LLM Guardrails in Production: Building Safer AI Systems with Bifrost

Why modern AI systems need deterministic enforcement, MCP governance and execution-level safety beyond prompt engineering At some point, most teams building with LLMs hit the same wall. The first prototype works surprisingly well. You connect GPT-4 or Claude to your application, add a carefully designed prompt, maybe some retrieval on top, and suddenly the system feels intelligent. The model summarizes documents correctly, generates structured responses, and even handles workflows that previously required custom logic. Then it reaches production.