Safety Constraint And Alignment Framework Extraction

Extracted system prompts from ChatGPT (GPT-5.5 Thinking), Claude (Opus 4.7, Opus 4.6, Sonnet 4.6, Claude Code), Gemini (3.1 Pro, 3 Flash, Gemini CLI), Grok (4.3 beta), Perplexity, and more. Updated regularly.

Unique: Documents system-level safety implementations including Claude's prompt injection defense mechanisms, GPT-5.4's personality-based constraint modulation, and Gemini's chain-of-thought protection. Reveals how providers encode safety rules at the system prompt level rather than just through post-hoc filtering.

vs others: More transparent than provider safety documentation; shows actual system prompt constraints rather than high-level policy statements.

via “safety-and-alignment-constraint-templates”

📏 Collection of prompts/rules for use within AI Agent settings

Unique: Provides explicit safety constraint templates that can be composed with task prompts rather than relying on model training or fine-tuning — enables rapid safety iteration without retraining

vs others: Faster to implement than fine-tuning safety into models and more transparent than relying on model training, but less reliable than runtime enforcement or dedicated safety frameworks

via “model alignment and safety considerations for foundation models”


Unique: Treats alignment as an integral part of foundation model development rather than a post-hoc safety layer, covering the technical mechanisms and trade-offs involved — a perspective that was emerging in 2023 but is now standard in responsible model development.

vs others: More technical and implementation-focused than policy-oriented safety discussions; more comprehensive than vendor safety documentation; grounded in academic research while acknowledging practical constraints.

via “ai alignment problem decomposition and framing”

Youtube channel about AI safety