The Cost of Evolution

originally published April 13th, 2025

The Cost of Evolution in Software Tooling

One of my primary concerns with tooling is understanding the cost of evolving through multiple stages of an app’s lifecycle. We start with rapid application development to test business and market fit, then scale up in complexity and traffic. Less-experienced developers don’t always realize how the app must shift between these stages; they just can’t predict what will be needed. That’s why we intentionally tell them, “Do not consider the future," because they tend to predict poorly, waste time, and miss the mark.

More experienced engineers can project their plans into the future. They know how to implement solutions now without inhibiting the current business or product development cycle. However, depending on the solution space, requirements in later stages can be significantly different from early ones. Some tools support these transitions better than others, but I rarely hear engineers discussing this. It’s the very thing I’m most interested in—finding approaches that make these shifts cheap and easy, rather than forcing you to consider too many things in advance.

Transitioning Through Product Stages

The gold standard would be tooling that supports rapid app development in the early phases so you can keep iterating and find market fit. Then, as you move forward, you’d seamlessly transition to solutions that handle increased complexity and load—all without having to plan far in advance. You’d consider as little as possible in each phase, then comfortably move on without facing expensive rewrites.

A classic example of an “expensive complexity transition" is starting with lots of CRUD code and then needing to transform it into highly modeled business processes once scaling demands it. CRUD often doesn’t handle complex growth without becoming a giant mess. Similarly, you eventually need to shift from synchronous to asynchronous processes, which introduces message brokers, queues, and workers that independently scale with infrastructure. You really don’t want junior developers worrying about that on day one, especially when their lack of experience means they can’t plan effectively.

But if your software factory is built around ignoring the future entirely, you pay a massive bill when it arrives—sometimes crippling your business. The reality is that technology choices can dramatically influence the cost and complexity of these transitions. A good CTO, for example, should look at the bigger picture, anticipating these shifts. Most programmers don’t come with enough vision to consider how a solution will evolve over the product’s life.

Real-World Observations

In my own experience, the vast majority of programmers can talk about the solution they’re implementing right now but can’t project into the future and explain the ramifications. Because of that, I don’t feel comfortable letting them pick their plans without oversight. I have to limit their options to ones that won’t cause massive problems down the line. Yet I also need to give them enough freedom to learn from their choices—otherwise, they’ll never grow. Unfortunately, that means I have to invest a lot of energy foreseeing potential issues and steering them away from truly catastrophic failures.

This dynamic forces me to develop models and preferences for solution profiles that reduce negative impact. It’s hard, because you can’t just hand someone years of experience. You can warn them about pitfalls, but they won’t really grasp them until they stumble into those issues themselves.

Conclusion

Ultimately, the question is: How do we pick tools and processes that let us evolve cheaply and effectively at every phase of development? You want to minimize the need for predicting the future while avoiding massive transitions that could sink your project. It’s a balancing act between empowering less-experienced developers to build rapidly, guiding them so they don’t create future landmines, and ensuring the overall architecture won’t crumble when the product inevitably scales. The more foresight and experience you inject into the process, the smoother these transitions become—and the healthier your business will be in the long run.