About

The thesis

Growth problems are usually systems problems wearing a sales costume. A missed forecast, a slow quote, a pipeline nobody trusts — behind each one is a data model, a process, or an incentive that was never designed, only accumulated. I build the operating systems for growth: the architecture, automation, and cadence that make revenue predictable instead of heroic.

Three chapters

01 Operations from the ground up

I learned revenue operations from inside it — marketing ops, sales ops, the unglamorous plumbing of B2B SaaS. Salesforce became my native environment: certifications, architecture, and years of production systems.

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02 Systems at leadership scope

The work grew from building reports to building the machine: CPQ and quote-to-cash transformations, GTM data models, revenue technology strategy, and the teams that run them.

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03 Building my own

The same discipline, applied to my own companies and products — software, hardware, and operating businesses, from robotic handwriting machines to revenue systems consulting.

How I operate

• Diagnose before prescribing — most GTM stacks fail on data model, not tooling.
• Build the system, then the automation, then the dashboard. In that order.
• Distinguish my decisions from my team’s output. Credit is a data-quality issue too.
• Ship. A running system beats a perfect deck.

Off the clock

Cooking, travel, languages, lifting heavy things, and building physical products — lately, 3D-printed hardware and machines that hold pens. What I do doesn’t make me who I am, but it does keep the workshop full.