Designing layered guardrails for reliable AI agents | Decagon

This post details the implementation of layered guardrails for AI agents to ensure reliability, safety, and brand alignment. It describes regression testing (single-turn and multi-turn interactions) before deployment, real-time guardrails during conversations (bad actor detection, human agent escalations, brand voice guidelines, response supervision) using separate fine-tuned models with minimal latency impact, and post-conversation analysis with Watchtower for continuous improvement. The technical depth includes details on how these guardrails function, such as parallel processing for bad actor detection and supervisor models evaluating responses for grounding and accuracy.