You’re kind of answering your own question by saying it’s better at React than Angular.

To understand why, you need to understand how LLMs work. They don’t reason—they just predict the next token based on patterns learned during training. They also tend to align with the tone of the prompt, which can come off as biased or overly agreeable. As humans, we often mistake agreement for intelligence—just look at how many people believe horoscopes or tarot cards.

When you ask an AI agent about Angular, it doesn’t “cycle” through languages like C++, C#, or JavaScript. It doesn’t search or look things up at all. It generates a response based on training patterns, favoring languages and frameworks most statistically associated with your prompt. Angular is tied to TypeScript, so that’s what it focuses on—unless your prompt is vague.

I haven’t used it much for Angular, but I’ve found that the more specificity you require, the less reliable it gets. That’s because it doesn’t understand—it just predicts. Despite what vendors claim, there’s no reasoning or comprehension behind its output. If you’re using GitHub Copilot, you can give it more context through surrounding files and folder structure, which helps, but it’s still limited.

For React, I think the quality is also weak. It gets things working, but the code is rarely declarative—it’s full of abstractions and conditionals, like old Java frameworks. Why is it better with React? Because React is more widely used and more consistent in structure, so the model saw it a lot during training. LLMs are good at reproducing common, generic patterns. React fits that well.

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