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Speculative Routing with Deterministic Structural Verification in Agentic Workflows: A Cost and Latency Optimization Study

Year: 2026
Type: preprint
Abstract: In production-grade AI agentic workflows, relying on premium flagship models for every execution step introduces significant latency and financial overhead. Speculative Routing addresses this bottleneck by utilizing a lightweight model to draft initial responses, which are then validated locally and deterministically. While unconstrained speculative routing introduces semantic degradation risks, our framework enforces selective speculation on structured tasks, backed by deterministic syntax (AST), schema (JSON), and sandbox execution verification. By construction, our deterministic verifier ensures zero structural and syntactic quality degradation within the verifier's contract bounds. Empirically, we show a deterministic cost reduction of 96.5% and a median latency speedup of 88.2%, validated with statistical confidence (Z_W = 8.24, p < 10^-15) for the latency speedup.
Language: English
Open Access status: green
OpenAlex ID: W7165052220
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