| I’ve come to the same conclusion in regards to my own learning, even after 15 years doing this. When I want a quick hint for something I understand the gist of, but don’t know the specifics, I really like AI. It shortens the trip to google, more or less. When I want a cursory explanation of some low level concept I want to understand better, I find it helpful to get pushed in various directions by the AI. Again, this is mostly replacing google, though it’s slightly better. AI is a great rubber duck at times too. I like being able to bounce ideas around and see code samples in a sort of evolving discussion. Yet AI starts to show its weaknesses here, even as context windows and model quality has evidently ballooned. This is where real value would exist for me, but progress seems slowest. When I get an AI to straight up generate code for me I can’t help but be afraid of it. If I knew less I think I’d mostly be excited that working code is materializing out of the ether, but my experience so far has been that this code is not what it appears to be. The author’s description of ‘dissonant’ code is very apt. This code never quite fits its purpose or context. It’s always slightly off the mark. Some of it is totally wrong or comes with crazy bugs, missed edge cases, etc. Sure, you can fix this, but this feels a bit too much like using the wrong too for the job and then correcting it after the fact. Worse still is that in the context of learning, you’re getting all kinds of false positive signals all the time that X or Y works (the code ran!!), when in reality it’s terrible practice or not actually working for the right reasons or doing what you think it does. The silver lining of LLMs and education (for me) is that they demonstrated something to me about how I learn and what I need to do to learn better. Ironically, this does not rely on LLMs at all, but almost the opposite. |
Is this "AI is good" or "Google is shit" or "Web is shit and Google reflects that"?
This is kind of an important distinction. Perhaps I'm viewing the past through rose-tinted glasses, but it feels like searching for code stuff was way better back about 2005. If you searched and got a hit, it was something decent as someone took the time to put it on the web. If you didn't get a hit, you either hit something predating the web (hunting for VB6 stuff, for example) or were in very deep (Use the Source, Luke).
Hmmm, that almost sounds like we're trying to use AI to unwind an Eternal September brought on by StackOverflow and Github. I might buy that.
The big problem I have is that AI appears to be polluting any remaining signal faster than AI is sorting through the garbage. This is already happening in places like "food recipes" where you can't trust textual web results anymore--you need a secondary channel (either a prep video or a primary source cookbook, for example) to authenticate that the recipe is factually correct.
My biggest fear is that this has already happened in programming, and we just haven't noticed yet.