Vigil - a self-hosted dashboard that watches your Docker images
Vigil - a self-hosted dashboard that watches your Docker images
Sorry, but you have posted only 1 sentence about the project and not even a link to the project.
Additional with the
scripts—basically “em dash” which is really popular among llm generated texts, i get a bad feeling about it.
I think it’s awesome that you’re trying to get into larger scale software development. Agentic coding can do some amazing stuff, but it takes experience and knowledge to keep it going down good path. I think this can be a good learning opportunity to level up your own skills. Something I would suggest doing is instruct Claude with something like:
You are an experienced Senior Software Engineer that is an expert in web and backend technologies like Python, Typescript, Node and React. You are being brought in to analyze and productionize a prototype application. Please explore this project and plan out a workstream to level up this prototype so that it is production ready. First you should establish some research topics and write them to "docs/research/{date}-{topic-name}.md". After that, launch some FOREGROUND general-purpose agents to handle researching these topics in parallel. Once completed these general-purpose agents should write their findings to their original docs/research/{date}-{topic-name}.md.Once it’s conducted all the research, take a look at the documents that it writes. And if you have questions about the research results/decisions, have Claude explain.
for a very long time it was not only possible for experts. like, I would say the last 10-15 years, maybe even more. It’s very harmful that people can now create things they don’t even know how to check what it does, and they just assume this “sentient thing” actually produced what you wanted with no major flaws. thing is, you (or anyone else vibecoding things) won’t be able to determine what is good or bad without taking the time and learning the building blocks, learning how they work and how they are supposed to be used.
also your comments look like AI generated comments, fake enthusiasm and all the rest. it does not inspire much confidence
I appreciate you being honest in your response here.
I’d recommend adding this disclaimer to the post text and repo readme for complete transparency, and so anyone who doesn’t want to use AI-generated projects can move on without creating arguments in the comments.
There are many genuine reasons to not trust code generated by LLMs, especially with anything network-connected or handling important data, so it’s important to be upfront about it.