I build internal products and business systems that help revenue teams work with more clarity, consistency, and leverage. My work sits between product strategy, GTM operations, workflow design, and AI-assisted execution.
These are real product directions and working systems, presented with synthetic data and generalized interfaces where the underlying work is internal. The through-line is turning messy GTM workflows into visible, maintainable products.
A full seller workflow system that has evolved through multiple iterations. The Command Center is its latest operating surface: the right next action, useful context, and fewer record hops.
A reusable, record-aware context layer that gives NetSuite AI tools workflow, audience, field meaning, and review boundaries instead of raw schema alone.
A governed seller workflow joining stage guidance, Smart Notes verification, contact selection, and clearly bounded scheduling actions.
A design for connecting meeting intelligence to the right NetSuite customer, opportunity, contact, and activity context with privacy and auditability in view.
A source-linked schema explorer that turns metadata, forms, relationships, and confidence boundaries into a safer implementation contract.
An N-of-1 study tool testing delayed recall, transfer, confidence, time, and enjoyment instead of treating “learning style” as a conclusion.
A catalog-first intake and operating-model proof of concept that turns dispersed requests, stakeholders, process evidence, and decisions into a testable product definition.
A reusable internal build-and-learning system for preserving evidence, testing UIF components in context, documenting constraints, and carrying good patterns forward.
I start with the job to be done, make the invisible workflow concrete, and use short feedback loops to move from ambiguity to something a team can trust.
Not a list of tools for their own sake. A set of ways to make complex work more visible, usable, and adaptable.
Roadmaps, requirements, workflow surfaces, UAT, rollout, and adoption for the systems teams use every day.
Seller workflows, revenue operations, enablement, CRM data models, and the handoffs between them.
Rapid prototypes and practical AI adoption with configurable context, evaluation loops, human review, and governance.
Source-linked artifacts that separate what is known, what is inferred, what shipped, and what still needs to be tested.
“The work is strongest where the problem is ambiguous, the workflow is real, and someone needs to move from ‘we know this is broken’ to ‘we understand the system well enough to change it safely.’”
The final site will grow as project stories, artifacts, and interactive demos are made safe to share. For now, this is the shape of the work and the way I approach it.