some long term projects were due to the tons of details in source code, but some were due to inherent complexity and how to model something that works, no matter what the files content will be
I enjoy when: Things are simple. Things are a complicated, but I can learn something useful. I do not enjoy when: Things are arbitrarily complicated. Things are a complicated, but I'm just using AI to blindly get something done instead of learning. Things are arbitrarily complicated and not incentivized to improve because now "everyone can just use AI" It feels like instead of all stepping back and saying "we need to simplify things" we've doubled down on abstraction _again_
One concern is those less experienced engineers might never become experienced if they’re using AI from the start. Not that everyone needs to be good at coding. But I wonder what new grads are like these days. I suspect few people can fight the temptation to make their lives a little easier and skip learning some lessons.
> I feel like I can manage the entire stack again - with confidence. By not managing anything? Ignorance is bliss, I guess. I understand it. I've found myself looking at new stacks and tech, not knowing what I didn't know, and wondering where to start. But if you skip these fundamentals of the modern dev cycle, what happens when the LLM fails?
As someone that only has sporadic pockets of deep time in my free time the thing that has been immensely helpful from an LLM coding point of view is mental model building. I can now much more easily get "into the flow" after being away from a codebase for a period of time by asking questions. For example, remind me where all the integration points for that API route is located. Or give me a rundown on this file. Etc.. It gets me back up to speed so much more quickly and makes me productive with limited amounts of time. It also means I don't have to try to carry this context around with me or I'll forget it.
With all due respect you were reading, not learning. It's like when people watch educational YouTube videos as entertainment, it feels like they're learning but they aren't. It's fine to use the LLMs in the same way that people watch science YouTube content, but maybe don't frame it like it's for learning. It can be great entertainment tho.
The YouTube analogy doesn't completely hold. It's more like jumping on a Zoom screen sharing session with someone who knows what they're doing, asking for a tailored example and then bouncing as many questions as you like off them to help understand what they did. There's an interesting relevant concept in pedagogy called the "Worked example effect", https://en.wikipedia.org/wiki/Worked-example_effect - it suggests that showing people "worked examples" can be more effective than making them solve the problem themselves.
Disagree, it can be learning as long as you build out your mental model while reading. Having educational reading material for the exact thing you're working on is amazing at least for those with interest-driven brains. Science YouTube is no comparison at all: while one can choose what to watcha, it's a limited menu that's produced for a mass audience. I agree though that reading LLM-produced blog posts (which many of the recent top submissions here seem to be) is boring.
I agree with this. I've been able to tackle projects I've been wanting to for ages with LLMs because they let me focus on abstractions first and get over the friction of starting the project. Once I get my footing, I can use them to generate more and more specialized code and ultimately get to a place where the code is good.
100% the opposite. LLMs lack high level creativity, wisdom and taste. Being a generalist is how you build these. For example, there's a common core to music, art, food, writing, etc that you don't see until you've gotten good at 3+ aesthetic fields. There are common patterns in different academic disciplines and activities that can supercharge your priors and help you make better decisions. LLMs can "see" these these connections if explicitly prompted with domains and details, but they don't seem to reason with them in mind or lean on them by default. On the other hand, LLMs are being aggressively RL'd by the top 10% of various fields, so single field expertise by some of the best in the world is 100% baked in and the default.