camdenreslink

I have had to force quit Spotify a couple times recently because it was using many GB of memory to the point where it was unresponsive.

Agreed, considering "taste" to only mean UX or aesthetics is taking things too literally in my opinion.

It does make you wonder if the July shedding of jobs could be lowered even further to ~100k+ jobs lost (since they revise down very consistently).

You can be 10x more productive if you don’t verify anything the LLM generates and just YOLO it into your codebase. I wouldn’t recommend it.

Is this actually happening anywhere in a medium-large business with an established product and real customers?

You overestimate the average person

The interesting question is "Which problems are LLMs good at solving, and which problems are LLMs bad at solving?", which could also be restated as "Which problems are cheap for an LLM to solve?". So cost is relevant here.

If the prompt was crafted by an expert mathematician with pages of context and insights provided to the LLM to put it on the right path, that is a lot less impressive than a prompt that just says "find a counterexample to this conjecture".

Similarly, if they are spending millions of dollars in inference just churning on thousands of problems and these are the 10 solutions they came up with, that would be less impressive than if they chose these 10 problems specifically and were able to come up with solutions.

Hey, thanks for trying my thing! The first couple of steps in the project are sort of "welcome/intro" steps. Once you move a few steps forward then you will actually be in the spider project code.

I'm wondering if it might be better to get rid of these introduction steps and just drop the user directly into the project. Or maybe it's just an issue with this project where I've mentioned `import spider` directly in the welcome step when it can't be used yet.

Either way, thanks for the feedback, I'll make some sort of change to make things less confusing!

This is very cool, I've never heard of Scastie, I'll need to take a closer look at that. I created a similar platform for Python (actually submitted to HN earlier today: https://news.ycombinator.com/item?id=49083146)

The subtext of this whole post (or at least a subtext that some might read), is "we don't need mathematicians/programmers anymore" or "we will need much fewer mathematicians/programmers". So the fact that this result required a year of prior research and a 10 page prompt of specialized knowledge goes against that subtext. You still needed the human just as much to get to the result, and the LLM ended up being a tool to find the last bit.

I wonder about his marketing channels. If it was primarily SEO, that has taken a huge hit especially for programming related searches since AI answers showed up at the top of the SERP.

Really depends on the suburb. Where I live in NYS (a suburb of Buffalo) all of those things are within walking distance if you live within the village limits.

In some languages you can create a type that is equivalent to a string, but it’s own distinct type (sometimes called the New Type pattern). Which I guess is the same as a struct with a single field, but languages have syntactic sugar, and depending on implementation doesn’t allocate another extra wrapper object on the heap (this would happen in JavaScript/TypeScript).

I had a repeatable process set up with o4-mini that gave very good results. It generated output in a structured format, and the results were fairly formulaic but good. I did a lot of runs of this process and observed a lot of output.

I set that process down for like 4 or 5 months and then came back to it after GPT 5 came out. o4-mini was literally unusable. I've seen it with my own eyes.

Yea, more likely for the majority of the code nobody reviewed it. It was over a million line diff.

Most people have no need for a SOTA model, and even a model from a year ago would be fine for their needs (a little bit of research, small bits of writing prose, etc).

It's true for computer science and any STEM discipline. Even if the PhD eventually does account for increased wages (it often doesn't), you usually have to work decades at that higher rate to make up the foregone wages.

I would only ever get a PhD due to intrinsic interest, or if it unlocks a specific type of job I want that would be unavailable without it. It's a bad investment to get a PhD to get higher wages (in America, I don't know the labor market in other countries).

I think it just depends on the workflow. A lot of times (probably the majority of the time) a well crafted deterministic process is what people want.

Sometimes you can have a multistep deterministic workflow with a decision that needs made somewhere in the middle, which is where an LLM that can call tools is useful.

I think there are much less repeated tasks where you would want a fully agentic process (but there are many ad hoc tasks where that is exactly what you want).

The real best case scenario is using LLMs to help build deterministic systems. Instead of asking an LLM to do some task that you know will be repeated, instead ask the LLM to build a program (Python script or whatever) to do the task.

Getting a PhD is almost never worth the foregone wages if your goal is to be in private industry. For sure, people should get one if they are interested in research, or specific jobs that are only available to people with PhDs. But otherwise it isn't something to get into half-hearted.

I agree, it seems like the current most popular languages and frameworks will become ossified, because they have the highest amount of training data. It's hard to see a future where Python and JavaScript aren't the most popular languages to use (assuming LLM-assisted development is the norm moving forward).

> many are doing class-wide weighted adjustments

Isn't this just grading on a curve, which has been done probably as long as universities have existed? The key is the instructor making sure a high standard is met (which seems to be the crux of the issue).

You should probably use software to do such large transformations (especially in dynamic languages). In Python LibCST is available, not sure what exists for Ruby.

I'm sure the many software engineers employed in his companies love to hear that.

I think you agree with me? It is unambiguously associated with PricewaterhouseCoopers.

To be fair PwC is a very well established initialism. It would be like saying HTTP but actually referring to something other than the well understood meaning of that thing.

Humans also make mistakes in ways that other humans can understand or expect. Sometimes LLMs make mistakes in a way that makes you say “no human would have ever done that”.

The original post said “in college”. It might be true for PhD candidates halfway through their program, but that’s like 0.5% of college students. The vast majority of students are leagues behind their instructors in domain knowledge.

People game benchmarks for fake internet points to get their favorite web framework to the top of the list. I'm pretty sure they will do it for billions of dollars.