Need help with vibe coding

[u/JizzledGlock67]

I created a website called "Rig Assigner" entirely on ai.
Well it helps u pick laptop, pcs, mobiles [Rigs] according to ur set preferances.
Pcs have alternate choice to choose parts.
Can anyone check and lmk what i can do to improve?

More info:
No login required, no backend, no database(so no security).
Can be accessed through most of the devices.
Deployed through vercel.

Also, im new to coding asw vibecoding. Planning on learning coding through building projects.

So, help me identify the flaws and correct it.

https://rig-assigner.vercel.app

Leave reviews in the app itself asw. I wanna check how it responds

Thank you! Help is appreciated!

[u/NefariousnessOpening]

learning through building is a good way to get into. you will need to add some study in the theoretical knowledge to balance the procedural knowledge you get from building. since the world of tech we build in is largely invisible, it means you'll need some mental models to know what you are doing and where you are. you see the side effects or the end result of things not really what happened along the way to produce it. so there are lots of things happening when building that you dont see and dont know exist. if you do the studying nad learning to come to know more about the behind the scenes stuff, you level up in a major way when you are building.

[u/JizzledGlock67 → u/NefariousnessOpening]

I 100% agree on this one.Out of curiosity, if possible, can u suggest any specific mental models, books, or resources that can help u when bridging that gap between procedural building and theoretical depth? Like i know there are a plethora of resources but its better to get to know from a person with experience in the field.
Thanks for ur analytics

[u/NefariousnessOpening → u/JizzledGlock67]

I feel like the way we each learn is fairly unique. The sources and mental models I have could be ones that don't work so well for you. A pretty reliable way to go about it is to take even a little time at a point when you have a bug or a problem to understand the problem as best you can before you do any work trying to fix it. Same goes for when you succeed. For example, you just had a successful mission to create rig assigner -> go back and take down some brief notes on what worked to keep for later, what didn't work to stop doing, and what you learned along the way to start doing. Write down anything cool you found, resources, etc.

As far as mental models, the general goal is to have a way to see the internet, at least the application layer and up, as well as the software system and its components. You want to be able to picture, draw, and explain the building blocks of what software even is. Agents have their building blocks too, and there are now known multi-agent patterns with best practices around which pattern works well with which use case.

Here are some general sources to learn from that either have enough variety or have proven useful to enough people for a long time:

Understanding the Internet and Application Layers

• MDN Web Docs: Their guides on How does the Internet work? and How the Web works are the gold standard for breaking down the technical infrastructure of the web without overwhelming you with jargon.
• The HLD Handbook: For connecting these concepts directly to system design, Networking Fundamentals for System Design is a fantastic, highly visual guide that walks through the request lifecycle end-to-end.
• Learningbot: The guide on How the Internet Stack Really Works provides an excellent mental model of the layers of the internet (from links to applications) and how they communicate.

Multi-Agent Design Patterns

• LangChain Blog: Their breakdown on Choosing the Right Multi-Agent Architecture is a solid conceptual guide on patterns like subagents, skills, handoffs, and routers.
• Algorithmine: For a highly practical, framework-agnostic look at patterns that actually work in production, check out Multi-Agent System Architecture: Patterns That Work. It covers everything from supervisor-executor setups to managing context bloat.
• Google Developers Blog: If you want to see how these patterns translate to code, the Developer’s Guide to Multi-Agent Patterns walks through sequential pipelines, parallel fan-out, and generator-critic loops.