Hello everyone,
I'm writing this post in relation to AI and programming. I often see people post on Reddit and Instagram saying there is no reason to program anything at all anymore, or they say something similar to "just use claude to make the solution."
To me, this just doesn't make sense. How can you create something without having a deep understanding of the underlying architecture or the logic behind it. The logic is so important especially for me (I do R&D and Tech Innovation). If it's not correct, everything fails. How can they just let Claude or an LLM do this without supervision? I've used it before, and it works great for boilerplate code, but as logic advances, the solution gets unnecessarily large.
I've been looking at statistics regarding this vs what social media/ LinkedIn is saying, and now software fails more often, security risks are more abundant than ever, and we're just churning out bad solutions that we hope works. Sometimes, the cost of tokens is as expensive as just hiring an engineer. Reviewing the code sometimes takes longer than making it myself, or the logic is just odd. Does our expertise in Golang, or programming, matter anymore? Is there still a need to learn the newest additions to Golang or anything else?
You could say I'm just a bit worried, but I don't know where things are going.
------Edit in lieu of great feedback------
Thank you to everyone that responded to this post and provided their thoughts, experiences, and feedback. From what I've read, there seems to be a mix of opinions regarding AI. Some of us are finding it to be problematic while others are making great use of it. However, most of us are saying that our skills are still very useful, and the vibe coder/coder will be forced out of the industry for actual engineers.
It should also be mentioned that the previous most upvoted comment referenced how AI tokens are subsidized, and when it reaches the full, unsubsidized cost, we will see another shift. From what I've read in articles, this seems to be true as some companies are pulling back their "AI First"/Tokenmaxxing mindset.
This is a great conversation, and I'll be sure to keep it going in another post with a new question.
I built a Containerization API that executes untrusted code and returns output plus memory and CPU metrics. Instead of running a container per submission, it creates the boundary directly with Linux primitives: PID, mount, network, and user namespaces, a chroot into a minimal per-language rootfs, cgroups v2 for memory and CPU limits, and a seccomp-BPF denylist. The sandbox root maps to host UID 65534, so root inside is never root outside.
It supports Python, C++17, C11, and Java, capped at 60s and 128MB, with a global admission controller that rejects work before a sandbox is created. Every limit is kernel-enforced.
Code:
Live Demo Website:
Although I've done rigourous testing for resource management and permissions based sandbox escape, I've still hosted the api on a very small server on an isolated network, just in case im wrong
I think its pretty cool, its faster in code execution than most of the other containerization services like docker or firejail, do check it out!
