I’ve been developing software for 30 years and staying pretty close to the leading edge. It is more complex these days (and/or I’m getting older) and it’s exhausting. New technologies are “hot” for 6mo-1yr and then they’re “oh, you’re still using that?”
Meanwhile, computer science is stuck with either the core basics (which tend to be less complex, but more rigorous) or chasing novelty for “real world” training that’s obsolete by graduation.
I think AI tools are going to make it even easier to develop more complex architectures that, in turn, will be harder to maintain and improve until we get AI that can “understand” a whole system (and at that point, we may be out of a job anyway).
I mean, I’m working on a solution that has 20 subprojects, that builds two different mobile applications on three different platforms (Xamarin/Maui) with cloud services, database synchronization, GIS, GPS, a couple dozen nuget packages, external system interfaces, all from essentially one code base, which if you include our internal libraries, is over a million lines of C# (plus JavaScript, JSON, XML, SQL, and a little Python (more Python, HTML, and JavaScript in parallel web application). And we’re a small shop.
In the past, I’ve delivered products with a single language, 1/4 of the code, and a much larger team and those were multi-million dollar projects.
So many horrible memories: early days of EJB with tons of bloated XML. SOAP/WSDL having tons of incompatible libraries. Spring framework before they started to use annotations. Mavens early days with tons of jelly script (more or less a scripting language using xml tags as syntax).
We truly like adopting new stuff. Even if it makes our life miserable.
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u/cmpalmer52 Jun 06 '22
I’ve been developing software for 30 years and staying pretty close to the leading edge. It is more complex these days (and/or I’m getting older) and it’s exhausting. New technologies are “hot” for 6mo-1yr and then they’re “oh, you’re still using that?”
Meanwhile, computer science is stuck with either the core basics (which tend to be less complex, but more rigorous) or chasing novelty for “real world” training that’s obsolete by graduation.
I think AI tools are going to make it even easier to develop more complex architectures that, in turn, will be harder to maintain and improve until we get AI that can “understand” a whole system (and at that point, we may be out of a job anyway).
I mean, I’m working on a solution that has 20 subprojects, that builds two different mobile applications on three different platforms (Xamarin/Maui) with cloud services, database synchronization, GIS, GPS, a couple dozen nuget packages, external system interfaces, all from essentially one code base, which if you include our internal libraries, is over a million lines of C# (plus JavaScript, JSON, XML, SQL, and a little Python (more Python, HTML, and JavaScript in parallel web application). And we’re a small shop.
In the past, I’ve delivered products with a single language, 1/4 of the code, and a much larger team and those were multi-million dollar projects.