71–80 of 464 posts
This truly is shocking. If you are reviewing every single line of every package you intend to use how do you ever write any code?
It would be interesting to see which is faster/better in competitive coding, the human coder or the human using AI to assist in coding.
I had AI create me a k8s device plugin for supporting sr-iov only vGPU's. Something nvidia calls "vendor specific" and basically offers little to not support for in their public repositories for Linux KVM.
I loaded up a new go project in goland, opened up Junie, typed what I needed and what I have, went to make tea, came back, looked over the code to make sure it wasn't going to destroy my cluster (thankfully most operations were read-only), deployed it with the generated helm chart and it worked (nearly) first try.
Before this I really had no idea how to create device plugins other than knowing what they are and even if I did, it would have easily taken me an hour or more to have something working.
The only thing AI got wrong is that the virtual functions were symlinks and not directories.
The entire project is good enough that I would consider opensourcing it. With 2 more prompts I had configmap parsing to initialize virtual functions on-demand.
AI is a tool like any other, you have to learn to use it. I had AI create me a k8s device plugin for supporting sr-iov only vGPU's. Something nvidia calls "vendor specific" and basically offers little to not support for in their public repositories for Linux KVM. I loaded up a new go project in goland, opened up Junie, typed what I needed and what I have, went to make tea, came back, looked over the code to make sure…
Earlier quoted context omitted.
You're going to spend a little over $1k to ramp up your skills with AI-aided coding. It's dirt cheap in the grand scheme of things.
do I get a refund if I spend a grand and I'm still not convinced? at some point I'm going to start lying to myself to justify the cost and I don't know how much y'all earn but $1k is getting close
I get confused when I see stances like this, because it gives me the sense that maybe people just aren't using coding tools efficiently. 90% of my usage of Copilot is just fancy autocomplete: I know exactly what I want, and as I'm typing out the line of code it finishes it off for me. Or, I have a rough idea of the syntax I need to use a specific package that I use once every few months, and it helps remind me what t…
My experience is that the "fancy autocomplete" is a focus destroyer. I know what function I want to write, start writing it, and then bam! The screen fills with ghost text that may partly be what I want but probably not quit. Focus shifts from writing to code review. I wrest my attention back to the task at hand, type some more, and bam! New ghost text to distract me. Ever had the misfortune of having a conversation…
Autocomplete is a total focus destroyer for me when it comes to text, e.g. when writing a design document. When I'm editing code, it sometimes trips me up (hitting tab to indent but end up accepting a suggestion instead), but without destroying my focus.
I believe your reported experience, but mine (and presumably many others') is different.
Earlier quoted context omitted.
You're going to spend a little over $1k to ramp up your skills with AI-aided coding. It's dirt cheap in the grand scheme of things.
How are those without that kind of scratch supposed to keep up with those that do?
To some degree, traditional coding and AI coding are not the same thing, so it's not surprising that some people are better at one than the other. The author is basically saying that he's much better at coding than AI coding. But it's important to realize that AI coding is itself a skill that you can develop. It's not just , pick the best tool and let it go. Managing prompts and managing context has a much higher ski…
> But it's important to realize that AI coding is itself a skill that you can develop. It's not just , pick the best tool and let it go. Managing prompts and managing context has a much higher skill ceiling than many people realize No, it's not. It's something you can pick in a few minutes (or an hour if you're using more advanced tooling, mostly spending it setting things up). But it's not like GDB or using UNIX as…
You can start in a few minutes, sure. (Also you can start using gdb in minutes) But GP is talking about the ceiling. Do you know which models work better for what kind of task? Do you know what format is better for extra files? Do you know when it's beneficial to restart / compress context? Are you using single prompts or multi stage planning trees? How are you managing project-specific expectations? What type of testing gives better results in guiding the model? What kind of issues are more common for which languages?
Correct prompting these days what makes a difference in tasks like SWE-verified.
> It takes me at least the same amount of time to review code not written by me than it would take me to write the code myself, if not more. As someone who uses Claude Code heavily, this is spot on. LLMs are great, but I find the more I cede control to them, the longer it takes to actually ship the code. I’ve found that the main benefit for me so far is the reduction of RSI symptoms, whereas the actual time savings a…
There's an implied assumption here that code you write yourself doesn't need to be reviewed from a context different from the author's. There's an old expression: "code as if your work will be read by a psychopath who knows where you live" followed by the joke "they know where you live because it is future you". Generative AI coding just forces the mindset you should have had all along: start with acceptance criteria…
To some degree, traditional coding and AI coding are not the same thing, so it's not surprising that some people are better at one than the other. The author is basically saying that he's much better at coding than AI coding. But it's important to realize that AI coding is itself a skill that you can develop. It's not just , pick the best tool and let it go. Managing prompts and managing context has a much higher ski…
> But it's important to realize that AI coding is itself a skill that you can develop. It's not just , pick the best tool and let it go. Managing prompts and managing context has a much higher skill ceiling than many people realize No, it's not. It's something you can pick in a few minutes (or an hour if you're using more advanced tooling, mostly spending it setting things up). But it's not like GDB or using UNIX as…
Here’s what my today’s task looks like: 1. Test TRAE/Refact.ai/Zencoder: 70% on SWE verified 2. https://github.com/kbwo/ccmanager: use git tree to manage multiple Claude Code sessions 3. https://github.com/julep-ai/julep/blob/dev/AGENTS.md: Read and implement 4. https://github.com/snagasuri/deebo-prototype: Autonomous debugging agent (MCP) 5. https://github.com/claude-did-this/claude-hub: connects Claude Code to GitHub repositories.