Model Evaluation and Threat Research is an AI research charity that looks into the threat of AI agents! That sounds a bit AI doomsday cult, and they take funding from the AI doomsday cult organisat…
Yeah, the glorious future where every half-as-good-as-expert developer is now only 25% as good as an expert (a level of performance also known as being “completely shit at it”), but he’s writing 10x the amount of unusable shitcode.
You scoff, but this is exactly the future CEOs and upper management absolutely want.
Why? Because labor is too expensive and “entitled” (wanting things like time off, health insurance, remote work, and so on).
They will do everything they can to squeeze labor and disempower the bargaining capability that knowledge workers have.
Why do you think Microsoft has been trying to screengrab everything that knowledge workers do? To train their models to do that work instead. Why did they just lay off thousands of workers and direct something like $80 billion towards AI investments?
You know why.
Quality doesn’t matter. Income minus expenses matter. You are an expense. They will do everything they can to replace you as soon as they catch even a whiff of economic viability (or even before), because even if it’s more costly right now, it can drive down labor costs by putting the squeeze on employees.
But when a mid-tier or entry level dev can do 60% of what a senior can do
This simply isn’t how software development skill levels work. You can’t give a tool to a new dev and have them do things experienced devs can do that new devs can’t. You can maybe get faster low tier output (though low tier output demands more review work from experienced devs so the utility of that is questionable). I’m sorry but you clearly don’t understand the topic you’re making these bold claims about.
Even pre AI I had to deal with a project where they shoved testing and compliance at juniors for a long time. What a fucking mess it was. I had to go through every commit mentioning Coverity because they had a junior fixing coverity flagged “issues”. I spent at least 2 days debugging a memory corruption crash caused by such “fix”, and then I had to spend who knows how long reviewing every such “fix”.
And don’t get me started on tests. 200+ tests, of them none caught several regressions in handling of parameters that are shown early in the frigging how-to. Not some obscure corner case, the stuff you immediately run into if you just follow the documentation.
With AI all the numbers would be much larger - more commits “fixing coverity issues” (and worse yet fixing “issues” that LLM sees in code), more so called “tests” that don’t actually flag any real regressions, etc.
For now.
But when a mid-tier or entry level dev can do 60% of what a senior can do, it’ll be a great way to cut costs.
I don’t think we’re there now. It’s just that that’s the ultimate goal - employ fewer people, and pay the remaining people you do employ less.
Yeah, the glorious future where every half-as-good-as-expert developer is now only 25% as good as an expert (a level of performance also known as being “completely shit at it”), but he’s writing 10x the amount of unusable shitcode.
You scoff, but this is exactly the future CEOs and upper management absolutely want.
Why? Because labor is too expensive and “entitled” (wanting things like time off, health insurance, remote work, and so on).
They will do everything they can to squeeze labor and disempower the bargaining capability that knowledge workers have.
Why do you think Microsoft has been trying to screengrab everything that knowledge workers do? To train their models to do that work instead. Why did they just lay off thousands of workers and direct something like $80 billion towards AI investments?
You know why.
Quality doesn’t matter. Income minus expenses matter. You are an expense. They will do everything they can to replace you as soon as they catch even a whiff of economic viability (or even before), because even if it’s more costly right now, it can drive down labor costs by putting the squeeze on employees.
And that is the point.
Okay but that is different from the argument that entry developers only need to be half as good to deliver a working product
Same as how an entry level architect can build a building 60% as tall, and that’ll last 60% as long, right?
Edit: And an entry level aerospace engineer with AI assistance will build a plane that’s 60% as good at not crashing.
I’m not looking forward to the world I believe is coming…
Get 2 and the plane will be 120% as good!
In fact if children with AI are a mere 1% as good, a school with 150 children can build 150% as good!
I am sure this is how project management works, and if it is not maybe Elon can get Grok to claim that it is. (When not busy praising Hitler.)
this brooks no argument and it’s clear we should immediately throw all available resources at ai so as to get infinite improvement!!~
(I even heard some UN policy wonk spout the AGI line recently 🙄)
is there like a character sheet somewhere so i can know where i fall on this developer spectrum
It’s going to be your INT bonus modifier, but you can get a feat that also adds the WIS modifier
For prolonged coding sessions you do need CON saving throws, but you can get advantage from drinking coffee (once per short rest)
I must have picked up a feat somewhere because I hit that shit way more than once per short rest
This simply isn’t how software development skill levels work. You can’t give a tool to a new dev and have them do things experienced devs can do that new devs can’t. You can maybe get faster low tier output (though low tier output demands more review work from experienced devs so the utility of that is questionable). I’m sorry but you clearly don’t understand the topic you’re making these bold claims about.
I think more low tier output would be a disaster.
Even pre AI I had to deal with a project where they shoved testing and compliance at juniors for a long time. What a fucking mess it was. I had to go through every commit mentioning Coverity because they had a junior fixing coverity flagged “issues”. I spent at least 2 days debugging a memory corruption crash caused by such “fix”, and then I had to spend who knows how long reviewing every such “fix”.
And don’t get me started on tests. 200+ tests, of them none caught several regressions in handling of parameters that are shown early in the frigging how-to. Not some obscure corner case, the stuff you immediately run into if you just follow the documentation.
With AI all the numbers would be much larger - more commits “fixing coverity issues” (and worse yet fixing “issues” that LLM sees in code), more so called “tests” that don’t actually flag any real regressions, etc.