Raw LLM Responses
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in
This breakdown is excellent, Luís. What I see in real systems is that the “body”…
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in
Imagine explaining your job in 2036: “I don’t build products anymore - I generat…
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in
Pascal BORNET part of this awareness that we champion, is understanding that AI …
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in
Users who are vulnerable, who are forming genuine relationships with AI, who are…
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in
Nice anatomy. But bodies have one thing this model skips: an immune system. Who …
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in
The AI debate keeps getting stuck at the surface level: “good or bad” “ethical o…
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in
So true. People never wunder why they are pushing Ai. It's not for the greater g…
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in
Thanks for emphasizing "a process of shared discernment.” In that context, it is…
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Comment
Incredible milestones at I/O, Demis. The speed of Gemini 3.5 Flash and Omni opens immense possibilities. However, scaling frontier models on flat rates creates an unsustainable compute drain. To protect CapEx ROI, we must shift from text approximation to guaranteed data fidelity via a "Pay-per-Logic" Hybrid Framework: Track A (Free): Statistical answers for low-stakes curiosity. Track B (Premium): High-compute multi-agent reasoning using live, verified third-party APIs. Users pay a dynamic micro-fee (e.g., $1.50 for localized real estate audits) for 100% accuracy. Professionals gladly pay per query for trustworthy data they can financially back up. This turns AI from a cost center into a transactional revenue engine. Love to share the full brief with your team!
LinkedIn
AI Safety & Risk
Assistant Manager at AllNet Systems Ltd
2026-05-22T08:5…
Coding Result
| Dimension | Value |
|---|---|
| Primary value | sustainability |
| Secondary value | economic_equity |
| Alignment target | organisations |
| Stance | demanding |
| Emotion | approval |
| Value justification | The speaker wants AI to be aligned with sustainability by reducing the compute drain and shifting to a more efficient framework. |
| Target justification | The target of the speaker's suggestion is organisations, as they discuss protecting CapEx ROI and turning AI into a revenue engine. |
| Coded at | 2026-06-11T07:58:26Z |
Raw LLM Response
```
{
"value_primary": "sustainability",
"value_secondary": "economic_equity",
"target": "organisations",
"stance": "demanding",
"emotion": "approval",
"value_justification": "The speaker wants AI to be aligned with sustainability by reducing the compute drain and shifting to a more efficient framework.",
"target_justification": "The target of the speaker's suggestion is organisations, as they discuss protecting CapEx ROI and turning AI into a revenue engine."
}
```