We've built careers leading go-to-market transformation at enterprise scale - and carrying the number through it.
Post-acquisition integrations. CRM migrations lived end to end. Billion-dollar pipeline engines. Martech rolled out across regions, languages, and segments. The technology always mattered - and it was never the hard part. Change comes down to people. They have to see the vision, understand the work, and get through it as a team.
The AI chapter is already written into that CV. Two and a half years building an AI-native marketing function from the inside - context systems, agent harnesses, evals on real accounts - tripling pipeline per rep on the same headcount. An AI-native workforce platform taken from concept to nationwide deployment. We didn't study this transformation. We've been running it.
Bigger than the cloud shift. Bigger than the CRM era. And it lands on teams that still have a quarter to close.
It also lands harder in go-to-market than anywhere else. AI is superhuman on some tasks and unusable on others that look simpler - and most GTM work still sits on the wrong side of that line, because the context that makes the work good has never been written down, and the tasks were never defined sharply enough to hand off.
The full argument - and the two conditions that move work across the frontier - is in our research: The Jagged GTM Frontier
Every organization starts this change from a different place, so the work starts by finding yours.
We embed as your chief of staff for AI. Four to six weeks inside the org: interviews at every altitude, your operating reality mapped into a context graph built for your org alone, current best practice weighed against how your company actually runs. You leave with a roadmap - where AI moves your numbers, what to build first, what it takes to deliver - and the plan is yours to run, with us or without us. It's a paid engagement that stands on its own, and it's how both sides decide the bigger work on evidence instead of a pitch.
One focus from the roadmap, delivered: your context systems, your AI harnesses and the tasks that run in them, or the enablement of your team. Working software on your real accounts, owners named, results measured against a baseline. We only build on a map - discovery comes first, every time.
We stay embedded with your team for the year and run the AI experiments that move the revenue numbers named in your plan - one after another, each building on the last, with your people learning the pattern by running it beside us.
If what you need is a room of leaders aligned - an offsite, an annual planning cycle, a kickoff that sets the AI agenda - we do that at smaller scale.
Your people build it. We install the pattern. From early in the engagement we train a cohort inside your team - the ones who own the system after we're gone. The build team is small. The team that runs it is your whole go-to-market org. The decisions that matter never leave your side of the table.
The pattern comes from having lived it.
Growth leader at enterprise scale - ran a 230-person B2B marketing organization at Adobe through the acquisitions that reshaped it - and an Inc. 500 founder out of a Stanford startup incubator. Spent the last two and a half years at WorkSpan building an AI-native marketing function from the inside, tripling pipeline per rep on the same headcount. He leads the vision and the executive alignment: the part where a transformation gets bought at the top or quietly dies.
Took the AI-native workforce platform at Forward from concept to nationwide deployment. Before that, ran data engineering and platform at ApplePie Capital, through more than $200M in loan transactions. Harvard, Psychology and Computer Science. He lives in the build - the harness, the context graph, the evals - and turns the operating model into software your team can actually run.
Five-plus years inside go-to-market organizations where enterprise complexity meets real scale. She runs the delivery plan, the stakeholder interviews, and the operating cadence - the unglamorous machinery that makes a transformation survive contact with the org chart. When the change takes and doesn't snap back the quarter after we leave, this is why.
