Four ways to work together.
Speaking, consulting, advising, hiring. Every lane runs through the same operator — with the same standard for pace, honesty, and outcome.
Talks, panels, and podcasts on AI-native operations.
Selective, prepared, and worth the audience's time. Written and delivered by the operator, not a comms team.
Outcome as a Service. On human capital, after AI.
Why the next decade of workforce software will be sold as measurable outcomes, not subscriptions.
The operator moat in AI.
The next wave of billion-dollar AI companies won't be built by ML PhDs in San Francisco; they'll be built by operators who lived the problem in regulated industries.
Building a national company without engineers.
A team of four built a healthcare AI platform serving 78,000+ clinicians. What it took, and what nobody warns you about.
One day. One question. One plan.
A single, focused engagement for healthcare and staffing operators who need to figure out where AI actually earns its keep — before spending twelve months and seven figures learning the same thing.
The AI Operating Day.
A single, on-site day with your leadership team — CEO, COO, CFO, CIO if you have one — to answer one question honestly: where in our operation does AI meaningfully move the number, and how do we get there without wasting a year on the wrong pilot. No slide decks. No frameworks. One operator asking your team hard questions and leaving you with a written plan you can execute.
Right fit
- Healthcare / staffing, $10M–$500M revenue
- CEO or COO in the room the whole day
- Want a written plan, not a framework
- Can act within 90 days
Wrong fit
- Want a slide deck for the board
- Want validation of a decision already made
- No authority to move budget
- In a sector I don't know
- Want an ongoing retainer
A small number of advisory seats, taken carefully.
For founders building at the intersection of AI, regulated industries, and the future of work — where an operator's context is worth more than a check.
Selling to regulated buyers.
Healthcare, staffing, long-term care, compliance-heavy operations.
Building the operator moat.
Where AI actually earns its keep inside a real operation.
Founder discipline.
Team shape, hiring cadence, board dynamics, cost of saying yes to the wrong thing.
Right fit
- Building in healthcare / staffing / workforce
- Have shipped something with real customer signal
- Pre-seed to Series A
- Know exactly what you'd ask
- Willing to send updates on a rhythm
Wrong fit
- Want an advisor for logo value
- Want cash-only
- Pre-idea and want brainstorming
- In a market I don't know
- Not willing to be told no
Come build the thing you'd want to work at.
ShiftNex AI and Actriv Healthcare are both hiring. Small teams, real problems, no theater.
We hire slowly. The résumé matters less than a specific shape of person.
I read every introduction. Not every one gets a role — but every one gets read, and every one gets a reply within a few weeks.