AI · Evaluation
AI Response Evaluation Lab
Rubric-based AI response evaluation lab focused on accuracy, instruction following, completeness, clarity and safety. Structured scoring across multiple response dimensions.
AI Playground
AI Evaluation & Quality.
Structured evaluation projects focused on AI response quality, prompt robustness, LLM comparison and rubric-based feedback systems. Each project documents the evaluation criteria, methodology, findings and lessons learned.
Selected Projects
A curated set of AI evaluation experiments built to demonstrate structured quality review, scoring methodology and practical LLM analysis.
QA · Support
Customer Support Email QA
Simulated customer support email QA project focused on tone, accuracy, empathy, resolution clarity and escalation handling. Practical quality review applied to real support scenarios.
AI · Prompting
Prompt Robustness Testing
Prompt robustness testing lab analyzing AI behavior under ambiguity, conflicting instructions, formatting changes and edge cases. Focused on identifying failure modes and consistency gaps.
AI · Comparison
LLM Comparison Matrix
Structured comparison matrix evaluating AI-generated responses using accuracy, clarity, formatting, instruction following and usefulness criteria. Side-by-side model analysis with consistent scoring.
Why this section exists
These projects are not just documentation exercises. They reflect how I approach AI quality work in practice: defining clear evaluation criteria, applying consistent rubrics, identifying patterns in model behavior and turning findings into structured, reusable review frameworks.