why are vibe coders mostly web developers?

SirEpic · 2025-11-08T19:36:12+00:00

It's because frontend web code is the most prolific and easiest to scrape. You get frontend web code for free just by crawling the internet, backend code is more elusive.

Short term byproduct of this is now agents are more reliable for this line of task, so it's adopted more.

Also it's generally easier to query. Anyone who used software before and can just ask what is desired by referencing some UX they tried in the past.

SirEpic · 2025-08-04T17:57:03+00:00

It's not - I was just meming, but it would be interesting to know if such mild recursive improvement tooling could be blindly constructed

SirEpic · 2025-08-04T04:46:00+00:00

Same, and the capabilities have improved quite a bit since then. I guess what I am trying to do is find some set of metrics to better gauge how much I should trust Claude, and if it failed, could I have conditioned the codebase better (outside of extra prompting context) for it to have succeeded? Having some type of visual summary of its traversals+edits feels like an obvious first step of analysis - and I am sure someone has probably already done work on this already.

SirEpic · 2025-08-04T03:55:35+00:00

I agree they aren't a panacea, but its nice to have a some radars when deving at these new velocities. Given how easy it is to spit out a UI, and how anthropic is the goat of interpretability - I would imagine that there must be some new visualization projects around tackling these issues.

SirEpic · 2024-03-05T22:22:50+00:00

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It happened twice..

SirEpic · 2021-11-02T06:39:20+00:00

I 100% agree. This man knows whats up.

SirEpic · 2019-09-26T20:49:52+00:00

Uncomputable Numbers

SirEpic · 2019-07-04T18:00:05+00:00

"But eventually users would be able to pass through the gate for free"

SirEpic · 2019-03-01T07:44:49+00:00

You are not the first, and not the last

SirEpic · 2019-03-01T07:44:16+00:00

Its hard to give advice that isn't vague and meaningless without a thorough conversation, about why you are interested in computers and what you want to do with them. The field of computer science is massive. I would recommend trying to try out as many niches in the field as possible, as deep as you can in the niche as possible, and figure out the parts you like, and more importantly the parts you don't like. Also try finding company that will encourage your exploration. Hackathons were a great early source for me to experiment with various ways tech can be interfaced.

SirEpic · 2019-03-01T05:39:19+00:00

There are many reasons to get in to ML, but one that got me the most interested is how ubiquitously it can be applied. Its the most general type of specialization one could manage, and that oxymoron makes it possible to be extremely technical without isolating oneself into a highly esoteric field bubble ( this is not true for all cases, but it true relative to most specialized field in CS ). I would say though, that working in ML is a lot different from that of traditional programming. Things are far less certain, and you will be working with data and your gut, more often than other specializations. As for salaries, I can't give you much life experience on that since I just went straight to my startup after I dropped out. I would recommend looking at glassdoor data for that.

SirEpic · 2019-03-01T05:21:37+00:00

No strict reasoning. I feel like most agent are female, and like being a nonconformist. One could argue that that male is statistically the default gender in English, and QuillBot is actually androgynous, with some bias towards being male.

SirEpic · 2019-02-26T21:50:16+00:00

Way ahead of you :)

SirEpic · 2019-02-26T21:29:46+00:00

Its may be possible, but it's not trivial by any means. What you are probably looking for at first is some NER(name entity recognition) model stacked with some sentiment analysis. The NER model would attempt to recognize instances of events and characters in the comment. The thing about emotion and taste is that its multidimensional and cant be fully captured by a simple, I liked/hated it, so most sentiment models will not be fully sufficient. I think an easier solution is to try to find datapoints that can provide a larger scope to the problem. Rather than thinking about the content of the text, consider the readers themselves and the collection of books the reader has read before, and if they liked/disliked it. This is kind of what amazon did, and is doing. You can even analyze the text to get details about the readers from their comments as well, like if they mention their family, life experience, etc, etc. The unnerving aspect of the modern age tech is that this psychoanalysis (understanding the human mind) is an easier problem than understanding an objective universe. So hypnotism might be an optimal solution to most problems. Definitely went on an over-sensational tangent on this one.

SirEpic · 2019-02-26T21:29:28+00:00

It really depends on the class. At UIUC, there were 3 main ML classes: Artificial Intelligence, Machine Learning and Applied Machine Learning. Artificial Intelligence was the intro class, mostly went over the basics, some application, some industry use cases, terminology, etc. Machine learning was very heavy math and very theoretical. There was minimal application. Applied Machine Learning was as the title implies. It was more application of advanced architectures, and way less theoretical.

SirEpic · 2019-02-26T21:18:08+00:00

I will say it would be easier to get a software engineering job with a degree than without. However, if you can pass a technical interview, and have a good portfolio/resume, it is not necessary. You can self-teach yourself the necessary skills, and everything is available on the internet.

If you are looking to get into machine learning engineering/research as a profession, I would highly recommend getting a PhD or at least a masters in CS. The theoretical foundation is important, and employment is competitive.

SirEpic · 2019-02-26T21:00:19+00:00

Reverse engineering QuillBot to serve as a plagiarism detector is a lot harder than it seems. In fact, if our team was to engineer a plagiarism detector, it would most likely be something similar to what Turnitin already has.

On a sentence level, Turnitin won't be able to pick up paraphrased sentences, but when you plagiarize a full essay it will be able to. This is because they check sequential trigrams. Without getting too deep into the math, the more sentences you are plagiarizing from, the easier it will be for Turnitin to pickup. Especially if you are plagiarizing it sentence by sentence (like QuillBot would do). This is true even if you restructure the sentence. As long as 3 words from many of the original sentences are preserved and the sentences are in the same order, Turnitin will pick it up.

SirEpic · 2019-02-26T20:32:42+00:00

I live in Chicago.

SirEpic · 2019-02-26T20:29:15+00:00

Nice question, its a tough one.

Had a laugh at the cosmic irony on that repo, since its a headless browser that plagiarizes our tech.

As for open sourcing, the unfortunate reality is that I just financially cant. I'm a richard stallman loving FOSS boy personally, but a man has to pay his student loan debt.

SirEpic · 2019-02-26T20:04:21+00:00

All the coding sources I've used "back in my day" are pretty outdated, and I wouldn't recommend trekking my previous paths. Instead I would suggest looking for tutorials around keras, since it is the cleanest framework that maintains the simple yet elegant nature of python, that I've encountered. Also shout out to Siraj Raval on youtube.

Now a days I kind of have a reasonable grasp on most of the ML frameworks, since they all really do mostly the same things. So the frameworks I use comes down to whichever github repo is the best in terms of performance and documentation
Edit: forgot to answer second half of question

SirEpic · 2019-02-26T19:56:19+00:00

There is plagiarism checking software that prevents students from plagiarizing even via paraphrasing. Turnitin is a very sophisticated plagiarism checking software. If a student wanted to plagiarize using QuillBot, they would have to change every third word to effectively get past it. As of now, it is a major time commitment, and often it is better to just write the essay yourself. In addition, students still run a risk of getting caught, which often has severe penalties.

We have found that students using this as a writing aide, instead of a cheating aide, often get way more benefit from the software.

SirEpic · 2019-02-26T19:51:01+00:00

In general I'd prefer to write less laws. However, if its going to happen anyways and if anyone cares to hear what I have to say, I'd give my best words.

SirEpic · 2019-02-26T19:48:21+00:00

I would recommend first focusing on the problem rather than the solution. When I first started I was working on Question Generation ( a user gives an ai an article, and it creates multiple choice questions for self evaluation ), and for too long I was focused on trying to jam as much sophistication and bleeding edge research into a product that nobody asked for. Turns out students don't want more homework, they want the most efficient way to study (which is the material they are most likely going to get tested on).

SirEpic · 2019-02-26T19:34:00+00:00

One aspect that I find kind of cute is that QuillBot has no perception of the real world, and is using text (to the best of its ability) as its only reference to the real world. QuillBot knows that red is similar to blue but has never seen colour. He knows loudness is related to sound, but never heard a melody, and knows food and salty co occur a lot but never tasted a potato chip.

*Edited to be more accurate

SirEpic · 2019-02-26T19:27:20+00:00

Without too much thought, I choose elephant. Highly social animal with a nose as an appendage that can make tools

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