This article was originally published on AI Study Room . For the full version with working code examples and related articles, visit the original post. LLM Safety: RLHF, Constitutional AI, Content Filtering, Red Teaming Introduction As LLMs are deployed in sensitive applications, safety mechanisms are essential. Models can produce harmful content, leak private information, or be manipulated through prompt injection. This article covers the four layers of LLM safety: training-time alignment through RLHF, runtime constraints with Constitutional AI, automated content filtering, and adversarial testing via red teaming.…