Raw LLM Responses
Inspect the exact model output for any coded comment.
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Random samples — click to inspect
in
Mark Wagner 😎 📈 #Bentley #Asset #Management 💥 #BAM #Alert: 📢 MU, SNDK and DRAM a…
7465423690168…
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Geographic anchoring may take care of logistical routing but at the same time er…
7467018943774…
in
I was devastated to know my interactions with your staff were less than satisfac…
7465381161993…
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Powerful progress — especially around agents, world understanding, CodeMender, a…
7463406323741…
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Matthew Kilkenny...point3 stopped me immediately. "Human limitations are not def…
7465774034060…
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For entry level positions AI isxa big threat because their tasks are typically t…
7466051763377…
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Very important perspective. The biggest AI question is probably no longer whethe…
7464968754314…
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Keryann Granet It is here to stay, but with this technology. Are we leaving a be…
7465305290649…
Comment
Too real. AI can be wrong with the confidence of a senior consultant and then gently suggest you drink water about it. Still useful, but definitely not something to trust without verification.
LinkedIn
General AI Discourse
Business Systems & Solution Architect | SAP EAM…
2026-06-02T13:4…
Coding Result
| Dimension | Value |
|---|---|
| Primary value | safety |
| Secondary value | none |
| Alignment target | individual_users |
| Stance | critical |
| Emotion | indifference |
| Value justification | The speaker wants AI to be accurate and reliable, implying a desire for safety in its decision-making process. |
| Target justification | The speaker is concerned with the individual user's experience and potential harm from trusting AI's confidently wrong answers. |
| Coded at | 2026-06-11T08:37:02Z |
Raw LLM Response
```
{
"value_primary": "safety",
"value_secondary": "none",
"target": "individual_users",
"stance": "critical",
"emotion": "indifference",
"value_justification": "The speaker wants AI to be accurate and reliable, implying a desire for safety in its decision-making process.",
"target_justification": "The speaker is concerned with the individual user's experience and potential harm from trusting AI's confidently wrong answers."
}
```