I work at the intersection of AI and go-to-market.

For most of the last decade, go-to-market meant the same thing everywhere: build a funnel, hire SDRs, run sequences, measure MQLs. The playbook was settled. The job was execution.

That changed fast. AI compressed the cost of every repeatable GTM motion to near zero. Buyers started doing in an afternoon what used to take a six-week sales cycle. The funnel didn't get faster. It started dissolving.

I got interested in that moment. Not in AI as a feature to bolt onto existing workflows, but in what actually changes when the information asymmetry that justified the entire GTM stack disappears. The answer, I think, is most of it.

My background is in the operational side of revenue: RevOps, pipeline architecture, demand generation, and the systems that connect them. I've spent time inside the machinery that most companies use to move prospects from aware to closed. That background is useful now because the replacement isn't being designed by people who understand what they're replacing.

This site is where I think out loud about that transition. Four essays up so far. More in progress. A playground for sales and marketing teams built on the Mistral API is coming here too.

If you're hiring for AI-native GTM, RevOps, or marketing strategy, or if you're building something at this intersection and want to compare notes, the connect page works.