201–210 of 464 posts
To me the part I enjoy most is making things. Typing all that nonsense out is completely incidental to what I enjoy about it.
So far as I can tell, generative AI coding tools make the easy part of the job go faster, without helping with the hard part of the job - in fact, possibly making it harder. Coding just doesn't take that much time, and I don't need help doing it. You could make my coding output 100x faster without materially changing my overall productivity, so I simply don't bother to optimize there.
Are you a plumber perhaps?
In contrast, when I’m trying to do something truly novel, I might spend days with a pen and paper working out exactly what I want to do and maybe under an hour coding up the core logic.
On the latter type of work, I find LLM’s to be high variance with mostly negative ROI. I could probably improve the ROI by developing a better sense of what they are and aren’t good at, but of course that itself is rapidly changing!
Earlier quoted context omitted.
Do you find your agent actually respecting the mdc file? I don’t.
There should be no difference between the mdc and the text in the prompt. Try something drastic like "All of responses should be in Chinese". If it doesn't happen, they're not included correctly. Otherwise, yeah, they work modulo the usual issues of prompt adherence.
Using them for larger bits of code feels silly as I find subtle bugs or subtle issues in places, so I don't necessarily feel comfortable passing in more things. Also, large bits of code I work with are very business logic specific and well abstracted, so it's hard to try and get ALL that context into the agent.
I guess what I'm trying to ask here is what exactly do you use agents for? I've seen youtube videos but a good chunk of those are people getting a bunch of typescript generated and have some front-end or generate some cobbled together front end that has Stripe added in and everyone is celebrating as if this is some massive breakthrough.
So when people say "regular tasks" or "rote tasks" what do you mean? You can't be bothered to write a db access method/function using some DB access library? You are writing the same regex testing method for the 50th time? You keep running into the same problem and you're still writing the same bit of code over and over again? You can't write some basic sql queries?
Also not sure about others, but I really dislike having to do code reviews when I am unable to really gauge the skill of the dev I'm reviewing. If I know I have a junior with 1-2 years maybe, then I know to focus a lot on logic issues (people can end up cobbling toghether the previous simple bits of code) and if it's later down the road at 2-5 years then I know that I might focus on patterns or look to ensure that the code meets the standards, look for more discreet or hidden bugs. With an agent output it could oscilate wildly between those. It could be a solidly written search function, well optimized or it could be a nightmarish sql querry that's impossible to untangle.
Thoughts?
I do have to say I found it good when working on my own to get another set of "eyes" and ask things like "are there more efficient ways to do X" or "can you split this larger method into multiple ones" etc
Earlier quoted context omitted.
I mostly just approve PRs because I trust my engineers. I have developed a 6th sense for thousand-line PRs and knowing which 100-300 lines need careful study. Yes I have been burned. But 99% of the time, with proper test coverage it is not an issue, and the time (money) savings have been enormous. "Ship it!" - me
I think this points out the crux of the difference of collaborating with other devs vs collaborating with am AI. The article correctly States that the AI will never learn your preferences or idiosyncrasies of the specific projects/company etc because it effectively is amnesic. You cannot trust the AI the same you trust other known collaborators because you don't have a real relationship with it.
> Another common argument I've heard is that Generative AI is helpful when you need to write code in a language or technology you are not familiar with. To me this also makes little sense. I'm not sure I get this one. When I'm learning new tech I almost always have questions. I used to google them. If I couldn't find an answer I might try posting on stack overflow. Sometimes as I'm typing the question their search wo…
What do you think will happen when everyone is using the AI tools to answer their questions? We'll be back in the world of Encyclopedias, in which central authorities spent large amounts of money manually collecting information and publishing it. And then they spent a good amount of time finding ways to sell that information to us, which was only fair because they spent all that time collating it. The internet pretty much destroyed that business model, and in some sense the AI "revolution" is trying to bring it back.
Also, he's specifically talking about having a coding tool write the code for you, he's not talking about using an AI tool to answer a question, so that you can go ahead and write the code yourself. These are different things, and he is treating them differently.
To some degree, traditional coding and AI coding are not the same thing, so it's not surprising that some people are better at one than the other. The author is basically saying that he's much better at coding than AI coding. But it's important to realize that AI coding is itself a skill that you can develop. It's not just , pick the best tool and let it go. Managing prompts and managing context has a much higher ski…
Is it a skill worth learning though? How much does the output quality improve? How transferable is it across models and tools of today, and of the future? From what I see of AI programming tools today, I highly doubt the skills developed are going to transfer to tools we'll see even a year from now.
From what I see of the tools, I think the skills developed largely consists of skills you need to develop as you get more senior anyway, namely writing detail-oriented specs and understanding how to chunk tasks. Those skills aren't going to stop having value.
My company just had internal models that were mediocre at best, but at the beginning this year they finally enabled Copilot for everyone.
At the beginning I was really excited for it, but it’s absolutely useless for work. It just doesn’t work on big old enterprise projects. In an enterprise environment everything is composed of so many moving pieces, knowledge scattered across places, internal terminology, etc. Maybe in the future, with better MCP servers or whatever, it’ll be possible to feed all the context into it to make it spit something useful, but right now, at work, I just use AI as search engine (and it’s pretty good at it, when you have the knowledge to detect when it have subtle problems)
Yep, this is pretty much it. However, I honestly feel that AI writes so much better code than me that I seldom need to actually fix much in the review, so it doesn't need to be as thorough. AI always takes more tedious edge-cases into account and applies best practices where I'm much sloppier and take more shortcuts.