The Case Against Over-Engineering Your Side Project From the Start

Software side projects have a well-documented failure mode: they start with an ambitious architecture decision. The developer spends the first weekend setting up Docker Compose with separate services for the API, database, and frontend, configures CI/CD pipelines, establishes test infrastructure, and plans the microservices boundaries. By the second weekend, they’re refining the infrastructure rather than building the feature. By the third weekend, the project is abandoned, its elaborate skeleton never populated with the actual functionality it was designed to support. The engineering was thorough; the product was never built.

The case against over-engineering from the start is not an argument for writing terrible code or ignoring good engineering practices permanently. It’s an argument calibrated to the specific reality of side projects: they have limited time, uncertain futures, and a specific failure mode (not shipping anything) that sophisticated architecture contributes to rather than prevents.

What Over-Engineering Actually Is

Over-engineering is solving problems you don’t have yet at the cost of solving the problems you have now. A side project that will have one user (the developer) doesn’t need horizontal scalability. A project that might never leave development doesn’t need production-grade deployment infrastructure. A project with one contributor doesn’t need a microservices architecture designed to allow independent team deployment. These architectural decisions make sense at specific scales and team sizes; applying them to a project that hasn’t demonstrated any users is investing in infrastructure for a future that may never arrive.

The temptation to over-engineer comes from several sources. Developers working in production systems at their day jobs are accustomed to the infrastructure of mature systems and may apply those patterns reflexively to new projects. Learning new technologies — Kubernetes, GraphQL, event-driven architecture — is often more interesting than building features, and a side project provides a testing ground for technology exploration that bleeds into the project’s structure. Perfectionism and the desire to build things “right” leads to spending time on architectural concerns before the fundamental usefulness of the project is established.

The Constraint That Changes Everything

Side projects run on limited time — typically evenings and weekends carved out around full-time employment, personal obligations, and life in general. This time constraint is qualitatively different from professional work where the project is the primary focus. A complex architecture that would be entirely manageable with 40 focused hours per week becomes unwieldy when you have 3–5 hours per week, each session requiring context reconstruction before any forward progress is made.

The time-per-session constraint is why simplicity has compounding value in side projects that it doesn’t have in full-time work. A simpler architecture requires less context per session, makes forward progress possible in shorter blocks, and reduces the cognitive load of returning to the project after a week away. A project structured so that each evening’s work can produce visible, testable output is more likely to sustain momentum than one where three evenings of infrastructure work must precede any visible result.

The appropriate architecture for a side project is the simplest one that solves the problem well enough to validate whether the project is worth continuing. For most web applications at side project scale (dozens to hundreds of users), this is typically: a monolith with a server-rendered or SPA frontend, a single database, deployed as simply as possible (Railway, Fly.io, Render, or a single VPS), and version-controlled in a simple repo. This is not exciting architecture. It builds features quickly, is easy to understand after a week away, and handles the load of a growing side project effectively until the scale genuinely demands more complexity.

When to Add Complexity

The right time to introduce architectural complexity is when the project has demonstrated that it deserves it: it has users, it has specific bottlenecks that simple architecture can’t address, or it has a team size that creates coordination problems the architecture needs to solve. At that point, the refactoring cost of introducing necessary complexity is justified by the known problem it solves, and the project’s existence is no longer in question.

The argument against premature architectural investment is not that good architecture doesn’t matter — it’s that the appropriate level of architecture is context-dependent, and for early-stage side projects, the context is: uncertain future, limited time, single contributor, probably small scale. Building for the architecture of a successful, scaled product before knowing whether the product will succeed is betting on an outcome that most side projects don’t reach.

The Technology Choice Corollary

The same principle applies to technology choices: use the technology you know best, not the technology you want to learn. A side project is often used as an opportunity to learn a new framework, language, or database — which is a legitimate goal, but one that competes with actually building the product. Learning a new technology while building a product multiplies the sources of confusion and slows progress. The most successful side projects are typically built with boring, familiar technology that doesn’t require learning overhead, because familiar technology means all the cognitive effort goes to the product rather than the tooling.

If learning a specific technology is the explicit goal of the project (building something in Rust to learn Rust, building a mobile app to learn SwiftUI), that’s a different constraint — the learning is the point, not the product. But if the point is to build and potentially launch a product, the technology choice should optimize for speed and familiarity, not for interesting technical challenges. Those challenges come for free as the product matures and presents real engineering problems worth solving well.