AI-Native CMO
A decade plus leading marketing at venture-backed technology companies, from zero-to-one functions to organizations reaching billion-dollar valuations. Now building AI marketing infrastructure at Northstar Stack.
Selected work
Each of these started with a small team, an unproven category, and a number to move. The through line is the same: find the audience, earn attention that compounds, and connect it to revenue.
Story Protocol
Led marketing for a blockchain protocol backed by $140M from a16z, Polychain, and Samsung Next. Built the go-to-market function and the community engine behind a launch that reached a $15B fully diluted valuation and a top-40 market position.
Secured coverage in TechCrunch and Variety, extending reach past the core technical audience into mainstream tech and entertainment.
1,500%Increase in signups post-launch
Scroll
Ran marketing and communications for a company valued at $1.8B. Built an audience of 800,000 to support early product releases and drove co-marketing campaigns that helped the platform pass a $1B milestone in assets held.
Coordinated more than ten founder speaking engagements and media placements to establish category authority.
800KAudience built to support launches
Supra
Directed a 12-person marketing team and a seven-figure annual budget at a 100+ employee B2B organization. Managed over 300 cross-functional partnership and integration announcements with institutions across finance, technology, and academia.
Led campaigns that raised $7.1M, and generated coverage in Nasdaq, Bloomberg, and Yahoo.
$7.1MRaised through marketing-led campaigns
Capabilities
Five layers, built over a decade plus. The AI layer on top is what makes the four beneath it move faster than they used to.
AI + AutomationThe multiplier
StackTools in daily use
Growth + DemandPipeline
Brand, Content + CommunityAttention
Leadership + OpsThe function
What I am building
Championship teams are rarely the ones with the most individual talent. They are the ones that execute well together. Marketing works the same way. Strong marketing teams underperform all the time, and rarely for a lack of effort.
The information marketing needs already exists elsewhere in the company. Sales hears the objections stalling deals, customer success knows why accounts churn, product knows what ships next. The instinctive fix is to schedule more time together, and it quietly backfires. Calendars fill, execution time disappears, strategy gets rewritten each week by whoever is loudest in the room, and teams drift into reacting to competitors instead of compounding their own advantage.
Northstar Stack removes the meeting as the primary transport layer. AI systems move the information continuously, and a shared dashboard keeps marketing's work and numbers visible to everyone, so alignment happens without spending the week getting aligned.
Visit Northstar StackPerspective
Positions I have arrived at from running the function, not from observing it. Longer essays on each are in progress.
Everyone is a marketer until the number is due.
Marketing is the only function where everyone in the room believes they are qualified. Nobody overrules the engineers on architecture. The fix is not a better argument, it is shared evidence.
The copier is always behind.
A competitor's marketing is their highlight reel, not their strategy. Reacting to it means starting their play after they have finished it, and abandoning the strategy that was compounding for you.
Marketing amplifies truth. It cannot manufacture it.
When a product resonates, marketing pours fuel on the fire. When it does not, marketing buys you clearer data faster, but it cannot compensate indefinitely for a product the market has not embraced.
Move the decision from the room to the dashboard.
When marketing runs on opinions in meetings, the loudest opinion wins. When it runs on data everyone can see, the evidence wins. That is a governance change, not an efficiency one.
The next frontier
For twenty years the question was whether your page ranked. Increasingly it is whether your brand gets cited inside the answer a model generates, because a growing share of buyers never reach a results page at all.
Answer engine optimization is early enough that most companies have not started, which is exactly why it is worth starting now. The compounding advantage goes to whoever builds the citation surface first.
The AI Tool Arsenal
Dozens launch every month and sorting the wrappers from the genuinely useful ones eats hours. Every issue puts the new arrivals into three piles, use it, watch it, skip it, with the reasoning and where each one earns a place in a real stack.
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Contact
Tell me what you are trying to fix. The more context you give, the more useful my first reply will be.