Raw LLM Responses

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Paul Crinigan I didn't Experiance that, AI developed my autonomous crypto trading bot and created and trained the 5 ML models it depends on for probability analysis. It also continually improves itself, catches and fixes errors and self executes ML training updates and recursive testing of algorithms it created. Structured prompts, boundaries, and all the other discipline we already use for developing apps must be included in the build pipeline. WBS, dependency and code maps as well as full regression testing of back and front ends after each WP step critical.
LinkedIn AI Safety & Risk Director Technical Services & Sr. Manager SAP B… 2026-06-05T22:3…
Coding Result
DimensionValue
Primary valueaccountability
Secondary valuenone
Alignment targetindividual_users
Stancedemanding
Emotionapproval
Value justificationThe speaker emphasizes the need for structured prompts, boundaries, and discipline in the build pipeline, indicating a desire for accountability in AI development.
Target justificationThe speaker shares their personal experience with AI developing an autonomous crypto trading bot, suggesting that the target of alignment is individual users like themselves.
Coded at2026-06-11T08:39:32Z
Raw LLM Response
```json { "value_primary": "accountability", "value_secondary": "none", "target": "individual_users", "stance": "demanding", "emotion": "approval", "value_justification": "The speaker emphasizes the need for structured prompts, boundaries, and discipline in the build pipeline, indicating a desire for accountability in AI development.", "target_justification": "The speaker shares their personal experience with AI developing an autonomous crypto trading bot, suggesting that the target of alignment is individual users like themselves." } ```