No Stupid Questions

Think of LLMs as the person who gets good marks in exams because they memorized the entire textbook.

For small, quick problems you can rely on them ("Hey, what's the syntax for using rsync between two remote servers?") but the moment the problem is slightly complicated, they will fail because they don't actually understand what they have learnt. If the answer is not present in the original textbook, they fail.

Now, if you are aware of the source material or if you are decently proficient in coding, you can check their incorrect response, correct it, and make it your own. Instead of creating the solution from scratch, LLMs can give you a push in the right direction. However, DON'T consider their output as the gospel truth. LLMs can augment good coders, but it can lead poor coders astray.

This is not something specific to LLMs; if you don't know how to use Stackoverflow, you can use the wrong solution from the list of given solutions. You need to be technically proficient to even understand which one of the solutions is correct for your usecase. Having a strong base will help you in the long run.

In my experience, an LLM can write small, basic scripts or equally small and isolated bits of logic. It can also do some basic boilerplate work and write nearly functional unit tests. Anything else and it's hopeless.

I use it as a friendlier version of stackoverflow. I think you should generally know / understand what you are doing because you have to take everything it says with a grain of salt. It's important to understand that these assistants can't admit that they don't know something and come up with random generated bullshit instead so you can't fully trust their answers.

So you still need to understand the basics of software development and potential issues otherwise it's just negligence.

On a general note: IQ means nothing. I mean a lot of IQ tests use pattern recognition tasks that can be helpful but still, having a high IQ says nothing about you ability as developer

if you know how to code, you can vibe code because you can immediately see and be confident enough to identify and not use obvious mistakes, oversights, lack of security, and missed edge cases the LLM generated.

if you don't know how to code, you can't vibe code, because you think the LLM is smarter than you and you trust it.

Imagine saying "I'm a mathematician" because you have a scientific calculator. If you don't know the difference between RAD and DEG and you just start doing calculations without understanding the unit circle, then building a bridge based on your math, you're gonna have a bad time.

If you "vibe code" your way through trial and error to an app, it may work.
But if you don't understand what it's doing, why it's doing it and how it's doing it?
Then you can't (easily) maintain it.
If you can't fix bugs or add features, you don't have a saleable product - you have a proof of concept.

AI tools are useful, but letting the tool do all the driving is asking for the metaphorical car to crash.

It's cool for little things when working on an unfamiliar project or learning something new.

But don't trust one example and read about the features you're using.

Only for really basic things. I’m trying to use it to build tools in the background while I do real work, but it quickly falls into a pattern of presenting a working product that actually doesn’t work at all (and then If have to dedicate a lot more time analysing the generated code to find out why. It often can’t fix its own workings even with a “reasoning” model.)

People who vibe code are not using free LLMs, they are using custom AI code generation systems they pay subscriptions for. I don't know which ones work best but I do have a close friend who runs a software company and he just bought subscriptions for all his employees to some system I've never heard of because the code it generated drastically sped up their development time.

If you care about it at all, don't vibe it otherwise go hog wild

It works short term. If you have a deadline tomorrow by all means.

Long term you need to be aware of not just the code but the theory behind the code. You can make it work if you're promoting what you need and read the result, understand it and test it but if we pure vibe coding is probably too much. How are you gonna solve problems when you don't fully understand how things work?

Another thing, a lot of AI generated code solves the problem in the most obvious often bad way. For example I asked the AI for help with an ORM limitation I was running into and so many times the code it suggested was just query the db, then filter in code afterwards

I have successfully written and deployed a number of large complex applications with 100% AI written code, but I micromanage it. I’ve been developing software for 30 years and use AI as a sort of code paintbrush. The trick is managing the AI context window to keep it big enough to understand its task but small enough to not confuse it.

It already kinda works 95% of the way. But more often than not the last 5% still requires you to understand everything the AI did which can be hard. If it was you implementing everything, you'd already have the whole context in working memory. I've been learning better prompting and getting better at it. I think it thrives in typed languages and where the code base has clear design patterns it can follow.

I pretty much only use it to generate boilerplate. I've tried using it to learn the syntax of new languages and it kind of works, but in my experience just reading the docs is better even if it seems like a lot of text. Also your IQ really does not matter. You can learn anything as long as you're willing to put in the time and effort; don't compare yourself to others it's fine to go at your own pace. (I'm Autistic also btw)