This piece departs from previous Rails-centered articles by taking a Rails-adjacent approach.

Rather than explaining what Rails is or how convention over configuration works, this piece focuses on what it means for a Rails project to scale technically and socially.

This perspective grows out of an iterative approach to Rails development. The framework's strong encouragement of experimentation makes it easy to spin up a new project around an app idea just to see what emerges, or to prototype a feature as a standalone project before ever creating a branch on the main codebase, which raises further questions:

How might these projects grow if taken further? 

How would another team approach scaling them? 

These questions have persisted over the years, and what follows is an exploration of what it means for software to scale, both technically and socially.

Technically speaking.

Tech debt accumulates as a byproduct of scaling.

"The best code is no code." You’ve likely heard this gem before, and it's always worth aspiring to. Any code is code that must be maintained. 

Deleting code without losing functionality is more satisfying than flicking a block off a Jenga tower. It's efficient, freeing, and cuts what wasn't truly load-bearing. But this is a deliberate practice that runs counter to what naturally happens as projects scale: tech debt accumulates.

Software projects inherit the problems of all projects: shifting priorities and competing urgencies. 

The calendar booking feature that was the star of last quarter can, like neglected physical infrastructure, fall into disrepair. Tests linger for features that were never fully built out. A hacky fix pushed through to meet a deadline becomes too risky to touch or simply never rises to the top of the priority list again.

To scale a project is to start leaving these archaeological code remnants behind, and the longer that context stays buried, the harder it becomes to reconstruct why something exists at all. In that sense, scaling and accumulating tech debt go hand in hand. It's simply the cost of doing business.

Scaling is a commitment locked in by architectural decisions.

Scaling a project is a lot like marriage. Committing to scale means committing to the current working system, with its underlying mechanisms and limitations. You're marrying your choices, whether you know them or not, and once committed, jumping ship carries a steep cost. 

That's exactly why project leads should be asking hard questions about the implications of scaling early, particularly regarding service cost management.

One useful strategy for surfacing those costs, both in raw compute and architectural limitations, is to build things more than once. Kent Beck's programming notion of coding things three times captures this well. 

The first pass gets a concept working, the second cleans it up and extracts useful abstractions, and the third optimizes for performance and other key metrics.

For scaling a whole project, this looks like getting a proof of concept first. When deciding to scale, we may, secondly, build it out as a monolith and not worry too much about optimization quite yet. The goal is still to have a proof of concept, but now at a larger scale. 

The third time around, when changes due to tech debt become more painful, the core services can be extracted or partitioned off, and teams can be built around these core parts of the projects. This enables a new level of optimization of the key parts we identified in the second build.

Scaling socially.

Scaling is a team sport where resources matter more than ideas.

Deciding to scale a project automatically means involving more people. Ideally, these people are prepared to back the project with resources such as money, time, skills, and political capital, and a project's ability to scale is directly shaped by how these resources are allocated. 

The more clarity there is around partners and their resource contributions, the better the decisions that can be made regarding the most crucial requirements of scaling. Who is being brought onto the team is of great importance, and so is what they bring to the table, as the team's skill set will directly shape the characteristics of the scaling project. No matter how brilliant an idea is, talent and resources will have the largest say in whether it is executed successfully.

Say you craft a feature and a co-worker shows interest. The chances of it succeeding are greater if you also get buy-in from the lead developer, or if your co-worker is also interested in working on the feature themselves. A great feature can exist, yet never flourish, because the resources needed to bring it to a point of success were never available. 

This may sound simple, and that's because it is. Being a very technical profession, developers can get lost in the brilliance of an idea, and founders, being so immersed in their vision, can also lose sight. Both of these roles are heavily mental and abstract, yet there is a very concrete, pragmatic set of resources needed to keep a project alive and give it a chance to flourish.

The two-pizza rule for engineering teams.

A pizza lunch or a pizza party? It is important to keep in mind the boundaries of team sizes and whether crossing them is worth it to the particular scaling project.

More people mean more communication, which brings to mind Amazon's two-pizza team heuristic: a productive team is one small enough to be fed by two pizzas, roughly four to eight people. 

Fewer than four, and you deal with more issues of accountability, bottlenecks, and power imbalance. 

More than eight, and communication becomes more difficult, as it is harder to align everyone's schedules and focus. 

The limiting factor is often organizational rather than technical, and it's worth weighing whether crossing a team-size threshold is worth it for a given project. 

If a four-person team needs to double to build out a core service, that shift into eight-person territory typically means less autonomy, the need for a dedicated lead or communication liaison, and details that are more easily lost. 

If a four-person team needs to double to build out a core service, that shift into eight-person territory typically means less autonomy and the need for a dedicated lead or communication liaison. This also generally means details are more easily lost. 

If a high enough proportion of the team is off-site, rules need to be put in place for communication, as a direct message now connects only a quarter of the team instead of half.

If these changes fundamentally change what made the original team effective, scaling may not be worth pursuing for social reasons, regardless of the technical case. 

Some recommended reading on decision-making based on product objectives is Team Topologies by Matthew Skelton and Manuel Pais.

Growing teams change code culture.

Lastly, more people mean less ownership, a double-edged sword. 

The more people involved, the less likely any single individual is to be the leading contributor. While this protects the product from being overly dependent on the skills of a handful of individuals, it also means declining ownership and, eventually, declining enthusiasm. 

The product may become less interesting to the developers, who could move on to projects where they can have a greater impact. And the bigger a project scales, the more developers it needs to maintain it, meaning higher turnover. This makes documentation and code hygiene even more critical, since people take less care of places they're passing through than of a home they own. 

At the same time, this shift brings the benefits of a public space, one where multiple contributors can build something no single person could have created alone. 

Commitment to growth comes with inherent technical and social implications that are constantly shaping each other. Choosing to scale means living with the architecture already in place, the tech debt still to come, and the team dynamics that will shift as more people and resources enter the picture. 

It makes the origins of major Rails-based companies like Airbnb and Instacart worth reflecting on. 

Both started as small, scrappy projects and eventually faced the same questions raised here: how large teams could grow before communication broke down, and which technical debt was worth living with a little longer. Their paths to scale weren't dictated by Rails itself, but by how they navigated these tradeoffs within the environments they grew into.

There's no universal formula for getting these decisions right, but approaching scale with intention gives a project the best chance of growing into something that still works, both technically and for the people building it.