The key to my point is in the word "generating". Meaning human input/judgement by actually typing more SQL than the LLM produces. The model's reasoning and code generation pipelines are typically 2 separate code paths, so it may not always actually do what it intends which can lead to unexpected results.
The key to my point is in the word "generating". Meaning human input/judgement by actually typing more SQL than the LLM produces. The model's reasoning and code generation pipelines are typically 2 separate code paths, so it may not always actually do what it intends which can lead to unexpected results.