01
Operating model
How work is planned, staffed and delivered: clear ownership, real capacity data, and a rhythm the organisation can keep.
Operations & AI advisory · Bucharest
Operating models, delivery and AI adoption for leadership teams who need all three to work. Built on years of running large, complex productions in games, now applied to your company.
The problem
Most companies don’t have an AI problem.
They have an operations problem: unclear ownership, invisible capacity, plans nobody trusts.
Fix that, and AI has something to scale.
What transfers
Fixed launch dates, big budgets, large teams spread across companies and countries. Games are a hard place to run production, and the lessons travel well beyond the industry.
In games
Scaled a studio from 3–4 to 12 simultaneous projects.
In your company
Run work as a portfolio: one view of capacity, clear priorities, and the discipline to cut what isn’t working, AI projects included.
In games
Contributed to one part of the outsourcing pipeline on a AAA production: ~1,000 people, an estimated $200M budget, work moving between companies.
In your company
Vendors, partners or AI agents: work that crosses boundaries needs clear briefs, quality gates and clean hand-offs.
In games
Mapped capabilities across 20 business units and 3,000 people.
In your company
See who does what before you redesign anything. You can’t improve, staff or automate work you can’t see.
In games
A decade at a leading mobile game developer, ending as Senior Producer on a ~$20M flagship title.
In your company
Hold transformation programmes to launch-date discipline: a fixed budget, visible milestones, and no endless pilots.
In games
Driving a PSA roll-out across a global services group.
In your company
Systems change is operations change. A roll-out lands when process, data and people move together.
The work
Consultants fix process. Vendors sell AI. I work on both, because AI only pays off inside an operation that already works.
01
How work is planned, staffed and delivered: clear ownership, real capacity data, and a rhythm the organisation can keep.
02
Where the margin is and where it leaks. Business cases for operational change and AI that leadership can defend in front of a board.
03
Guardrails, governance and change management, so AI lands inside the operation instead of next to it.
Selected work
Six productions. Made in games, built to transfer.
20
business units brought into one capability map
3,000
people covered by that map
12
simultaneous projects, scaled up from 3–4
€5M+
revenue, growth I supported at a scaling services business
Track record
Cut 01
Senior Producer
A decade of shipping games, ending on a ~$20M flagship title.
Cut 02
Outsourcing pipeline · Canada
Contributed to one part of the pipeline on a AAA production of ~1,000 people and an estimated $200M budget.
Cut 03
Production Director
Scaled from 3–4 to 12 simultaneous projects and built an internal HR AI chatbot.
Cut 04
Programme lead
Capability mapping across 20 business units, a PSA roll-out, and a multi-agent AI platform taken from internal tool to client delivery.
Cut 05
Founder
Taking the playbook beyond games: independent advisory on operations and AI.
Master’s in Organisational Management
On stage
Scorewarrior Summit · Limassol · 2026
AI toolsets for production · AI governance & risk · Change management
DevGAMM
AI in production and governance
Next step
The Operations & AI Readiness Scorecard is a short diagnostic of how ready your operation is for AI: ownership, capacity, execution, economics, data and AI governance. You get a score, a profile and the first moves to make. 18 questions · about 4 minutes