Choose Your Level
Pick the difficulty that matches where you are. You can come back and try a harder level later.
Create a Golden Test Set
Create 10 test cases to evaluate a new customer support prompt.
Write an LLM-as-a-Judge Prompt
Use GPT-4 to grade the outputs of a smaller, cheaper model.
Design an A/B Testing Framework
Compare two different prompts in production and determine the winner statistically.
LLM Output Evaluation & Benchmarking Rubrics (LLM-as-a-Judge)
Rigorous evaluation guarantees AI applications maintain quality in production. AI QA engineers evaluate LLM applications using LLM-as-a-Judge methodologies, RAG Triad metrics (Context Relevance, Groundedness, Answer Relevance), scoring rubrics, and automated test datasets.
1. LLM Evaluation Rubric & Scoring Matrix
Multi-dimensional scoring rubric evaluating accuracy, tone, compliance, completeness, and hallucination rates.
2. Automated LLM-as-a-Judge Test Suite
Python test script using a powerful evaluator LLM (e.g. GPT-4o) to grade application responses against ground-truth datasets.
3. RAG Triad Performance Benchmark Report
Benchmark report evaluating Context Relevance, Groundedness (Faithfulness), and Answer Relevance scores.
Frequently Asked Questions (AI Evaluation & Benchmarking)
What is the LLM-as-a-Judge evaluation methodology?
Using a high-capability LLM (like GPT-4o or Claude 3.5 Sonnet) as an automated evaluator to grade candidate model outputs against structured scoring rubrics and reference answers.
What are the 3 metrics of the RAG Triad?
1. Context Relevance (was retrieved context relevant to query?), 2. Groundedness / Faithfulness (is the answer derived solely from retrieved context?), 3. Answer Relevance (does the answer directly address the user query?).
How do you detect hallucinations programmatically?
Compare claims in the model's output against facts in the retrieved context using NLI (Natural Language Inference) premise-entailment verification.
Explore AI & Prompting Career Paths
Build proof of work across other topics or view full career roadmaps mapping technical skills to hiring expectations.