Human judgment.
AI-powered possibilities.
How I'm exploring AI in modern product design: from research and rapid prototyping to designing reliable human–AI interactions. A living learning roadmap—not a list of completed client engagements.
Discuss an AI product ideaTwo different design challenges.
Accelerate the process.
Summarize research, explore alternative flows, generate prototypes, refine copy, and shorten the distance between design and working code.
Make intelligence usable.
Design copilots, recommendations, conversational interactions, automation with approval, trust, feedback, and safe recovery when a model is wrong.
What I'm learning and applying.
AI UX patterns
Conversational interfaces, prompt guidance, confidence, citations, controls, escalation, feedback and error recovery.
DESIGNING FOR AIAI-assisted research
Interview synthesis, theme clustering, hypothesis generation, and reviewing AI interpretations against real source evidence.
RESEARCHRapid functional prototyping
Build working flows using Figma Make or code assistants, then validate interaction quality rather than trusting generated UI.
PROTOTYPINGAI-native product flows
Copilots, support-assistant workflows, smart search, recommendations, automation and human approval loops.
PRODUCT STRATEGYDesign systems for AI
Reusable components for chat, agent progress, source attribution, loading, model uncertainty, review and retry states.
SYSTEMSEvaluation and responsible AI
Assess usefulness, task success, failure modes, privacy, bias, accessibility and user trust with observable criteria.
VALIDATION