Grounding AI: How Agentic Workflows Eliminate Hallucinations in Career Coaching

LLM hallucinations—inventing credentials and suggesting unrealistic roles—erode trust in AI-powered career coaching. By combining Retrieval-Augmented Generation with Agentic Workflows, developers can build systems that ground responses in factual data and self-verify before outputting. This shift from single-prompt interactions to multi-agent verification loops is essential for high-stakes applications where accuracy directly shapes users' career decisions.