Raw LLM Responses
Inspect the exact model output for any coded comment.
Look up by comment ID
Random samples — click to inspect
G
I think about the new AI anime. It is coherent and that is the best I can say ab…
ytc_UgwYSfqDf…
G
Isn’t Elon just going to stick all the info he scraped, combine it with all the …
ytc_UgxzgzRqo…
G
CNN is garbage and I guarantee you these nice Christians are nasty people with b…
ytc_UgwX9inaZ…
G
@ yo there's like 70000 Artificial Intelligence Companies worldwide, with a few …
ytr_UgyxM8oVa…
G
Al are billionaires who want to control everything and they tried to manuplate p…
ytc_UgzVf-vzI…
G
Hmm just saw the orange con signed an executive order saying state’s have no say…
ytc_Ugzee-Gm7…
G
Don't worry about the younger genearation, this world is over! Jesus is at the d…
ytc_Ugx6SsxK8…
G
ChatGPT can be very useful, if you have expertise
in that field, if you dare …
ytc_Ugy1eKomM…
Comment
4:12 Not quite actually. Modern agentic LLMs are a lot more defined by code than you would think. For example, lets consider a chess playing agentic AI. The agentic AI doesn't reason on playing a game of chess, it launches a docker container with a python fast MCP server that executes the chess python library/package. In this case almost all of the output of the AI is defined by code, the AI merely did a little bit of reasoning to orchestrate the task.
This is actually essential for future AI driven performance. For starters, it greatly improves performance for the same reason giving a human a hammer or a calculator improves their performance at a particular task, and it greatly improves reliability as well as speed. The AI is trained on how to use these deterministic coding tools, but looking at things from a system level you'd see that in many cases the code represented 99% of the actual work with a little bit of AI reasoning filling in the gap, representing the glue that ties in the pieces together into a coherent single structure.
youtube
AI Moral Status
2025-12-11T04:2…
♥ 3
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | developer |
| Reasoning | mixed |
| Policy | none |
| Emotion | indifference |
| Coded at | 2026-04-27T06:24:53.388235 |
Raw LLM Response
[
{"id":"ytc_UgzfkJjjmVroB0IM8LF4AaABAg","responsibility":"developer","reasoning":"consequentialist","policy":"none","emotion":"resignation"},
{"id":"ytc_Ugw4tnbRxkkmSrEfjLx4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"indifference"},
{"id":"ytc_UgztoMsIJds3l5aPyIl4AaABAg","responsibility":"developer","reasoning":"mixed","policy":"none","emotion":"indifference"},
{"id":"ytc_UgyITxXnLlFhOAHKGBJ4AaABAg","responsibility":"user","reasoning":"virtue","policy":"none","emotion":"mixed"},
{"id":"ytc_Ugy9KFesjcJsMSNVfIt4AaABAg","responsibility":"developer","reasoning":"consequentialist","policy":"regulate","emotion":"fear"},
{"id":"ytc_UgzfcWx1_nPsEF855VB4AaABAg","responsibility":"ai_itself","reasoning":"consequentialist","policy":"none","emotion":"fear"},
{"id":"ytc_UgzFKMJ4CLvmP3uxEOJ4AaABAg","responsibility":"ai_itself","reasoning":"deontological","policy":"none","emotion":"outrage"},
{"id":"ytc_UgzWYagWJhiFibWNY9B4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"mixed"},
{"id":"ytc_UgyQ1L00vAevLsr3o6Z4AaABAg","responsibility":"developer","reasoning":"mixed","policy":"regulate","emotion":"approval"},
{"id":"ytc_UgwKzdJA9OgIy7LnGJ54AaABAg","responsibility":"company","reasoning":"virtue","policy":"liability","emotion":"outrage"}
]