Decoupling Search from Reasoning: A Vendor-Agnostic Grounding Architecture for LLM Agents

Researchers introduced Decoupled Search Grounding (DSG), a vendor-agnostic architecture that separates search from reasoning in LLM agents, enabling independent control over retrieval policy, provider routing, and caching. In tests across five frontier models, DSG nearly matched native search accuracy on SimpleQA (86.1% vs. 87.7%) while reducing search costs by 91%, achieving 99.4% warm-cache hit rates and 68% lower latency. The approach also cut search costs by over 98% on an e-commerce query-understanding workload, suggesting real-time grounding should be treated as an optimizable interface rather than a fixed model feature.

arXiv:2606.18947v1 Announce Type: new Abstract: Production LLM agents increasingly depend on real-time search, yet native search grounding bundles retrieval policy, provider choice, evidence injection, cost, latency, and generation behavior behind a single model-provider boundary. This coupling makes grounding hard to inspect, tune, reuse, or port, and can trigger Search-Induced Verbosity that breaks strict output contracts. We present Decoupled Search Grounding DSG , a vendor-agnostic boundary that moves grounding outside the reasoning model through an MCP-compatible gateway, exposing provider routing, source-aware context rendering, configured fallback, retrieval-depth control, and exact plus semantic caching as first-class controls. Across five frontier models on SimpleQA, FreshQA, and HotpotQA, native search leads on recency-sensitive FreshQA, but DSG exposes a stronger frontier when control matters: on SimpleQA it nearly matches native accuracy 86.1% vs. 87.7% at 91% lower search cost, preserves concise answer contracts, and reaches a 99.4% warm-cache hit rate with 68% lower latency. Deployed as a shared production grounding layer for large-scale agentic workloads with interchangeable models, DSG matches or slightly exceeds native-search accuracy on an e-commerce query-understanding QIU workload while cutting search cost by over 98%. Real-time grounding is best treated as an optimizable interface boundary, not a fixed model feature.