AI intention in dashboards
AI Dashboard Strategy
Tests how structured insight modules can help people decide faster without making chat the default interface.
Build with AI
Useful AI, explainable systems, and experimentation
TLDR
What was broken
Many AI experiences add novelty without reducing effort or improving trust.
What I did
I prototype systems that test workflow fit, explainability, and useful conversational design.
Why it mattered
The experiments sharpen a practical point of view on AI that is clearer, lighter, and more humane.
Useful AIExplainable SystemsLower Cognitive Load
Why this lab exists
AI is moving quickly, which makes first principles more important, not less. I use prototypes to test when conversation helps, when structure helps more, and how explainability changes trust.
My recurring belief: useful AI should reduce effort, reduce ambiguity, and fit the workflow instead of demanding that people adapt themselves to the tool.
What I test
I explore guided dashboards, service conversations, retrieval quality, embedded assistance, and explainable systems. The lab is where theory meets practice: small experiments that sharpen how I think about better product experiences.
Live prototypes
These public experiments are the practical side of that point of view:
Useful AI for everyday decisions
Rate Advisor
Explores how comparison logic and explanation can reduce decision fatigue in a high-friction consumer choice.
Conversational design
Airline Support Chat
Tests how tone, task framing, and guided prompts can make support interactions feel clearer under pressure.
AI-ready UX and explainability
Explainable Docs Demo
Shows how retrieval structure changes answer quality and makes trust more inspectable.