Building a SaaS product is rarely just a technical challenge. In reality, it is a long-term exercise in balancing speed, reliability, maintainability and business constraints.
Over the past years, I've worked as a freelance full-stack developer on a wide range of production systems: internal logistics platforms, large Shopify automation projects, AI-powered services, data pipelines, and complex Node.js backends used daily by real teams. Those experiences shaped the way I design and build SaaS applications today.
This article is not about theory or trendy buzzwords. It's a practical overview of how I approach real SaaS projects.
Scalability is more than traffic
When people talk about scalability, they often think only about handling more users. In practice, the real difficulty appears much earlier.
A SaaS product must be able to evolve without breaking existing features, accept new business requirements without becoming fragile, onboard new developers without months of ramp-up, and stay observable when something goes wrong in production. At the same time, infrastructure costs must remain under control and deployments must not become stressful events.
Most technical failures I've seen were not caused by lack of performance, but by systems that became impossible to understand or modify safely.
My goal when starting a project is therefore simple: build something that can grow calmly.
Starting from the product, not from the stack
Before choosing any technology, I spend time understanding the product itself. Who are the users? Is this an MVP that needs to move fast, or a platform that is already business-critical? What level of availability is required? Will the team grow? Is the project meant to be maintained for years?
These questions influence architecture far more than any framework choice. They help avoid both extremes: over-engineering a simple product or, on the opposite side, building something fragile for a system that will quickly become central to a company.
Once the constraints are clear, the technical design becomes much more straightforward.
A stack built for real production
Most of my SaaS projects today rely on a stack that is deliberately boring in the best sense of the word: TypeScript on both backend and frontend, Node.js APIs, PostgreSQL, Redis when needed, and React on the client side.
This setup is not chosen because it is fashionable, but because it is predictable, well-understood, easy to recruit for, and extremely reliable in production. It allows me to move fast while keeping strong type safety, clean data models, and consistent contracts between frontend and backend.
For infrastructure, everything runs in Docker, with automated deployments and clearly separated environments. Whether the project is hosted in the cloud or on self-managed servers, the objective remains the same: reproducibility and minimal surprises.
Designing backends that survive change
In SaaS projects, change is constant. New features, new pricing models, new user roles, new integrations, new compliance constraints.
To handle this, I structure backends around business domains rather than technical layers. Instead of a giant folder full of generic services, each part of the product has its own clear space: users, billing, products, analytics, logistics, and so on. This makes the codebase easier to understand and allows future refactoring or service extraction without chaos.
Database design also plays a central role in scalability. I spend a significant amount of time thinking about data structures, relations, indexes and growth patterns before writing too much code. A poorly designed schema will create performance problems and logical inconsistencies long before CPU usage becomes an issue.
Whenever possible, APIs remain stateless, authentication is handled with tokens, and shared state is externalized in Redis. This keeps horizontal scaling simple and avoids tight coupling between servers.
Long-running or heavy operations are always processed asynchronously: imports, exports, AI processing, report generation, large synchronizations. Users should never wait for those tasks, and the system should never block because of them.
Frontend: clarity over complexity
On the frontend side, my focus is less on visual effects and more on predictability and long-term maintainability.
Large SaaS dashboards and admin tools quickly become difficult to manage if structure is not enforced early. I try to keep components simple, business logic explicit, and API interactions clearly separated. A consistent design system helps avoid UI fragmentation, and careful loading strategies keep interfaces responsive even as they grow.
Many of the projects I work on are internal tools used daily by teams. Performance, clarity and reliability matter far more than flashy animations.
What real projects taught me
My approach is largely shaped by the type of systems I've built.
In e-commerce and logistics platforms, I worked on tools handling thousands of products, complex SKU and EAN mappings, automated pricing analysis, multi-store synchronization, translation pipelines and warehouse optimization. These systems run continuously in the background and touch critical business data.
They taught me that correctness, automation and data consistency are far more valuable than rapid but fragile feature delivery.
In AI-driven projects, I designed infrastructures involving GPU clusters, LLM hosting, Dockerized model servers and large-scale data processing. There, scalability is not optional: separating compute, APIs, storage and user interfaces is mandatory if the system is to remain stable.
Earlier in my career, I also worked on security-sensitive applications involving cryptography, smart cards and secure communications. That experience permanently influenced how I design authentication systems, validate inputs, manage secrets and think about permissions.
All of this gradually formed a single philosophy: production systems should be boring to operate.
Keeping technical debt under control
Speed is important in startups, but uncontrolled speed creates systems that collapse under their own weight.
I rely heavily on TypeScript, automated tooling, strict API contracts, versioned migrations and structured logging from day one. I avoid "temporary" shortcuts in core logic, because temporary code often becomes permanent.
Technical debt is sometimes unavoidable, but it should be a conscious decision, not an accident.
Deployment should never be scary
A SaaS that is painful to deploy will eventually fail.
That's why I always implement automated build pipelines, staging environments, predictable migrations and rollback strategies. Environments are clearly separated, configuration is externalized, and deployments are reproducible.
Equally important, everything is documented. Clients should never be locked into a system that only one person understands.
The freelance advantage
Working as a freelance full-stack developer allows me to take full ownership of the technical side of a product.
There are no communication layers, no project managers translating requirements, no dilution of responsibility. I often act as a mix of senior engineer, architect and technical advisor, helping founders make decisions that will affect their product for years.
This direct collaboration tends to produce cleaner systems and faster progress, especially for startups and small teams.
When this approach makes sense
This way of working is particularly well suited for SaaS startups, internal company platforms, AI-based products, marketplaces and automation tools, especially when reliability matters and the product is expected to evolve quickly.
If you are building such a system, or if your current platform is becoming difficult to maintain or scale, this is exactly the type of challenge I enjoy working on.
I currently work remotely with clients in France and abroad, helping them design and build SaaS products that are meant to last.