One more thing to add: AI enhances capabilities of everyone, including juniors. Juniors with LLMs can do more than juniors without them could and therefore their value proposition is greater than before.
Today’s juniors still learn the same core skill, the abstract thinking and formalization of a problem is still there. It’s just done on a higher level of abstraction and in an explicitly formulated natural language instead of a formal one for the first time ever. They’re not even leaving out the formal one completely, because they need to integrate and fine tune the code for it to work as needed.
Does it introduce new problems? Sure. Does it mean that today’s juniors will be less capable compared to today’s seniors once they have the same amount of experience? I really doubt it.
Not the same. Whether you are writing Assembly or Java, you have to determine and express your intent with high accuracy - that is a learned skill. Providing problem details to an LLM until it produces something that looks correct is not the same type of skill.
If that is the skill that the business world demands in 5 years, so be it, but arguing that it's simply the next step in the Assembly, C, Java progression makes no sense.
If you're using LLMs to code like this, you're using them incorrectly. You need to specify your intent precisely from the start which is a skill you learn. You can use other tools like OOP languages incorrectly with "working" results as well, that's why code quality, clean code and best practices are a thing.
I'm sure many junior developers use LLMs the way you described but maybe that's exactly what the universities and seniors need to teach them?
Or maybe I'm wrong and we're all headed for a future of being prompt engineers.
I was a sceptic up until recently, where I failed to create a solution myself.
Since I am mostly a hobbyist programmer(for 25 years and counting) I often find I don’t have the time to sit down for prolonged periods to reason about my code.
ChatGPT helps my tired brain from work develop my code 10x quicker, easily, by removing road blocks for me.
I find it an excellent tool.
This is a senior-level view. Juniors don't have this skill yet, and is one of the things we're concerned they won't pick up.
That's at least my experience working with multiple digital agencies and seeing it all unfold. Most juniors don't last long these days precisely because they skip the part that actually makes them valuable - storing information in their head. And that's concerning, because if to make actually good use of AI you have to be an experienced engineer, but to become an experienced engineer you had to get there without AI doing all your work for you, then how are we going to get new experienced engineers?
The nerdy tinkerers stay the same and AI empowers them even more. Are they rare? Yes. But this shifts the topic from science/engineering to economics/sociology. Granted, that was the topic of the original submission but for me that’s the less interesting part.
Wildly debatable
> Juniors with LLMs can do more than juniors without them could
Except that being juniors they lack the critical skills to understand when code produced by AI is trash
If Seniors are too busy babysitting the AI, then no.
I disagree. LLM assisted coding is yet another level of abstraction. It’s the same thing as an assembly programmer saying that OOP programmers don’t learn from OOP coding.
Today’s juniors still learn the same core skill, the abstract thinking and formalization of a problem is still there. It’s just done on a higher level of abstraction and in an explicitly formulated natural language instead of a formal one for the first time ever. They’re not even leaving out the formal one completely because they need to integrate and fine tune the code for it to work as needed.
Does it introduce new problems? Sure. Does it mean that today’s juniors will be less capable compared to today’s seniors once they have the same amount of experience? I really doubt it.
One can be confident that they wrote correct Java code without knowing what the JVM machine code output is. But you can't know if the code outputted by an LLM is correct without understanding the code itself.
I'm sure there're some pretty major bugs in production code because someone used some Java functionality intuitively without understanding it fully and in some edge case it behaves differently than anticipated.
Of course this issue is much more prominent in LLM assisted coding but we're back to square one. The higher the level of abstraction provided by the tool, the more room for mistakes it leaves but the higher the productivity is. It's easier to avoid bugs of this type when using assembly vs when using Java.