20 years of engineering decisions. Now I help leadership teams make the right ones about AI.
From building and scaling engineering teams to leading AI adoption for 100+ engineers at enterprise scale. Two decades of hands-on experience — strategy and execution, not one or the other.
How does 20 years of engineering experience shape AI strategy?
2004: started writing code. A decade of shipping products, designing systems, learning what works by watching what breaks. PHP, Java, TypeScript, Python — the language never mattered as much as the architecture decisions behind it.
Then leadership. Building teams, scaling organizations, owning a company. Learning that the hardest bugs are human ones. Managing engineers taught me more about systems thinking than any technical book.
Lean Six Sigma Green Belt certified. Because "I think it is faster" is not a measurement. If you cannot quantify the improvement, it did not happen. I brought this discipline to every team I have led since.
Now: leading AI adoption for 100+ engineers at a major Polish insurer. Every day, at scale. Not as a consultant who flies in — as someone who lives with the consequences of every decision. I see what works, what breaks, and what gets quietly abandoned.
That range — from individual contributor to executive leadership — is what makes the difference. Strategy without implementation experience is guesswork. Implementation without strategic context is wasted effort.
Where I have done this before
Insurance
Currently leading AI adoption at a major Polish insurer. Regulated environment, complex legacy systems, distributed teams, 100+ engineers. This is where I operate daily — not as a visiting advisor, but as someone accountable for outcomes.
Financial Services
Governance frameworks and AI strategy for organizations where compliance is not optional and regulators are paying attention. Built rollout plans that passed board review and satisfied audit requirements.
Technology
Engineering leadership across product companies and consultancies. From early-stage startups to established enterprise firms — scaling teams, defining architecture, and shipping products that users depend on.
E-Commerce
Process automation and AI-driven optimization for online retail operations. Measurable ROI from day one, not speculative pilots that never reach production.
I still ship my own code
Talk is cheap. I build my own products to stay sharp and test ideas in production — not sandboxes.
What principles guide effective AI implementation?
Most AI strategies fail at the implementation layer — built by people who have never shipped AI into production.
Depth of experience outperforms breadth of coverage.
How I help organizations with AI
AI strategy, governance, and rollout planning for leadership teams
Explore AI strategy advisoryHands-on AI workshops and tools training for engineering teams
Explore AI workshops for teams