About
Five chapters, not a straight line. Each one taught a capability the last one didn't have — and together they became the way I build systems today.
I started in industrial gas and applications sales, carrying a bag and a quota. There's no abstraction between you and the customer at that stage — you either understand what they actually need, or you don't close. Standing up a new applications vertical at SICGILSOL meant learning to build trust from zero, with no brand and no case studies to lean on.
A refusal to design systems from the inside out. Every process I build still starts with what the customer is actually trying to get done.
Selling closes one deal at a time; marketing has to work at scale, on people you'll never speak to. At ekincare I learned to move enterprise buyers and end users with the same campaign under real budget pressure. At Publicis Sapient and Encora I moved into the machinery behind demand — outbound systems, marketing automation platforms, and the agentic workflows that are starting to replace manual campaign ops.
An instinct for behaviour at scale — how audiences actually move through a funnel, and where marketing automation earns its keep versus where it just adds noise.
This is where I stopped thinking in campaigns and deals and started thinking in loops: ownership, handoffs, checkpoints, feedback. At HCL I built whitespace and scoring tools for a sales org generating most of the company's revenue. At Hevo I stood up a customer success function from nothing and had to own outcomes for hundreds of enterprise accounts, not just influence them.
Process and ownership. A system without a clear owner and a feedback loop isn't a system — it's a hope.
Everything before this taught me what to build and why. This is where I learned to build it myself — data pipelines, automation, AI agents — instead of briefing someone else to. ICB is a solo-built product: scraping, schema, SEO and AI-assisted content running end to end with no team behind it. Emergence AI puts the same instinct to work from inside a live revenue org, designing AI-native GTM systems where I'm both the operator and the builder.
Leverage. Once you can build the system, not just design it, headcount stops being the constraint on how much you can improve.
You can get away with a fuzzy mental model when you're the one executing. You can't get away with it in front of a room of practitioners who will ask you to explain, right now, why a step exists. Teaching Gen AI and GTM at NSBT forces me to turn instinct into a method I can actually hand to someone else — which is most of why this six-step operating loop exists in a form clear enough to publish.
Clarity. If I can't explain a system simply enough to teach it, I don't understand it well enough to build it.
Every chapter added another layer. Together, they became the way I build systems today.
See the systems this built →