How a Shared Search Layer Can Reduce Outdated Answers in Agent Graphs

Agent graph frameworks help AI systems plan tasks, call tools, and maintain state, but they can still produce confidently wrong answers when relying on outdated or unverifiable information. A proposed architecture addresses this by treating real-time search as a shared evidence layer rather than giving each node its own independent search tool. In this design, the workflow is divided into specialized nodes — router, query planner, search, source verifier, and answer generator — each with a narrower responsibility. Search results are normalized into a common evidence object so that citation metadata, source recency, and relevance scores are preserved consistently across the entire graph. The approach is described as provider-agnostic and compatible with any search API that returns structured results and source metadata.