Rodrigo Florencio, CEA — Postgraduate in Artificial Intelligence at POLI USP and Blockchain Dev |Crypto enthusiast since 2017| Generative Engine Optimization specialist at GenSearch Me |Product Manager with 7 years of experience

Postgraduate in Artificial Intelligence at POLI USP and Blockchain Dev |Crypto enthusiast since 2017| Generative Engine Optimization specialist at GenSearch Me |Product Manager with 7 years of experience

Rodrigo Florencio, CEA ranks #433 of 14,983 LinkedIn creators in Higher Education, and is a standout voice in Brazil. They have 3.8K followers and published 19 posts in the last 30 days at a 5.4% average engagement rate.

The roast

Rodrigo is a Generative Engine Optimization specialist, which is just fancy LinkedIn talk for spending seven years practicing how to make AI hallucinate professional value where there is none. He claims to teach an MBA at FAAP, but the only lesson he’s mastered is how to curate a career as a glorified prompt engineer for his own ego.

About Rodrigo

AI Product Builder driven by curiosity and a strong bias for experimentation. I’ve always been self-taught and deeply curious about how things work. Today, with the rise of Large Language Models, I’m able to turn ideas into working systems quickly, building and testing continuously across different domains. What started as curiosity became both my work and my daily practice. I actively experiment with AI in real scenarios, building MCP servers, prototyping agent-based systems, and testing new models across text, voice, and multimodal interfaces. I closely follow the evolution of the field, exploring releases from models like Claude, Mistral, Qwen, and Gemma, and understanding their trade-offs in practice, including running open source models locally on constrained hardware. Professionally, I focus on applying AI where it creates real value. I have experience putting AI agents into production workflows, aligning business needs with engineering and security constraints. As Cofounder of VeeCee, I built an AI-driven platform used by 130+ investors and 260+ startups. At GenSearch, I develop systems to monitor and improve how AI models generate answers about brands in real environments. My work sits at the intersection of product, experimentation, and applied AI. I am particularly interested in making AI systems more reliable, more human-aware, and more useful in real-world decision contexts, while helping people interact with them in a more structured and rational way.

Highlights

Recent posts