61–70 of 103 posts
there are "a few" problems with this. if you know how you want something done, tough luck. LLMs, even the "really smart" ones, still often do it "their way". they use "their style" (whatever the most common way to write something might be) and "their preferred packages" (what ever the most common ones for the language are). i remember someone told me "hey dude try vercel's v0 it's so good" and i asked it for some bas…
But then again, I have been doing this for 10 years; that is my edge. Same exact stack (Django + boring frontend). I know the ins and out of my stack, quite obviously every single day, I see AI go into a direction that I know is going to produce a huge footgun along the way. I can just see that up ahead, suggest a different approach, and continue. IF I was entirely new to this, I would end up building stuff that breaks down after weeks or months or investments, not knowing when things went wrong, or how to go forward. Regardless, I feel like my time has come, and I am definitely spending 95% of my time just prompting the AI versus writing actual code. Even for the most minor changes, like changing a CharField to a TextField, I don't even want to open the models.py myself. In Cursor, I am averaging 5000-7000 fast requests per month, because in terms of ROI it pays off. I am looking forward to this getting better.
For me, vibe coding is the only logical way forward. I see that the term gets a lot of flak. But in almost 10 years of writing web-applications for a living, this feels even more exciting then when I finally "got it". And its measurable, I am sitting on 5 completed web-apps with traffic just this year, working with 3 clients, and due to my ability to be this productive, feel like I have a very stable future ahead. I…
For me, vibe coding is the only logical way forward. I see that the term gets a lot of flak. But in almost 10 years of writing web-applications for a living, this feels even more exciting then when I finally "got it". And its measurable, I am sitting on 5 completed web-apps with traffic just this year, working with 3 clients, and due to my ability to be this productive, feel like I have a very stable future ahead. I…
As I said in one of my latest YT videos: if you can't code , sure, go all for it, the difference with x -> 0 in the denominator tends to infinity. But if you can code, there are much better ways to use generative AI to aid you in your coding tasks. Ways that will make you faster while you learn more, understand every single line of the code that is in your application, never letting badly written code go into your co…
on-topic: I have no desire to be a front-end dev but my friends don't know a front-end dev from a front-end loader, so whenever they need something thrown together i usually reach for Ghost or whatever. But now they want custom "web apps" - and that's fine, thank goodness for AI.
Most of my "LLM" use is remembering phrases, terms of art, and the like. I have used aider and Cursor, and they're about as useful to me as stackoverflow, i suppose. LLMs have definitely improved a lot, i don't get circular chats much except on Gemini, Gemini is the weakest LLM by far, which is ironic considering the extent of data they have.
Earlier quoted context omitted.
i'm glad they seem to work better for you. i sometimes seem to be the only person out there who can't get the same level of utility out of these models as others. my guess is for some applications they can, but even reasoning models (o3-mini-high, grok3, sonnet 3.7, o1, deepseek, etc.) often fail to fix logic bugs. note that this isn't necessarily a form validation logic bug I'm referring to but, say, a pretty in-the…
> even reasoning models [...] often fail to fix logic bugs. I think "often" is the key word here. To be clear, they often fail for me to! But they also often work.
> There are additional difficulties brought about by the economics of large scale production. Programmers have become "proletarianized". The elite expert programmer who crafted a system and stayed with it for many years, finely tuning it and adding new bells and whistles with ease, has by and large been superseeded by an entire generation of college graduates who were introduced to computing in their courses, and who…
That's hilarious! In 1974, that was decades from actually happening.
I wonder how many new developers will have legit panic attacks if their LLM of choice has an outage.
"I wonder how many new developers will have legit panic attacks if: * Slack is down * StackOverflow is down * their default docs website is down * their IDE of choice is being buggy and so they have to use something without autocomplete Life gets harder when assistive tools are lost, no matter what the tool.
It's interesting to see a lot of senior folks are against this arguing that if you're working on a larger software project this falls apart. Two things can be argued against this: 1. Context sizes are going to grow. Gemini with 2M tokens is already doing amazing feats 2. We all agree that we should break bigger problems into smaller ones. So if you can isolate the problem into something that fits in a LLM context, no…
You don't understand software engineering. The goal isn't to produce a bunch of code. The goals are actually: 1. Build a computable model of some facet of reality to an achieve certain goals. 2. Realize a system that manifests the model, satisfying a set of other constraints, such as resource constraints and performance. 3. Ensure a community of system owners comprehend the key decisions made in the system and model…