> I dont' have brainpower to completely relearn from scratch every few years anymore. I understand what you mean when it comes to new frameworks. I learned to

> I dont' have brainpower to completely relearn from scratch every few years anymore. I understand what you mean when it comes to new frameworks. I learned to code in the 80s, and nothing has really change since then. There is this misunderstanding that things change fast, they do not change at all. Only the level of abstraction changes. When I was a kid I was capturing interruptions to implement mouse movement, it requires fast code that runs for a moment to react to the event and returns to not block the system. Same that with AWS Lambadas. I personally do not see any difference. Immutable messages passed between actors to implement concurrent behavior of enemies was common when multi-thread PCs first appeared. The theory is form 1973. Now I use that same knowledge to build micro-services. The big challenge is that what I did at CPU level in the 80s now I do at the service level in clusters of machines in the cloud. From CPUs, to virtualization, to cloud, all the same thing: input in, output out. But, I am also tired of learning new syntax for the same things. The most difficult part of learning AWS is to remember the specifications of the product, if they offer this type of connection in S3 but not in EC2. The difficulty is to remember arbitrary decisions based on temporal situations. > machine learning with emphasis on theory That is the only innovation (applied, the theory existed by very long) that I have no real equivalent from the 80s. And, I am following your same advise and going for it.