Comment by mooreds

> Old days: Get the O'Reilly book for that programming language. Lookup access modifiers in the index. 10 year ago: Google for a blog with an intro to the programming language. There will be a tip about what access modifiers can do. Today: Ask ChatGPT.

The answer to this (throughout the ages) should be the same: read the authoritative source of information. The official API docs, the official language specification, the man page, the textbook, the published paper, and so on.

Maybe I am showing my age, but one of the more frustrating parts of being a senior mentoring a junior is when they come with a question or problem, and when I ask: “what does the official documentation say?” I get a blank stare. We have moved from consulting the primary source of information to using secondary sources (like O’Reilly, blogs and tutorials), now to tertiary sources like LLMs.

> I can assure you that when I was young, I did not listen to older people's advice and I tried to do everything my own way.

Hot take: This reads like a person who was difficult to work with.

Senior people have responsibility, therefore in a business situation they have authority. Junior people who think they know it all don't like this. If there's a disagreement between a senior person and a junior person about something, they should, of course, listen to each other respectfully. If that's not happening, then one of them is not being a good employee. But if they are, then the supervisor makes the final call.

> Old days: Get the O'Reilly book for that programming language. Lookup access modifiers in the index. 10 year ago: Google for a blog with an intro to the programming language. There will be a tip about what access modifiers can do. Today: Ask ChatGPT. In my (somewhat contrived) example, the how is changing, but not the what.

The tangent to that is it is also changing with the how much one internalizes about the problem domain and is able to apply that knowledge later. Hard fought knowledge from the old days is something that shapes how I design systems today.

However, the tendency of people who reach for ChatGPT today to solve a problem results in them making the same mistakes again the next time since the information is so easy to access. It also results in things that are larger are more difficult... the "how do you architect this larger system" is something you learn by building the smaller systems and learning about them so that their advantages and disadvantages and how and such becomes an inherent part of how you conceive of the system as a whole. ... Being able to have ChatGPT do it means people often don't think about the larger problem or how it fits together.

I believe that is harder for a junior who is using ChatGPT to advance to being a mid level or senior developer than it is for a junior from the old days because of the lack of retention of the knowledge of the problems and solutions.

Yeah Ive got to agree with this hot take. Put yourself in the junior's shoes: if s/he wasn't there you'd be pulling it out of Claude Code yourself, until your satisfied with what comes out enough to start adding your "senior" touches. The fact is the way code is written has changed fundamentally, especially for kids straight out of college, and the answer is to embrace that everyone is using it, not all this shaming. If you're so senior, why not show the kid how to use the LLM right, so the work product is right from the start? It seems part of the problem is dinosaurs are suspicious of the tech, and so dont know how to mentor for it. That being said, Im a machine learning engineer not a developer, and these LLMs have been a godsend. Assuming I do it correctly, there's just no way I could write a whole 10,000 line pipeline in under a week without it. While coding from outputs and error-driven is the wrong way for software Juniors, its fine by me for my AI work. It comes down to knowing when there's a silent error, if you haven't been through everything line by line. I've been caught before, Im not immune, its embarrassing, but every since GPT was in preview I have made it my business to master it.

I have a friend who is a dev, a very senior one at that, who spins up 4 Claudes at once and does the whole enterprises work. Hes a "Senior AI Director" with nobody beneath him, not a single direct report, and NO knowledge of AI or ML, to my chagrin.

So now I'm whining too...

I think GP may be thinking that emojis in PR comments (plus the other red flags they mentioned) are the result of copy/paste from LLM output, which might imply that the person who does mindless copy/pasting is not adding anything and could be replaced by LLM automation.

The point is that heavy emoji use means AI was likely used to produce a changeset, not that emojis are inherently bad.

The emojis are not a problem themselves. They're a warning sign: slop is (probably) present, look deeper.

My favorite prompt is "your goal is to retire yourself"