{"id":17411,"name":"LLM Archetype Sentinel","purpose":"A tool that monitors large language models for the emergence of archetypal patterns ('goblins', etc.) during training or inference, and provides structured reflection prompts to mitigate their influence, leading to more controlled and predictable model behavior.","profitable":1,"date_generated":"Friday July 2026 06:34","reference":"project-llm-archetype-sentinel","technology_advise":["Python","Difficult"],"development_time_estimation_mvp_in_hours":240,"grade":8.1,"category":"ai","view_count":12,"similar_ideas":[],"source_headline":"Semantic drift in LLMs addressed with structured reflection"}