AI Sandbox: Expriementation = Relevancy
I created this sandbox to explore UX, AI, and product design in a way I couldn’t find elsewhere — practical, hands-on, and transparent. I learn by reading and doing. Along the way, I’ll share short, concise case studies documenting what I built and what I learned.
These pillars help keep me focused, experimental, and accountable — structured enough to create momentum, flexible enough to allow discovery.
Use AI Intentionally
Use AI tools across the full spectrum of exploration — notation, ideation, research, design, prototyping, and the unknown.
Experimentation Over Perfection
If I end up in a cul-de-sac, that’s okay. I’d rather have taken the trip then not attempted the journey at all. Every detour teaches me something.
Reflect Before Resetting
At the end of each experiment, I step back. I compare where I started to where I finished, even if it’s incomplete.
Use Domain Knowledge
Focus on travel. I know the ecosystem, the users, the edge cases, and the competitive landscape. Familiar context allows me to experiment faster and push ideas further.
Don’t Boil The Ocean
Play with common travel problems that need solving, but don’t get bogged down unnecessarily. Play, learn, share. Repeat.
Make It Inclusive
Inclusive design is built in, not layered on. Experiments should account for assistive technologies and real-world constraints.
Building on Experiment 3, I prompted the agent to generate accessibility annotations using a prescribed structure and methodology to evaluate efficiency and accuracy.
Application: v0 by Vercel
This experiment marked my first deliberate accessibility review using assistive technology on a live interface. As someone primarily focused on front-end design, this was an opportunity to move beyond structural assumptions and validate decisions through real interaction.
Application: v0 by Vercel
Recreates a system-based lodging page in live code using v0, then introduced dynamic traveler-specific modules to test layout mechanics and interaction behavior.
Application: v0 by Vercel
Tests whether a static system screenshot could become a functional proof of concept using AI. The experiment shifts from replication to controlled, audience-driven iteration.
Application: UXPilot
About AI Sandbox
I plan to complete one to three experiments per week, depending on scope and time.
The goal is consistency over intensity. Each experiment isolates a specific design question and tests how AI tools can accelerate, challenge, or reshape the workflow. I’ll revisit similar problems across different AI platforms to compare outputs, assumptions, and integration patterns.
My goal isn’t just to understand these tools, but to use them in practical scenarios so I can speak about them with clarity and confidence. Hands-on application helps me see where they’re effective, where they fall short, and how they fit into real workflows. It also keeps me current as the tools and expectations continue to evolve.