I don’t think there’re many ridiculously useful things that are universally useful.
If some stuff is domain specific or have much theory involved doesn’t mean it’s not considered a fundamental concept in some areas of work.
If some other stuff was very useful for you doesn’t mean it’s universally applicable. For example, if you had worked on a high-frequency trading bot, I don’t think you would have used neither Python, nor ZMQ or other general-purpose messaging middleware, nor even OS-provided TCP/IP stack — they all cause too much latency.
I’ve been programming for living since 2000, worked in a lot of different stuff from web dev and enterprise to videogames, embedded, robotics and GPGPU. Yet I can name many huge areas which I hadn’t seen close enough, or at all, along with libraries and tools used by people working there.
Every time I start working in a new area, or when I resume working in an area after a long (years) pause, I read a lot of relevant stuff. Continuous learning is the key to stay good, IMO.
If some stuff is domain specific or have much theory involved doesn’t mean it’s not considered a fundamental concept in some areas of work.
If some other stuff was very useful for you doesn’t mean it’s universally applicable. For example, if you had worked on a high-frequency trading bot, I don’t think you would have used neither Python, nor ZMQ or other general-purpose messaging middleware, nor even OS-provided TCP/IP stack — they all cause too much latency.
I’ve been programming for living since 2000, worked in a lot of different stuff from web dev and enterprise to videogames, embedded, robotics and GPGPU. Yet I can name many huge areas which I hadn’t seen close enough, or at all, along with libraries and tools used by people working there.
Every time I start working in a new area, or when I resume working in an area after a long (years) pause, I read a lot of relevant stuff. Continuous learning is the key to stay good, IMO.