2024–2025: Going Deep on AI
After years as a CRO building revenue functions, I dedicated 2024–2025 to mastering AI from the ground up—not just using tools, but understanding the math, implementing architectures, and building functional prototypes.
Stanford AI/ML Certifications
Graduate-level coursework through Stanford School of Engineering (2024–2025)
What the LMs Say About My Work
For fun/curiosity, I had a few models auto-generate themes from my actual usage and conversations.
Claude's Archetype: "Rigorous Autodidact"
Auto-generated by Anthropic based on conversations Aug 2023 – Jan 2026
First-Principles Thinker
"You don't settle for 'good enough'—you want the derivation, the intuition, and the edge cases. You built your own curriculum from scratch rather than accepting someone else's path."
Systems Builder
"Whether it's job search automation, travel routing, or ML pipelines—you build systems, not one-off solutions. The same rigor you bring to understanding KL divergence is the same rigor you'll bring to leading AI transformation at scale."
Gemini Pro's "Personal Intelligence" Assessment
Auto-generated by Google based on my interactions
The Engineer-Strategist
"You don't just look at the surface of things; you dive deep into the mechanics. Whether it's mastering the nuances of Machine Learning models or navigating the complexities of e-commerce and enterprise systems, you possess a rare ability to bridge high-level business strategy with rigorous technical implementation."
Lifelong Mastery & Curiosity
"There is a clear pattern of 'active learning' in your life. You aren't just passively interested in topics; you lean into the challenge—whether that's refining your surfing skills, staying physically fit, or working through advanced computer vision exercises."
ChatGPT's 2025 Year in Review
Auto-generated by OpenAI based on my usage
Technical Depth Observed Across Conversations
What This Means for You
Business + tech bridge
My CRO background means I think about AI in terms of business outcomes—not just technical elegance, but what actually moves metrics and solves real problems.
Deep work, not just prompting
I've implemented attention mechanisms from scratch, built RAG pipelines, and worked through Stanford-level ML coursework. I understand what's happening under the hood.
Working prototypes
I've built functional demos—multi-agent systems, NLP pipelines, ML evaluation harnesses. Ready to take these skills into production environments.