Embed, retrieve, let the LLM decide works for about 100 tools. At 1,000 it needs a control plane: hybrid retrieval, hard filters, a learned reranker, progressive disclosure and per-stage evals.
Tool Selection at Scale: What Top-K RAG Leaves Out
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Author: Cyrus Wong (黃俊彥) — Google Developer Expert - Cloud (AI), Senior Lecturer at HKIIT ...
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How to Test an LLM When Pass/Fail Doesn't Work: A Practical Guide to AI Evaluation
A practical toolkit for evaluating LLM features: golden datasets, scored metrics, safety tests, CI gates, and production monitoring.