Hello, I'm Burak. BOO-rahk (/ˈbuː.rɑːk/)
Engineering Leader · Principal Engineer · Former CTO / Head of Engineering
I’m an engineering leader and software engineer based in Berlin, with 15+ years of experience building distributed systems, platform infrastructure, and data-intensive software across fintech, payments, e-commerce, logistics, and supply chain. Over the years, I’ve worked across both hands-on and leadership roles, including Principal Engineer, CTO, and Head of Engineering. I’m currently at Wayfair, where I work on large-scale platform and data systems.
Outside of work, I enjoy traveling with my family, exploring different cultures and cuisines, following basketball, and occasionally writing about technology, leadership, and the evolving craft of software engineering.
- Distributed systems
- Platform engineering
- Data platforms
- Engineering leadership
- Technical strategy
- Reliability
- Fintech & payments
- E-commerce & logistics
- Supply chain
- AI-assisted engineering
- Code Is Cheap. Guarantees Aren’t
If models write more of the code and humans increasingly review, constrain, and verify it, then popularity in the human-coded era is not the same thing as fitness for the next one. The harder problem is no longer just producing code. It is building stacks that can survive cheap generation without collapsing under ambiguity, review burden, and correctness debt.
- The Pull Request is Dead: Surviving the AI Code Avalanche
Code production is no longer our bottleneck. The newfound velocity of AI coding agents hasn't solved our problems; it has simply moved the bottleneck further down the pipeline, creating massive SDLC backpressure. The human "Looks Good To Me" on a PR is now the single biggest liability in deployment. It’s time to stop acting like typists and start acting like architects.
- AI Made Coding Cheap. Coordination Is Still Expensive
AI dramatically accelerated individual coding and local execution. End-to-end delivery barely moved. We optimized leaf-node execution but left the tree structure completely manual. Business intent (“add fraud detection”) decomposes into tasks across teams, each carrying implicit assumptions that only conflict during integration. Performance budgets, data freshness requirements, and retry semantics remain undiscovered until week 8 of 10. AI can breeze through well-defined tasks with deterministic verification. But getting from business requirement to that well-defined task? That’s where projects die.