A lot of it is perception. Writing software was long considered somewhat difficult and that it required smart people to do so.
AI changes this perception and coding starts to be perceived as a low level task that anyone can do easily with augmentation from AI tools.
I certainly agree that writing software is turning more into a factory job and is less intellectually rewarding now.
When I started working in the field (1996), I was told that I would receive detailed specs from an analyst that I would then "translate" into code. At that time this idea was already out of fashion, things worked this way for the core business team (COBOL on the AS/400) but in my group (internal tools, Delphi mostly) I would get only the most vague requirements.
Eventually everyone was expected to understand a good deal of the code they were working on. The analyst and the coder became the same person.
I'm deeply skeptical that the kind of people that enjoy software development are the same kind of people that enjoy steering and proofing LLM generated code. Unlike the analyst and the coder, this strike me as a very different skill set.
> I'm deeply skeptical that the kind of people that enjoy software development are the same kind of people that enjoy steering and proofing LLM generated code. Unlike the analyst and the coder, this strike me as a very different skill set.
indeed. people generally hate foreign/alien code, or rather - love their style too much. it is not hard to recognize this pattern - ive seen it with colleagues, with my students, with some topnotch 10x-coders back in the day. so proofing is a skill one perhaps develops by teaching others do things right, but is not something most people entertain about.
on the other hand, people who lack time and patience to implement complex stuff may benefit from this process. particularly if they are good code-readers, and some seasoned devs become such people. i can see little chance they wont be using llms to spit code out.
but the two groups largely don't overlap and are different as astronomers and astronauts.
For me it dependa on scale. Asking AI for something small and specific is a joy. Asking it to make a big change is a nightmare I so far only try every time a new model comes out.
Not everyone gets to code the next ground breaking algorithm at some R&D department.
Most programming tasks are rather repetitive, and in many countries there is hardly anything to look up to software developers, it is another blue collar job.
And in many cultures if you don't go into management after about five years, usually it is seen as a failure to grow up on their career.
Of course it is true. The thing was 90% of Amazon engineers made far more money at their job while essentially doing typical enterprise software work. This money led them believe it is some creative work. And now those task management and time monitoring tools are catching up to Amazon IT workers so they are realizing it is similar to another low end IT job/ factory work.
The pay and benefits at Amazon always seemed to offset the shit work/life balance and on-call rotation. What a gauntlet that was. The only engineers that got recognition were those that fixed high profile bugs, preferably after hours. Shipping a feature was always just "business as usual"
> if you don't go into management after about five years, usually it is seen as a failure to grow up on their career
I don't see how that's possible. Wouldn't such a norm result in something like a 7:1 ration of managers to engineers (i.e., assuming a 40ish year career, the first 5 years are spent as an engineer, and the remaining 35 as a manager)? For team managers, I've generally seen around a 1:10 ratio of engineers to managers. So a 7:1 ratio of managers to engineers just doesn't seem plausible, even including non-people leaders in management.
Have you wondered why japan, which is a powerhouse of electronics and manufacturing does not have any large software companies ?
Software is different from manufacturing.
The mindset, mentality, and culture required to do new software for an ambiguous problem is different from the mentality to produce boilerplate code or maintain an existing codebase. The later is pure execution and the former is more like R&D.
It means that the company is more likely to fire that person on the logic that they "failed" to be promoted to management, that they're "treading water" as a developer.
It's been like this for awhile now. Aside from companies like Google and Facebook, most companies are using some CRUD web app where the development consists of gluing code together for multiple third-party services and libraries.
It's these sorts of jobs that will be replaced by AI and a vibe coder, which will cost much less because you don't need as much experience or expertise.
Even before AI I've always had the perception that writing software felt more intellectually on the level of plumbing. AI just feels like a having one of those fancy new tools that tradespersons may use.
Yeah that’s what really worries me, many people have been clinging to this ability as something that’s really special and AI is really going to disillusion them.
