Artifacts
Presentations, talks, and materials from my professional journey.
To give UC Davis MSBA students a practical view of building a career in AI and taking AI products from concept to revenue.
Distilled lessons from go-to-market roles at Reka AI, Renesas, and Micron into a structured talk covering the AI industry landscape, career paths, and enterprise sales strategy.
Microsoft PowerPoint.
Shows the ability to translate real field experience into teaching material and communicate AI strategy clearly to a graduate business audience.
To practice deep interviewing, AI prompt engineering, and AI system design by building a working Speaker's Bureau booking bot as a graded team project.
Interviewed teammates to uncover their passions beyond the resume, used generative AI to write rousing TED Talk introductions and professional speaker profiles, compiled the profiles into a knowledge base, and built a booking agent in Google AI Studio with a strict system prompt grounded only in that data. The team then produced the marketing and process infographics entirely with AI tools and demonstrated the bot live in class with unscripted audience queries.
Google AI Studio, generative AI assistants for interview synthesis and speaker profiles, AI image generation for both infographics.
Proves hands-on skill in prompt engineering, grounding a chatbot in custom data, and pairing a working AI product with AI-generated marketing, from discovery interviews to a live demo.
To critically analyze a real-world AI ethics incident and identify systemic governance failures relevant to enterprise AI deployment.
Selected the 2018 Amazon AI recruiting tool bias incident from the AI Incident Database. Analyzed three ethical issues: training data bias from historical hiring patterns, failure to act after internal bias detection in 2015, and lack of transparency with affected candidates.
AI Incident Database, Reuters investigative reporting, Claude (Anthropic) for structural organization, AIML-500 course frameworks on data ethics and model governance.
Demonstrates the ability to move beyond technical bias detection toward governance design. The key insight: Amazon's failure was not discovering bias. It was the absence of an institutional process for deciding what to do when bias is found.
To explain how neural networks work in plain language, with an original diagram, for a general audience.
Wrote an original explainer covering forward pass, backpropagation, and gradient descent. Created an inline SVG diagram showing input, hidden, and output layers with weighted connections.
HTML, CSS, inline SVG, Claude AI for drafting and diagramming.
Demonstrates the ability to distill a technical ML concept into accessible writing paired with clear visual communication.
To trace the evolution of artificial intelligence from its origins to today's generative AI era and understand the breakthroughs behind modern machine learning.
Researched the key milestones, papers, and inflection points in AI history, then organized them into a clear chronological visual presentation.
Microsoft PowerPoint and AI research assistants.
Shows the ability to distill decades of technical history into an accessible narrative and demonstrates foundational AI literacy.