Raw LLM Responses
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Most people don’t actually need “autonomous agents,” they need reliable content …
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Mohammed Shakeer Mohammed Shakeer The prevailing theory is that AI generated pro…
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Thank you for sharing this Pascal BORNET. This is where the control question bec…
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Using AI-generated videos or voices to make it appear as if celebrities or billi…
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Strong explanation. Many people underestimate that enterprise AI is not just abo…
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The biggest AI debate is no longer about capability. It is about control, incent…
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Thank you for your reflections. I’ve ordered a hard copy, which will arrive in J…
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Good breakdown. One pushback on layer 1: calling the LLM a “brain”makes it sound…
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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."
}
```