My story

Why GTM engineering.

Dear Hiring Team,

I didn't start my career as a GTM Engineer. I started as the person who had to use GTM systems.

My background is in Management Information Systems, but I began my career on the revenue side: first as an SDR, then SDR Team Lead, and eventually Account Executive. That combination led me to become increasingly obsessed with one question:

Why are we asking expensive salespeople to do work that software can do better?

At FiscalNote, I was an early adopter of Clay and began using automation and waterfall enrichment to approach prospecting differently. I consistently operated at approximately 110% of a 16-meeting monthly quota while maintaining among the lowest activity levels on the team and one of the highest booking rates.

The lesson was simple: more activity wasn't necessarily the answer. Better data and better targeting were.

I carried that philosophy into my Account Executive work.

At Quorum, I wanted to know which companies in our market were already paying competitors. Rather than asking sellers to research accounts individually, I built a script that scanned more than 50,000 prospect websites in approximately three days.

It identified more than 5,000 competitor customers.

We could now approach those accounts knowing what technology they were likely using, understand approximate competitive pricing, and tailor the sales conversation around displacement rather than sending generic outreach. I trained other sellers on the workflow and provided the scripts and implementation logic to Revenue Operations for broader adoption. Targeted opportunities saw an estimated ~25% improvement in close rate.

I kept building.

Another workflow reduced account mapping from roughly four hours per seller per day to 30 minutes, an 87.5% reduction that returned approximately 17.5 hours of capacity to each rep every week.

Eventually, I began asking why we were researching accounts individually at all.

Today, I've built GTM intelligence infrastructure capable of deploying 100 to 500 parallel AI research agents across an organization's entire addressable market. Depending on research depth, the system can analyze approximately 50,000 companies overnight or 100,000 over two nights, combining paid databases, public data, niche sources, APIs, and AI enrichment.

Those systems reach approximately 95% enrichment coverage and approximately 98% classification accuracy after validation, while monitoring signals such as hiring, reviews, competitor usage, expansion, technology changes, growth, and other ICP-specific events.

I've also built and operated the activation layer behind these systems: more than 500 sending domains, 1,000 inboxes, and infrastructure supporting approximately 500,000 targeted emails per month. Across my sales, consulting, and GTM work, the systems I've built or operated have generated or influenced more than $20M in pipeline.

The common thread isn't a particular AI model, enrichment provider, or automation platform.

It's leverage.

I look at a revenue organization and ask:

• Where are sellers spending time that doesn't require a seller?
• What information is missing from the CRM?
• Can we map the entire market instead of buying another static list?
• What signals tell us why an account should be contacted now?
• Can we turn successful individual workflows into systems the entire organization can use?
• And most importantly: did what we built improve meetings, opportunities, seller capacity, pipeline, or revenue?

That's the perspective I would bring to your GTM team: the experience of someone who has carried the quota, managed the territory, built the pipeline, identified the bottlenecks, and then learned how to build the systems that solve them.

Tam Nguyen