Embracing the 3-Month Rule: A Practical Approach to Building Unscalable Solutions in Tech

In the startup world, the adage from Paul Graham to “do things that don’t scale” is widely recognized, yet the conversation surrounding its practical implementation—especially in coding—often gets overlooked. After spending eight months developing my AI podcast platform, I’ve devised a straightforward framework: every unscalable technique receives a 3-month trial period. At the end of this timeframe, it either validates its worth and transitions to a robust solution or it gets discarded.

As software engineers, we are frequently conditioned to focus on creating scalable solutions from the outset. We dive deep into design patterns, microservices, and complex architectures designed to support millions of users. However, in the context of a startup, this often turns into expensive procrastination—spending valuable time optimizing for hypothetical users and addressing concerns that may never materialize. My 3-month rule compels me to embrace simpler, albeit less refined, coding practices that yield tangible results and provide insights into the needs of users.

Unpacking My Current Infrastructure Choices: Effective Simplicity

1. Unified VM for All Operations

I’ve consolidated my entire infrastructure onto a single virtual machine (VM) that runs a database, web server, background jobs, and Redis—all for just $40 a month. While this setup lacks redundancy and relies on manual backups, it has offered me unparalleled clarity regarding my actual resource requirements. In just 60 days, I’ve discovered that my platform’s peak usage doesn’t exceed 4GB of RAM. The complex Kubernetes architecture I almost pursued would have required extensive management of unutilized containers. When the system has crashed—twice—I’ve gained real insights into what actually fails, which was never what I anticipated.

2. Hardcoded Configurations for Rapid Iteration

Throughout my codebase, configuration values are hardcoded:

plaintext
PRICE_TIER_1 = 9.99
PRICE_TIER_2 = 19.99
MAX_USERS = 100
AI_MODEL = "gpt-4"

There are no external config files or environment variables—just constants. Modifying anything necessitates a redeployment. The hidden advantage? I can quickly search my entire code for configuration values, and every change is tracked in my Git history. In three months, I’ve adjusted these values a mere three times, which equates to 15 minutes of redeployment rather than