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by eightnoteight
926 days ago
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while I agree that there is a half-life to certain type of knowledge but I think it would be overstating to reasonably apply to all knowledge. its very easy to retain a significant portion of the knowledge by building mental models. sure you will forget about the API surface of a technology, but you would surely remember the underlying knowledge models and you would surely apply it in many other contexts. like remembering the REST API inputs and output data types is also a knowledge whose half life is much shorter. but building mental models of those would stay for a long time. the point never is to remember and include REST API input and output data as part of your skill set, the point is to include their underlying knowledge. and you can't treat the API surface of a library as knowledge, its essentially a volatile memory and supposed to be cleared away |
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When you know the basic "underlying" model, switching from a framework or language to another is not a very big deal. Not much bigger deal than figuring out a new large codebase with a familiar framework/language.
Sure, it may take a few weeks of learning new stuff and being unproductive (or even negatively productive) during this phase, but this is to be expected in any job.
I don't think learning the more fundamental concepts is that hard but it does require some time (and interest) that is not immediately productive. Perhaps due to demands of being productive, as in churning code, all the time gets people (and the industry) to get stuck in such "local optimum".