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fivetenpen

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The biggest issue with business users (who don’t know SQL) writing SQL with an LLM is that there is no one to validate that query and now that business user will treat that LLM response as canon to share in meetings, presentations, and with clients. The LLM may have forgotten a filter, used the wrong definition of revenue, or misunderstood the user’s intent by writing a query that answers their question in the most literal way.

That is the crux of the issue. No amount of semantic layers and context will help this until an LLM can read the user’s mind to remove ambiguity in the prompt.

I see most of the benefits of LLMs to be used by analysts who know SQL to work more productivly.

The internet was never a danger to children’s mental health until social media engagement algorithms. The real solution is to ban any and all engagement algorithms that are designed to get people addicted. Age checks, aka identity checks, are just another blatant attempt to siphon more personal data by linking your real identity to all of your web activity

The internet was never a danger to children’s mental health until social media engagement algorithms. The real solution is to ban any and all engagement algorithms that are designed to get people addicted. Age checks, aka identity checks, are just another blatant attempt to siphon more personal data by linking your real identity to all of your web activity

The internet was never a danger to children’s mental health until social media engagement algorithms. The real solution is to ban any and all engagement algorithms that are designed to get people addicted.

Age checks, aka identity checks, are just another blatant attempt to siphon more personal data by linking your real identity to all of your web activity