My wife, our dog Charlemagne, and me.
I survived because the science reached me.
That's what drove me into deep tech — to fight back.
I built systems that halted drug diversion and privacy breaches, directly protecting patients from harm. Our technology achieved the highest KLAS score ever for patient safety monitoring.
I developed the AI powering 2.2 million drug experiments weekly, compressing years of research into weeks. Our goal: accelerate critical cures to patients when they need them most.
$2 billion, 15 years, most fail
AI tests millions of possibilities in weeks
65 petabytes of biological data
Then I realized something terrible.
The builders, immensely proud, hailed it as their magnum opus.
Executives championed it to Wall Street as a triumph of innovation.
Drug programs lauded its constant ability to "save weeks" and "de-risk development."
The verdict was unanimous: this was undeniably impactful.
Drug programs hit their milestones on schedule. Scientists used their own judgment like they always had.
If it actually saved weeks, they'd yell when it broke.
But they weren't yelling.
They learned to go along with the program.
Built Translation Platform team
Cut drug-to-trial time in half
Created predictive models
Harder than Harvard
The hurdle isn't building breakthrough AI. It's the human element: translating innovation into irresistible adoption.
At Techstars, I watched brilliant founders make avoidable mistakes — not because they lacked data, but because no one would tell them what it meant. The honesty gap isn't a character flaw. It's a structural problem.
The honest conversation you can't have anywhere else
The honesty gap
Executives making $20M decisions with nobody willing to push back. Your team won't tell you the hard truth. Your coach isn't awake at 11pm. ChatGPT agrees with everything you say.
Six expert perspectives that debate each other, challenge your assumptions, and force you to see what you're missing.
The ones where you need someone to say 'have you considered that this could blow up?'
Cost, ROI and risk
Feasibility and throughput
Positioning and demand
Biases and incentives
Practical experience
Scaling and acceleration
They debate each other. They challenge your assumptions. They disagree.
You get a map of the decision space, not a single answer.
+$20M value created
"Exclusivity is the most expensive thing you can give away for free. The $25M wasn't a ceiling — it was a floor."
— Sopheva's David Rubenstein (Carlyle Group founder)
I survived because the science reached me.
Now I'm building something so the truth reaches you.
The Translation Problem