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I've been experimenting with model-based development lately, and this resonated strongly with me.

The section "What Even Is Programming Anymore?" hit on a lot of the thoughts and feels I've been going through. I'm using all my 25+ years of experience and CS training, but it's _not_ programming per se.

I feel like we're entering an era where we're piloting a set of tools, not hand crafting code. I think a lot of people (who love crafting) will be leaving the industry in the next 5 years, for better or worse. We'll still need to craft things by hand, but we're opening some doors to new methodologies.

And, right now, those methodologies are being discovered, and most of us are pretty bad at them. But that doesn't mean they're not going to be part of the industry.



> I think a lot of people (who love crafting) will be leaving the industry in the next 5 years, for better or worse.

I think you're spot on. It was once necessary to acquire knowledge in order to acquire productivity. This made knowledge valuable and worth attaining. Now, with LLMs, we we can skip the middle man and go straight to the acquisition of productivity. I'd call it the democratisation of knowledge, but it's something more than that — knowledge just isn't needed anymore.


This kind of makes sense. I love acquiring knowledge, just for knowledges sake. That’s why I got into math and programming in the first place. I just like learning stuff. It was a happy accident that the stuff I like doing happens to also be lucrative. Kind of sucks that all that stuff I spent my life doing is losing value by the day. I love programming because there are an endless amount of things to learn. I actually care very little about the productivity.


Which makes me wonder: why shouldn't AI use be a core part of technical interviews now? If we're trading "knowledge of how to code" for "knowledge of how to use LLMs" and treating Claude like a much more productive junior engineer, do we still need to filter candidates on their ability to write a doubly linked list? And if we are still asking those sorts of interview questions, why shouldn't candidates be able to use LLMs in the process? After all, like others have said elsewhere in this thread, you still need some core technical capabilities to effectively manage the AI. It's just a tool and we can judge how well someone knows how to use it or not.


There's a fundamental problem with your question, which is the suggestion that technical interviews are still needed at all. Technical roles can be replaced with roles that are more akin to production managers, and we should absolutely be testing those candidates for LLM competency.


> knowledge just isn't needed anymore

I would argue we still need the knowledge: the principles aren't changing, and they are needed to be truly productive in certain things. But the application of those principles _are_ changing.




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