search in google images - eg: you want to understand "angular architecture" - usually first few of images will be very relevant to grasp things in a abstract way. By doing this first you get component names and how they are connected (by seeing the image) then you read documentation - you kind of know what documentation is trying to tell now.
Understanding meaning of words are important if you are non-native speakers. Say there is a word you have never come across eg: convolution neural networks. One needs to know 'convolution' means then 'neural networks' before going any further.
So the key takeaway I feel is how quickly can one abstract new concepts or relate them to what is known or build new models of understanding.
A handy trick is to make small diagrams of your readings - it can be as simple as writing a timing diagram of calls while reading documentation. This kinds of expands on what one reads - I found them really useful. Also, first search in google images - eg: you want to understand "angular architecture" - usually first few of images will be very relevant to grasp things in a abstract way. By doing this first you get component names and how they are connected (by seeing the image) then you read documentation - you kind of know what documentation is trying to tell now.
Understanding meaning of words are important if you are non-native speakers. Say there is a word you have never come across eg: convolution neural networks. One needs to know 'convolution' means then 'neural networks' before going any further.
So the key takeaway I feel is how quickly can one abstract new concepts or relate them to what is known or build new models of understanding.