Faruk Serhat TUNÇ
“The real joy of writing code comes when the code starts talking back to you.”
Engineering Principles
Design principles and thinking patterns that drive technical decisions.
Project Case Studies
Solutions to real problems — architecture choices and learnings.
Development Areas
Long-term investment areas for SaaS and product-scale engineering.
Engineering Principles
Six core principles guiding technical decisions.
Problem-First Mindset
Technology choices should be answers, not decoration.
$I start by clearly defining the problem and its constraints. Scale, expected growth, team size and operational constraints shape the solution more than trends or popular tools. I prefer the simplest solution that reliably solves the problem before adding complexity. Technologies change, but clear thinking and conscious decisions endure.
Simplicity Before Complexity
Readable systems scale faster than clever ones. Perfect is the enemy of good.
$I prefer simple, understandable designs over over-engineered solutions. Monoliths are acceptable when they make sense, and microservices only when there is a clear need. Complexity should be earned, not assumed.
Security by Design
Security is not a feature to add later, it is a foundation to build upon.
$I treat security as a core architectural concern, not an afterthought. The principle of least privilege guides access control decisions. I validate inputs at boundaries, encrypt sensitive data in transit and at rest, and design systems assuming components will be compromised. Authentication, authorization, and audit logging are built into the foundation, not bolted on later.
Trade-off Analysis
There are no solutions, only trade-offs. Every gain has a cost.
$Every architectural decision comes with a trade-off. Whether it is performance, sustainability or operational cost, I try to make clear what we gain and lose with each choice. I document these decisions so the system stays understandable for future contributors.
Performance as User Experience
Every millisecond is a design decision. Measure first, optimize what matters.
$Performance is not just about speed, it is about user experience and resource efficiency. I measure before optimizing and focus on what actually impacts users. Code splitting, lazy loading, and caching strategies are applied where they provide measurable value. I avoid premature optimization but design with performance in mind from the start, understanding that architectural choices are harder to change later.
Production Mindset
Systems must be observable, operable, and maintainable in real-world environments.
$I think beyond local development about how the system will behave in production. Logging, error handling, observability and deployment are part of the process, not afterthoughts. A system is not complete until it can be observed and maintained.
Project Case Studies
Problems, decisions, trade-offs, and learnings.
Development Areas
Long-term areas I invest in to operate at SaaS and product scale.
Platform & Scale
- Multi-tenant, scalable data models and API design that hold up as the product grows
- Event-driven architectures, domain boundaries, and maintainable long-term contracts
- Documented data and integration layer that remains portable as the product evolves
Reliability & Operations
- SLO/SLI definition, measurement, and incident response — building a reliability culture in production
- Cost-aware infrastructure, automation, and release safety (reducing risk to production)
- Real-time operational visibility in distributed systems (trace, metric, log)
Architecture & Product Thinking
- Architecture at SaaS scale: trade-off documentation and technical debt management
- Long-term roadmap, clear module boundaries, and crisp cross-team communication
- Technical strategy aligned with product and business goals — owning decisions and outcomes
Let's get in touch
Whether you have a product idea, need a technical partner, or want to discuss system design — I'm here to help. Reach out via the menu (email or social links) and let's turn your vision into reality.
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