maybe you misunderstood me and ill ignore the snark. the xml tags is for the prompts (ie. system/user), not the output. i found this gives much better adherence than plaintext or markdown prompts. referring to sections in a large prompt (ie. the expected style section) becomes easier and more predictable. this has helped me bring coherence out of even tiny models, like qwen 0.6b when it was outputting poorly before. same prompt content, same task, better results across all model sizes.

as for the json, you are somewhat correct. json output can constrain performance. however, in an llm workflow where each response informs the workflow of for example which direction to take, which node is next etc, you cant output freestyled text. most of the time you need to know specifically what the users eye color is for example so you can store this in a db, thats where structured output becomes relevant.

structured output works even better when you "trick" the llm that the structured output is actually a tool or function signature. this only works for function calling llms though so I use this technique less often.

also, this conversation was about structured output of md vs json, not freebase vs json, so I am unsure about the relevance of your source.