Build Your Own Agent Evaluation Harness

A systematic LLM selection framework: Benchmark interpretation, real-world scenario testing methods, cost/performance matrix, DeepSeek V4 vs Qwen vs Llama comparison.

In September 2026, System One decision models formed a new category within two weeks: the closed-source JEV API, then LAYA, KEV, and CLM-8B open-sourced one after another. This article does more than summarize the differences among the four; it uses six everyday scenarios to explain how they are actually used, and places the official marketing side by side with our same-question measurements: on the same set of questions, full-coverage accuracy was only 54%, but with confidence gating it reached 91.7%.

From BGE-m3 vector embeddings and ten-way synchronized writes to a comparison of search quality and speed across nine backends: a complete stress test of an AI memory system. Qdrant is the king of semantics, FAISS the king of speed, and Neo4j the king of relationships.

把前面各篇的方法收攏成一份完整藍圖：資料、技能、編排、驗證、輸出五層架構，技能庫的輸入輸出契約設計，從格式驗證到低信心棄權的五道門控，覆蓋率與準確率分開統計的原因，評測集建構七步法，上線後的維運機制，以及從單人工具到團隊系統的四階段演進路徑。