Raw LLM Responses
Inspect the exact model output for any coded comment.
Look up by comment ID
Random samples — click to inspect
in
If AI systems begin designing and operating businesses, the critical question is…
7468682821025…
in
The Pope Is right to liken the AI 🤖 arms race with the nuclear ☢️ arms race : th…
7465216814948…
in
Scott Schobert Totally agree! This is a major concern that is surfacing right no…
7468743178913…
in
Stand by me, Demis Hassabis... I create Sarinem Chat with Opal (your multi-modal…
7463455972225…
in
This resonates beyond pure research. In finance and compliance, AI is beginning …
7466375932891…
in
When your alignment models are so tangled in corporate static that they leak the…
7465482980279…
in
If task is vague, they complete the wrong thing fast. The hands need guardrails.…
7464694646338…
in
The best leaders right now are the ones who've made "cite your source and show y…
7467779330551…
Comment
This is a helpful way to explain the AI stack. LLMs think, RAG retrieves, Agents act, and MCP connects. But one layer is still missing: structural state. AI cannot make reliable enterprise decisions from files alone. A file stores content, but it does not carry state, permission, responsibility, history, risk, or execution conditions. Humans judge situations through relationships and context, not data alone. The same document can mean different things depending on who approved it, what state it is in, and whether action is allowed. So the next step is turning documents and data from static files into objects. Only then can AI move from retrieval and automation to responsible decision support. Enterprise AI will not mature only by connecting more tools. It will mature when data itself becomes structurally intelligent.
LinkedIn
Workplace & Jobs
Designing Structural Closure and Two-Mode Execu…
2026-05-25T13:4…
Coding Result
| Dimension | Value |
|---|---|
| Primary value | accountability |
| Secondary value | none |
| Alignment target | organisations |
| Stance | demanding |
| Emotion | approval |
| Value justification | The speaker emphasizes the need for AI to consider structural state, permission, responsibility, and history to make reliable decisions, which is related to accountability. |
| Target justification | The comment focuses on enterprise decisions and the maturity of enterprise AI, indicating that the target is organisations. |
| Coded at | 2026-06-11T08:07:58Z |
Raw LLM Response
```
{
"value_primary": "accountability",
"value_secondary": "none",
"target": "organisations",
"stance": "demanding",
"emotion": "approval",
"value_justification": "The speaker emphasizes the need for AI to consider structural state, permission, responsibility, and history to make reliable decisions, which is related to accountability.",
"target_justification": "The comment focuses on enterprise decisions and the maturity of enterprise AI, indicating that the target is organisations."
}
```