All the non prompt controls you mentioned have _nothing like_ the level of actual influence that a system prompt can have. They’re not a substitute in the same way that (say) bound query parameters are a substitute for interpolated SQL text.
These methods do work better than prompting. For example Prompting alone for example has much poor reliability in spitting out JSON output adhering to a schema consistently. OpenAI cited 40% for prompts versus 100% reliablity with their fine-tuning for structured outputs [1].
Content moderation is more of course challenging and more nebulous. Justice Porter famously defined the legal test for hard core pornographic content as "I will know it when I see it" [Jacobellis v. Ohio | 378 U.S. 184 (1964)].
It is more difficult for a model marketed as lightly moderated like Grok.
However that doesn't mean the other methods don't work or are not being used at all.
[1] https://openai.com/index/introducing-structured-outputs-in-t...
This makes invalid output (as far as the JSON schema goes) impossible, with one exception: if the model runs out of output tokens the output could be an incomplete JSON object.
Most of the other things that people call "guardrails" offer far weaker protection - they tend to use additional models which can often be tricked in other ways.
I didn't mean to imply that all methods give 100% reliability as the structured data does. My point was just that there are non system prompt approaches which give on par or better reliability and/or injection security, it is not just system prompt or bust as other posters suggest.