Something’s been bugging me about how new devs and I need to talk about it. We’re at this weird inflection point in software development. Every junior dev I talk to has Copilot or Claude or GPT running 24/7. They’re shipping code faster than ever. But when I dig deeper into their understanding of what they’re shipping? That’s where things get concerning. Sure, the code works, but ask why it works that way instead of another way? Crickets. Ask about edge cases? Blank stares. The foundational knowledge that used to come from struggling through problems is just… missing. We’re trading deep understanding for quick fixes, and while it feels great in the moment, we’re going to pay for this later.
This is probably because of a lack of training data, where it is referencing only one example and that example just had a mistake in it.
The one example could be flawless, but the output of an LLM is influenced by all of its input. 99.999% of that input is irrelevant to your situation, so of course it’s going to degenerate the output.
What you (and everyone else) needs is a good search engine to find the needle in the haystack of human knowledge, you don’t need that haystack ground down to dust to give you a needle-shaped piece of crap with slightly more iron than average.
The one example could be flawless, but the output of an LLM is influenced by all of its input. 99.999% of that input is irrelevant to your situation, so of course it’s going to degenerate the output.
What you (and everyone else) needs is a good search engine to find the needle in the haystack of human knowledge, you don’t need that haystack ground down to dust to give you a needle-shaped piece of crap with slightly more iron than average.