I've been in data and software engineering for more than 20 years. I started as a DBA when data wasn't trendy, moved through software and platform engineering leadership, and now serve as EVP Technology and Engineering at a global technology company.

Along the way, I ran data platforms at scale, spearheaded Hadoop adoption when most enterprises were skeptical, and used machine learning before it was a boardroom topic. I've led platform engineering organizations through transformations focused on infinite scalability and direct P&L contribution —building teams and architectures that scale infinitely while delivering measurable business value.

I've watched every major wave come through—Big Data, public clouds, ML, AI, LLMs—and learned that the gap between transformation intent and in context transformation delivered is where most hype goes to die.

Then agentic coding came along. And for the first time in years, I felt genuinely excited.

I couldn't just watch from the sidelines. So I built a production-grade pet project to test it myself—cloud native, multi-tenant, DR ready, HA, infinitely scalable, and configuration-based for self-service business operations. Because the goal for transformations should always be production deployment and P&L impact. Because if it can't ship, it can't teach me what I need to know.

What I discovered convinced me: this will fundamentally change how we do software engineering. The cards are being reshuffled. Agentic-native companies and startups will redefine what's possible.

This blog is where I share what I'm learning—visionary, strategic, and tactical perspectives on the rise of the agentic-native company. For engineering leaders, founders, and advisors who want signal, not noise.

I'm interested in your thoughts and comments—on the articles or directly on LinkedIn.