Stress-Test Your RAG Pipeline Before Users Find Its Weak Points
Small adversarial test sets target synonym, ambiguity, metadata, and multi-hop gaps to expose RAG retrieval failures before users encounter them.
Evaluation
Part 3 of Tuning Jev explains that tuning is task-specific and shows four places to put few-shot examples.
Jev few-shot tests compare four example placements. None wins everywhere; flattened state favors risk but causes significant quality regression.
Your Agent Nailed the Task. Can It Repeat the Success?
Benchmark averages hide a serious reliability problem in LLM agents: a GPT-4.1 ReAct agent scoring 77.4% average success (Mean@5) passed all five repeated runs on only 53% of tasks — a 24.4-point cons…
A Practical Guide to Creating Strong Evaluations for AI Agents
A practical guide for developers building AI agents, explaining why agent evaluation is harder than single LLM call testing. It covers the three failure layers—reasoning, action, and execution—how to …