Raw LLM Responses

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I'm an engineer. The way I see it, any use cases of LLMs in production is just complex translators between unstructured data and structured data. (Which is also Probabilistic) Agentic AI? Human query (Unstructured data)->Parameters(Structured data)->Code calls-> Code result-> AI response (Unstructured data). RAG? It's the same. Any other use case is just combination of these. Now, The problem of Unstructured data/Structured data conversions has been a big one for the computer science world and now that we have this translator, We can do many fancy things. However, There is nothing that is going to be replaced by this fancy translator especially in industries where reliability is important and mistakes are catestrophic. Definitely not as projected by these "CEO"s/ "AI experts".
youtube AI Jobs 2026-02-26T07:5… ♥ 1
Coding Result
DimensionValue
Responsibilitynone
Reasoningmixed
Policyunclear
Emotionindifference
Coded at2026-04-27T06:24:53.388235
Raw LLM Response
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