Raw LLM Responses
Inspect the exact model output for any coded comment.
Look up by comment ID
Random samples — click to inspect
in
🚨 Silent UI Fragmentation: The legacy, single-tap TTS "Speaker" integration was …
7466118625612…
in
What solution do the Pope and Olah propose? To make AI Catholic?! Will Bin Salma…
7465431573706…
in
Abu Dhabi targeting 50% of government operations run by autonomous AI agents is …
7464647546527…
in
Anthropic, who uses AI to train CAI ( methodology) by using AI to score the rein…
7468720376626…
in
The release of Magnifica Humanitas proves that the AI revolution has officially …
7466136344793…
in
Recursive self-improvement is one of the most fascinating and important concepts…
7468898922594…
in
For the last few years, the entire AI industry operated on a simple rule: if you…
7468721438821…
in
"Intelligence is not the ability to store information, but to know where to find…
7464018054570…
Comment
Luís Rodrigues I think this has to start higher and has to go deeper. First AI is not equal AI. Anthropic and OpenAI don't share training data, prompts, weights and built in configuration. Anthrophic has 11 products that all have different limits and purposes. When using any of those everything starts with understanding the built in tools like read, webfetch. What you describe is a set of fancy over hyped key term. Behavioral patterns, known use cases. There dependencies. Guardrails, built in immutable prompts, those are the things that differentiate. An MCP an agent could be anything.. My skills in my workspace use API calls, run external judges, confirm semantically, review visually. Are those skills them agents? Can they overcome the char count limit of any built in tool?
LinkedIn
Workplace & Jobs
Senior Director — Enterprise AI Transformation …
2026-05-26T05:4…
Coding Result
| Dimension | Value |
|---|---|
| Primary value | transparency |
| Secondary value | accountability |
| Alignment target | individual_users |
| Stance | critical |
| Emotion | outrage |
| Value justification | The speaker emphasizes the importance of understanding the built-in tools and limitations of AI systems, suggesting a desire for transparency in AI development and deployment. |
| Target justification | The speaker appears to be addressing individual users, such as themselves, who need to understand the capabilities and limitations of AI systems to use them effectively. |
| Coded at | 2026-06-11T08:12:11Z |
Raw LLM Response
```json
{
"value_primary": "transparency",
"value_secondary": "accountability",
"target": "individual_users",
"stance": "critical",
"emotion": "outrage",
"value_justification": "The speaker emphasizes the importance of understanding the built-in tools and limitations of AI systems, suggesting a desire for transparency in AI development and deployment.",
"target_justification": "The speaker appears to be addressing individual users, such as themselves, who need to understand the capabilities and limitations of AI systems to use them effectively."
}
```