Sales trajectory · Moat · A.I. · for tech CEOs
Helped Legitmix achieve 600% sales growth.
“Thanks to Adrian, the fog has lifted, I’m now navigating towards success, and the metrics prove it.”
Adrian Scott, Ph.D.
Founder of Ryze · Investor in Napster and On24 · Ph.D. in optimization
600%
sales growth at Legitmix
−100%
advertising spend, same company
1st
Silicon Valley institutional round
Invested in or advised, with exits
On24 (IPO) · Starmine (Thomson Reuters) · Plaxo (Comcast) · Giganet (Emulex) · BuyDirect.com
Founding investor in Napster · Founder of Ryze
Case study · Legitmix
Before
A lot of effort and money going into product features and marketing campaigns, with little to show for it.
What changed
Adrian joined the board and reframed the question from what to do to what to learn, then put frameworks and metrics in place to turn data into decisions.
After
“Adrian asked the simple question: what do I need to learn to succeed. This simple question was an epiphany for me. … Thanks to Adrian, the fog has lifted, I’m now navigating towards success, and the metrics prove it.”
Case study · Enterprise A.I. company
+100%
Sales growth
A new sales trajectory for an enterprise A.I. company.
Media moat
Build-out underway
Thousands of subscribers, thousands of views
An owned audience and body of content that keeps compounding, and that competitors can’t simply buy.
“Love it. This is it. Things are getting so clear now.”
Outcome 1
For when revenue is flat, lumpy or still depends on the founder, and effort on features and campaigns barely moves the numbers.
Outcome 2
For when your pitch sounds like everyone else’s, deals get discounted, and investors keep asking, “What’s your moat?”
Outcome 3
For when you can’t yet say what A.I. means for your market, product and team, or which A.I. features a competitor could copy in a weekend.
The approach
Tailored to your goals, strengths, and resources.
Examples of what we might work on in a call:
Immediate wins. Long-term priorities.
Why the A.I. advice is different
I build with LLMs directly, so advice is grounded in what models can and can’t do today, not in vendor demos or headlines.
Training a model is an optimization problem. My Ph.D. is in nonlinear optimization, so I know where the leverage and the limits come from.
That lets us separate A.I. features any competitor can ship in a weekend from the ones that compound into a moat.
So it matters that we’re a fit before we start.
Work with me
Both options are tailored to your company. The difference is how much of my energy goes to your company alone.
Group working call 3x a month + private monthly 1:1
The method in a small group of peer CEOs working on the same questions.
Limited availability
Weekly 1:1
For CEOs facing a fundraise, a sharp turn or a fast-moving A.I. shift in their market.
By application
Why me
So I look at your sales the way a board member, a buyer and a builder would, all at once.
Start with a short intro call. We’ll look at where revenue comes from today and whether we’re a fit.
Or get an intro from a mutual friend.