“evaluation”
Evaluating AI Agent Frameworks in 2026: An Enterprise Adoption Checklist
Key evaluation criteria for selecting an AI agent SDK: type safety, observability, state persistence, human-in-the-loop approval, sandboxing, and community support.
Feedback Loops: Turning Human Edits into Agent Improvements
Every time a human rewrites your agent's output, you throw away a training signal. A feedback loop turns those edits into datasets, evals, and measurable model improvements.
Evaluating Voice Agents: WER, Latency, and Dialogue Quality Metrics That Matter
A practical guide to measuring voice agent performance with WER, response latency, tool accuracy, and conversation quality metrics.
LLM-as-a-Judge for Agent Outputs: Strengths and Pitfalls
How to use LLMs as evaluators for agent outputs — the strengths, systematic biases, and practical debiasing strategies for production evaluation.
A/B Testing Prompts in Live Applications
You would never ship a UI change without testing it. Learn how to A/B test prompts in production: bucketing, determinism, and evaluating quality without chasing noise.
Gemini 3 in LegalTech: Automating Complex Contract Audits with High-Precision Reasoning
Contracts are full of computational clauses that probabilistic models get wrong. Learn to build a production-grade contract audit system that pairs Gemini 3 extraction with a deterministic rule engine to eliminate the "reasoning cliff" and the hallucination risk.
RAG Evaluation: Measuring Retrieval Quality Objectively
A RAG pipeline fails in two halves: retrieval and generation. Build a transparent Python eval harness computing hit_rate, MRR, context precision/recall, and faithfulness to know exactly which half to fix.
Building an Eval Test Suite for ADK Agents
Move from vibes-based testing to structured evaluation for ADK agents, tracking tool call accuracy, trajectory efficiency, and LLM-as-a-judge quality scoring.