I use LLM as a super Stackoverflow. So far it has been helpful. For code gen, 8 out of 10 cases, the code won't compile and need fixing. LLM did help a lot in learning new topics. Gemini did help tremendously recently in pointing out a new approach to a problem I was stumped on. Though the code it generated was garbage, the code did provide insight on a new approach which I adopted to make it work eventually.
My AI skeptic friends are all nuts
451–460 of 1001 posts
Re: My AI skeptic friends are all nuts
#452> As a mid-late career coder, I’ve come to appreciate mediocrity. You should be so lucky as to have it flowing almost effortlessly from a tap. If the kind of work this person is doing requires no thought, then of course an LLM will be perfect for it.
> I’ve come to appreciate mediocrity
I don’t care how long I can be in my career, I just can’t do BE like this. It feels off character for me to be mediocre.
Re: My AI skeptic friends are all nuts
#453I tried the agent thing on: - Large C codebase (new feature and bugfix) - Small rust codebase (new feature) - Brand new greenfield frontend for an in-spec and documented openAPI API - Small fixes to an existing frontend It failed _dramatically_ in all cases. Maybe I'm using this thing wrong but it is devin-level fail. Gets diffs wrong. Passes phantom arguments to tools. Screws up basic features. Pulls in hundreds of…
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Re: My AI skeptic friends are all nuts
#454Here are two routine problems I have to solve at the moment. Can any of the current LLM systems do either?
1. Input is an 256x256 pixel elevation map stored as a greyscale .png file, and a minimum and maximum elevation. A pixel value of 0 corresponds to the minimum elevation, and a pixel value of 255 corresponds to the maximum elevation. Read in the .png file and the elevation limits. Then construct a 256x256 floating point array of heights. From that array, construct a triangle mesh with X and Y dimensions 0..255. Perform a mesh reduction operation on the triangle mesh to reduce the number of triangles. Mesh reduction must not generate holes in the mesh. From the reduced mesh, generate a glTF file where the UV parameters run from 0.0 to 1.0 along the X and Y axes.
2. Given four glTF files constructed as above, corresponding to four quadrants of a larger square, construct a single 511x511 mesh which combines all four input meshes to cover a larger area. Because the input meshes are 0..255, not 0..256, there will be gaps where the four quadrants meet. Fill those gaps with reasonable triangles. Perform a mesh reduction as above. From the reduced mesh, generate a glTF file where the UV parameters run from 0.0 to 1.0 along the X and Y axes.
Rust code is preferred; Python code is acceptable.
So, what service should I sign up for?
Re: My AI skeptic friends are all nuts
#455There's something that seems to be missing in all these posts and that aligns with my personal experience trying to use AI coding assistants. I think in code. To me, having to translate the into natural language for the LLM to translate it back into code makes very little sense. Am I alone in this camp? What am I missing?
I'm also in this camp, and that's why it does not work for me.
Natural language is just a terrible interface and fundamentally not an appropriate one to communicate with a computer.
I wonder if I'm in the minority here because I'm neurodivergent.
Re: My AI skeptic friends are all nuts
#456The argument seems to be that for an expert programmer, who is capable of reading and understanding AI agent code output and merging it into a codebase, AI agents are great. Question: If everyone uses AI to code, how does someone become an expert capable of carefully reading and understanding code and acting as an editor to an AI? The expert skills needed to be an editor -- reading code, understanding its implication…
LLMs are also great to ask questions about existing code. It's like being able to converse with StackOverflow.
Re: My AI skeptic friends are all nuts
#457Here are two routine problems I have to solve at the moment. Can any of the current LLM systems do either? 1. Input is an 256x256 pixel elevation map stored as a greyscale .png file, and a minimum and maximum elevation. A pixel value of 0 corresponds to the minimum elevation, and a pixel value of 255 corresponds to the maximum elevation. Read in the .png file and the elevation limits. Then construct a 256x256 floatin…
try claude code, in python
Re: My AI skeptic friends are all nuts
#458Here are two routine problems I have to solve at the moment. Can any of the current LLM systems do either? 1. Input is an 256x256 pixel elevation map stored as a greyscale .png file, and a minimum and maximum elevation. A pixel value of 0 corresponds to the minimum elevation, and a pixel value of 255 corresponds to the maximum elevation. Read in the .png file and the elevation limits. Then construct a 256x256 floatin…
Why don't you paste that into Claude, ChatGPT — report back what you find?
Re: My AI skeptic friends are all nuts
#459I was a bit skeptical at first too, but once I let AI dive into my code, run tests, refactor functions, and even catch its own bugs, it felt like I suddenly had a really competent teammate.
AI has been genuinely helpful for me , it saves time and lets me focus on the things that actually matter.
Re: My AI skeptic friends are all nuts
#460Will LLMs ever break the “you have to treat it like an intern/junior” ceiling?