Raw LLM Responses
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in
Nice automation. How do you prevent losing your authenticity and credibility wit…
7447163842377…
in
Though not still in league of claude code or even codex but the direction is rig…
7464215188234…
in
The deeper issue for me is that there is still a long distance between an LLM an…
7463913377627…
in
This resonates deeply. AI’s greatest value may not be replacing researchers, cli…
7466315995339…
in
Excellent post pro From a security perspective: LLM: Protect against prompt inje…
7464722787039…
in
This is exactly the point: recursive self-improvement is not only a technical qu…
7468703210942…
in
"Kudos to those capable of working on complexity at such extraordinary speed." -…
7464978178743…
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Honestly the SynthID news is the one I'd underline twice, Demis. Watermarking is…
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Comment
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LinkedIn
AI Policy & Regulation
Chief AI Officer | Sovereign AI Consultant | So…
2026-05-26T09:3…
Coding Result
| Dimension | Value |
|---|---|
| Primary value | safety |
| Secondary value | none |
| Alignment target | organisations |
| Stance | optimistic |
| Emotion | approval |
| Value justification | The comment mentions 'safely automate' which implies a concern for safety in the deployment of AI systems. |
| Target justification | The comment is addressed to organisations, specifically government departments, offering a solution to accelerate their transition to AI-native departments. |
| Coded at | 2026-06-11T08:13:49Z |
Raw LLM Response
```json
{
"value_primary": "safety",
"value_secondary": "none",
"target": "organisations",
"stance": "optimistic",
"emotion": "approval",
"value_justification": "The comment mentions 'safely automate' which implies a concern for safety in the deployment of AI systems.",
"target_justification": "The comment is addressed to organisations, specifically government departments, offering a solution to accelerate their transition to AI-native departments."
}
```