Raw LLM Responses

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@KevinGulling It depends... It can do very complex math since it has a lot of training on mathematical concepts, but it can fail at properly carrying digits, similar to how it will mess up at identifiers or get confused about version consistency if you tell it to program something for you in one shot. The difference is that you can take that code, try to compile it, and then see exactly why it's wrong, which means you can bring it back to the AI with those results or let it do confirmation itself, like if you give it tools to confirm its results (like Python/REPL). This is why tool calling is more prevalent now. If you've tried telling an AI model to do something long-form or complicated like decoding from base64 or extracting text from a PDF, it will use tools automatically; but if it didn't have those tools, which it didn't for a long time, then yeah, it will be terrible at it and confidently provide/hallucinate wrong answers even for basic stuff because it had no symbolic grounding.
youtube AI Governance 2026-03-17T13:5…
Coding Result
DimensionValue
Responsibilitynone
Reasoningunclear
Policyunclear
Emotionindifference
Coded at2026-04-27T06:24:59.937377
Raw LLM Response
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