I appreciate the intent behind that sentence, and the problem is that is written (or said) by people who don’t understand coding.
Syntax was never the hard part. Code syntax is a set of rules that you can teach a machine and it’s “easy” enough for an LLM to grasp it. The problem here is that this phrase does a “code = syntax” but ignoring all the difficult things that actually are in the code. Architecture, design, tradeoffs, translation of vague requirements into concrete software components…
All of those things are terribly hard, and the reason why many LLM-first coding projects get abandoned at 70% and then companies need to hire a Software Development consultancy to mop up their mess.
Interestingly what I’ve said here ☝️ ️comes with an interesting implication. There used to be a type of software “engineer” that couldn’t actually think through a problem and implement a good software solution. They were valuable because they could refactor, write code, but not think through a problem. These are the people who have the most to lose at the moment, and also the ones that find the least value on AI, because AI only does really well the single thing they could do.
That style of software developer used to be called “monkey coders”.
Employing “monkey coders” because they are cheaper is a great way to end up paying a lot more money over the long run because their work is unmaintainable, ureliable, not robust and stupidly hard to be upgraded to implement new requirements.
Which, if you think about it, it’s pretty much what you get with AI code.
And yeah, totally agree that these are the people who are most threatenned directly by AI at the moment. Then again, they were the ones most threatenned by outsourcing already (to India especially, since when they grew massive as an outsourcing place for software development they started hiring tons of people there who had no skill whatsoever for it and would never have gone into software development and were pretty bad, so most coders based in India were eventually this kind of code writter).
Hiring “monkey coders” was always the product of bad management: they looked good on paper - cheap, made lots of code, bums on seats, often the kind of person who worked long hours (which in low efficient management cultures makes a manager look good because of “making their people work hard”) - whilst creating massive costs spread over time and hitting everything from production downtime costs to future system improvement costs. In some ways the mass replacement of developers with AI is born from the same management incompetence as outsourcing, which is probably why it is hitting the US so hard.
Which brings us around to how, indirectly, even good software developers are right now threatened by AI - the kind of incompetent manager who thinks code lines is a productivity metric aren’t replacing just “monkey coders” with AI, they’re cutting down head-count with no selectivity or even replacing first the more professional coders because they’re the most expensive.
This might not be sustainable in the mid and long term because AI, like “code monkeys”, just piles up massive less obvious over-time costs on software systems (I expect a lot of companies will go under from this shit) and some are already getting desperate for the kind of professionals that can fix their self-inflicted AI problem, but people who aren’t prepared for up to two of being out of well paying software development jobs (so, most people) are getting screwed instead of aligning themselves to really profit from the wave of post-AI “oh, shit or systems are unreliable shit” work for senior types that’s just starting, plus if indeed as I expect companies will fail due to this, the Tech boom will be over and there will be fewer positions than there were 2 or 3 years ago.
I appreciate the intent behind that sentence, and the problem is that is written (or said) by people who don’t understand coding.
Syntax was never the hard part. Code syntax is a set of rules that you can teach a machine and it’s “easy” enough for an LLM to grasp it. The problem here is that this phrase does a “code = syntax” but ignoring all the difficult things that actually are in the code. Architecture, design, tradeoffs, translation of vague requirements into concrete software components…
All of those things are terribly hard, and the reason why many LLM-first coding projects get abandoned at 70% and then companies need to hire a Software Development consultancy to mop up their mess.
Interestingly what I’ve said here ☝️ ️comes with an interesting implication. There used to be a type of software “engineer” that couldn’t actually think through a problem and implement a good software solution. They were valuable because they could refactor, write code, but not think through a problem. These are the people who have the most to lose at the moment, and also the ones that find the least value on AI, because AI only does really well the single thing they could do.
That style of software developer used to be called “monkey coders”.
Employing “monkey coders” because they are cheaper is a great way to end up paying a lot more money over the long run because their work is unmaintainable, ureliable, not robust and stupidly hard to be upgraded to implement new requirements.
Which, if you think about it, it’s pretty much what you get with AI code.
And yeah, totally agree that these are the people who are most threatenned directly by AI at the moment. Then again, they were the ones most threatenned by outsourcing already (to India especially, since when they grew massive as an outsourcing place for software development they started hiring tons of people there who had no skill whatsoever for it and would never have gone into software development and were pretty bad, so most coders based in India were eventually this kind of code writter).
Hiring “monkey coders” was always the product of bad management: they looked good on paper - cheap, made lots of code, bums on seats, often the kind of person who worked long hours (which in low efficient management cultures makes a manager look good because of “making their people work hard”) - whilst creating massive costs spread over time and hitting everything from production downtime costs to future system improvement costs. In some ways the mass replacement of developers with AI is born from the same management incompetence as outsourcing, which is probably why it is hitting the US so hard.
Which brings us around to how, indirectly, even good software developers are right now threatened by AI - the kind of incompetent manager who thinks code lines is a productivity metric aren’t replacing just “monkey coders” with AI, they’re cutting down head-count with no selectivity or even replacing first the more professional coders because they’re the most expensive.
This might not be sustainable in the mid and long term because AI, like “code monkeys”, just piles up massive less obvious over-time costs on software systems (I expect a lot of companies will go under from this shit) and some are already getting desperate for the kind of professionals that can fix their self-inflicted AI problem, but people who aren’t prepared for up to two of being out of well paying software development jobs (so, most people) are getting screwed instead of aligning themselves to really profit from the wave of post-AI “oh, shit or systems are unreliable shit” work for senior types that’s just starting, plus if indeed as I expect companies will fail due to this, the Tech boom will be over and there will be fewer positions than there were 2 or 3 years ago.