nyrulez

Joined 15 years ago

Karma
865
Submissions
280
Member since
Apr 7
I'm a Former Google/Wall Street engineer/data scientist. Founder of polymersearch.com

Passionate about programming, advancing technology, finance/investments, video games (PC/Nintendo Switch/PS5), VR, data-science, fitness (HIIT), fixing my ADHD/improving focus, quantified self, spirituality, non-duality and detachment.

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Recent submissions

Comment · 7 months ago
Bold claims that writing code was never the bottleneck. It may not be the only bottleneck but we conveniently move goal posts now that there is a more convenient mechanism and our profession is under threat.
Comment · 1 year ago
Things haven't changed much in terms of truly new ideas since electricity was invented. Everything else is just applications on top of that. Make the electrons flow in a different way and you get a different outcome.
Comment · 1 year ago
"But then I look at what these tools actually manage to do, and am disillusioned: these tools can be worse than useless, making us net-negative productive." It starts from this premise right in the first paragraph. And goes on to illustrate an example that proves their point ("Let's pick one of the best possible examples of AI-generated code changes.").

anyways, it doesn't matter that much :) we could be both right.

Comment · 1 year ago
I am not sure what you're implying. The first sentence makes no sense. LLMs aren't giving you non-deterministic code. The code is shown to you and have complete control over how it looks and operates. Not understanding the mechanics of how the code is generated by the LLM doesn't make the output non-deterministic.

If you choose to accept bad code, that's on you. But I am not seeing that in practice, especially if you learn how to give quality prompts with proper rules. You have to get good at prompts - there is no escaping that. Now programmers do suck at communicating sometimes and that might be an issue. But in my experience, it can write far higher quality code than most programmers if used correctly.

Comment · 1 year ago
"Mastering" is a strong term and is even misleading, especially when talking about tools that give you leverage. I mean if someone masters running, does it mean you never use a car? There are thousands and thousands of instances in everyday programming where AI is going to be 10x-100x faster than any human, especially at the function level and even file/script level.

I can give you a concrete example since things sometimes can be so philosophical. The other day I needed a LIS code (Longest Increasing subsequence) with some very specific constraints. It would've honestly taken me a few hours to get it right as it's been a while I coded that kind of thing. I was able to generate the solution with o3 in around 10 minutes, with some back and forth. It wasn't one shot, but took me 2-3 iteration cycles. I was able to get highly performant code that worked for a very specific constraint. It used Fenwick trees (https://en.wikipedia.org/wiki/Fenwick_tree) which I honestly hadn't programmed myself before. It felt like a science fiction moment to me as the code certainly wasn't trivial. In fact I am pretty sure most senior programmers would fail at this task, let alone be fast at it.

As a professional programmer, I deal with 20 examples every day where using a quality LLM saved me significant time, sometimes hours per task. I still do manual surgery a bunch of times everyday but I see no need to write most functions anymore or do multi-file refactors myself. In a few weeks, you get very good at applying Cursor and all its various features intelligently, like an amazing pair programmer who has different strengths than you. I'll go so far as to say I wouldn't hire an engineer who isn't very adept at utilizing the latest LLMs. The difference is just so stark - it really is like science fiction.

Cursor is popular for a reason. Lot of incredible programmers still get incredible value out of it, it isn't just for vibe coding. Implying that Cursor can be a net negative to programmers based on an example is a lot of fear mongering.

Comment · 1 year ago
I mean the headline "Net-Negative Cursor" is a pretty far reaching conclusion. The article does try to generalize on the implications from a code snippet for AI powered programming. The headline isn't "The example on Cursor's website is incorrect".
Comment · 1 year ago
Amazed at all the negative rhetoric around coding with LLMs on HN lately. The coding world is deeply split about their utility.

I think part of that comes from the difficulty of working with probabilistic tools that needs plenty of prompting to get things right, especially for more complex things. To me, it's a training issue for programmers, not a fundamental flaw in the approach. They have different strengths and it can take a few weeks of working closely to get to a level where it starts feeling natural. I personally can't imagine going back to the pre LLM era of coding for me and my team.

Comment · 1 year ago
Damn. Didn't expect so much bitterness this morning. What a strange set of "demands" for a pretty decent piece of kit.
Comment · 1 year ago
Landing page is nice but I am confused why this would be better than generating a prompt from the LLM itself? Latest models are extremely good in taking the seed of a problem and enhancing the prompt to the nth degree until you're satisfied.
Comment · 1 year ago
Asking a programmer to ditch their editor is just wild. A lot of this thread seems to be full of non-programmers trying to figure out why Cursor exists lmao
Comment · 1 year ago
Calling Cursor a vibe coding app is just wild. The journalists and influencers are so out of touch with the software engineering world.
Comment · 1 year ago
The point isn't to compare random AI art with random human art. The overarching sentiment lately has been that AI art feels bad and has this "Fake" quality to it.

This survey is refuting that argument. AI art can be used in media just like human art and people can't really tell (or care if they can't tell the difference).

Comment · 2 years ago
It's about stuff we don't know yet. From today's lens, the essay seems absurd. But I think it's hinging on continued discoveries that improve one or all of learning algorithms, compute efficiency, compute cost and applying algorithms to real world problems better.

5 years ago, I wouldn't have believed any of what exists today. I saw internal demos that showed 2nd or 3rd grade reading comprehension in 2017 and statements were made about how in the next decade, we will probably reach college level comprehension. We have come so far beyond that in less than half the time. Technology isn't about scaling incrementally and continuing on the same path using the same principles we know today. It's about disruption that felt impossible before - that feels like a constant to me now. Seeing everything I've seen in the last 20 years, it's going to continue to happen. We just can't see it yet.

Comment · 2 years ago
I missed the "yeah, we're done here" part. Don't think Waymo is going to pause their safety research program now.
Comment · 2 years ago
tbh this is the main thing I was looking for on the webpage. It's hard for me to jump ship from my existing workflows unless I see a professional and highly sophisticated app example. I am sure it works for simple cases but I am concerned about limitations that one hits as one does more complex things

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