For one leadership team or a cross-portfolio cohort.
The executive build loop
01
Find the value
Start with a real operating constraint.
02
Build the workflow
Turn executive expertise into a working example.
03
Test the boundaries
Evaluate accuracy, permissions and exceptions.
04
Lead the adoption
Give the work an owner and a measure.
Practical governance is part of the work, not a gate added at the end.
Built around the value creation agenda
01Margin
Redesign high-friction work
02Growth
Create customer value
03Adoption
Move with clear controls
The program
Develop the leaders. Change the work.
The executive's job is to choose valuable problems, ask better questions of builders, judge the output and lead adoption. This program develops that judgment through hands-on work.
01
Executive working session
Choose the right work.
Connect AI capabilities to your value creation plan. Map a workflow, establish its baseline and decide whether to build, buy, automate simply, or leave it alone.
Take away
A prioritized use-case brief and a clear success measure.
02
Guided build lab
Get your hands on it.
Work alongside me to assemble a representative workflow. Learn where agents, tools, data and human judgment fit, and test what happens when inputs are incomplete or wrong.
Take away
A working learning prototype and an evaluation checklist.
03
Leadership application
Make adoption someone's job.
Translate the exercise into a practical pilot proposal: ownership, budget, access boundaries, approvals, training and a review cadence tied to operating performance.
Take away
A pilot charter and an adoption plan your team can own.
Built for your context. One company's leadership team, a functional executive group or a cohort across the portfolio. The workflows, depth and format are scoped around their starting point.
Business expertise is the prerequisite. Coding experience is not.
Applied learning
Start where the business feels friction.
Select exercises tied to your portfolio's operating priorities. Each one connects a business problem, a working example and a way to judge whether it helps.
01Portfolio visibility
From scattered updates to a decision-ready report.
Practice turning inconsistent company inputs into a source-linked operating brief, with missing data clearly flagged.
What to measureReporting time · completeness · corrections
02Revenue operations
Find the gap between the contract and the invoice.
Compare sample terms, usage and invoices. Surface exceptions for a finance owner to verify before taking action.
What to measureExceptions found · review time · false positives
03Working capital
Make collections a prioritized workflow.
Use sample aging and account context to prepare a collections queue and draft follow-ups, with human approval before sending.
What to measureQueue preparation time · escalation quality
04Procurement & spend
See the spend patterns hiding across companies.
Normalize synthetic vendor records, identify possible overlap and assemble the evidence for a sourcing decision.
What to measureMatch accuracy · review effort · data coverage
05Expertise into customer value
Turn expert knowledge into a learning experience.
Build a source-grounded onboarding or training prototype from approved material, with expert review and checks for understanding.
What to measureTime to first value · accuracy · learner completion
06Service delivery
Give customer teams a better first draft.
Prototype request triage and a grounded response workflow. Define what it may answer, what it must escalate and who owns the result.
What to measureHandling time · resolution quality · escalations
Illustrative workshop exercises, not claims of completed PE engagements. Labs use synthetic or explicitly approved material; a training prototype is not a production deployment.
Learn what to do when the AI is wrong.
Every lab makes room for exceptions, evidence and human approval. Leaders learn to ask what the system can access, how its output is evaluated and when it must stop and ask for help.
Governance by doing.
Your instructor & building partner
An operator's lens. A builder's hands. A lawyer's judgment.
I work at the intersection of business transformation, hands-on AI building and practical governance.
I've spent six years doing business transformation in legal, led teams as a law-firm partner and consultant, and operated businesses as an entrepreneur. I understand the P&L, and the work it takes to change the processes behind it.
I also build applied AI and multi-agent systems myself. That means we can move from an executive's idea to the workflow, infrastructure, business logic and controls that would make it useful.
My legal background is an advantage when procurement, privacy, risk or governance slows adoption. The goal is to help your team move with sound judgment.
Former law-firm partnerFormer director, Elevate ServicesFounder, Lumen Atlas & PossibLaw
PE firms are investing in hands-on AI execution. My training offer focuses on a complementary need: executives who can identify, evaluate and sponsor that work.
Bring an operating priority, the leaders you want to develop and where they're starting. We'll scope the right working session and build lab. Prefer LinkedIn? Message me there.