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We have been there before, yet we are still here. The proportion of systems programmers that can writte assembly code consistently on par with the quality of t

We have been there before, yet we are still here. The proportion of systems programmers that can writte assembly code consistently on par with the quality of that from a decent compiler (such as Gnu's GCC) is probably less than 1%, and they take orders of magnitude more time to do so. Yet, you do not observe system programmers dying out. They use C (and increasingly, C++, Dart, etc) to build bigger and more complex systems, with more demanding requirements. Ditto for application developers. We now have this amazing enginees called DBMS, which handle out of the box a bunch of common requirements, and whose reign and management has spawned a new class of job that did not exist 30 years ago: DBAs. Some of those are glorified IT grunts, but many are not! They build (information) systems that are bigger and more complex than ever by translating business use cases into a description that is understandable by the DBMS engine. I could keep going on and on: web frameworks, game engines, simulation models, etc, etc. The point is that the hard part about this craft is not to know how to make the machine compute some XYZ calculation, it is to understand that computing XYZ is an acceptable way to fullfil a business need within the limits of available resources (in the dimensions of development cost, runtime cost, infrastructure maintenance, etc).

pedalpete 10y ago
Note, I was talking about the 'average modern programmer'. I believe your argument points to a smaller more specialized sub-sections of the field. At the same time, you say "We have been there before", but we haven't had the quality of AI that we are reaching today, so in many ways we have not 'been here before'. Let's not forget, there was a time when elevator operators thought they were irreplaceable by a machine. Today, you can't imagine having somebody operate an elevator. A few years ago you had to be a 'web developer' to build a web-page. It was unimaginable that somebody who is barely computer literate would be able to put a website online. Today, you can run an online store without knowing anything about programming. I suspect DBAs won't have an illustrious future as machines learn how to model data. Yes, they will need a person to train them, and tell them what to do, but I suspect an AI system can look at all the potential modeling options and give a layperson the option to pick one which best suits their needs, or recommend one. As far as 'magnitude more time' for computers to do the work, I often find this argument interesting with respect to processing power in IoT. In life-threatening situations, performance is very important, but often as long as a persons time isn't being wasted, it doesn't matter if a machine takes twice as long.

pedalpete 10y ago

Note, I was talking about the 'average modern programmer'. I believe your argument points to a smaller more specialized sub-sections of the field. At the same time, you say "We have been there before", but we haven't had the quality of AI that we are reaching today, so in many ways we have not 'been here before'. Let's not forget, there was a time when elevator operators thought they were irreplaceable by a machine. Today, you can't imagine having somebody operate an elevator. A few years ago you had to be a 'web developer' to build a web-page. It was unimaginable that somebody who is barely computer literate would be able to put a website online. Today, you can run an online store without knowing anything about programming. I suspect DBAs won't have an illustrious future as machines learn how to model data. Yes, they will need a person to train them, and tell them what to do, but I suspect an AI system can look at all the potential modeling options and give a layperson the option to pick one which best suits their needs, or recommend one. As far as 'magnitude more time' for computers to do the work, I often find this argument interesting with respect to processing power in IoT. In life-threatening situations, performance is very important, but often as long as a persons time isn't being wasted, it doesn't matter if a machine takes twice as long.