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Speculative Ad-hoc Querying
Large language models (LLMs) invite substantial effort and investment, yet agentic systems can spend much of their time waiting for tools. This paper explores how a small auxiliary LLM can reduce these waits by speculatively preparing a database while the primary LLM reasons. The challenge is that
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