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

In the startup world, we often hear the well-known advice from Paul Graham to “do things that don’t scale.” However, practical implementation of this principle, particularly in the realm of coding, is rarely discussed. After spending the past eight months developing my AI podcast platform, I’ve devised a framework that may change your perspective on unscalable solutions: each non-scalable approach gets three months to prove its worth.

The Problem with Overthinking Scalability

As software engineers, we are frequently conditioned to prioritize scalable solutions from the outset. With complex architectures like microservices and distributed systems, we aim for robust designs capable of accommodating millions of users. While this is essential in larger organizations, in a startup context, it can lead to costly delays. Instead of optimistically preparing for users who may never arrive, I’ve adopted a method that encourages simplicity and actionable feedback through fast deployment.

My Infrastructure Hacks: Learning Through Simplicity

Here are some of the current infrastructure strategies I’ve employed, demonstrating that unorthodox solutions can yield valuable learning experiences.

1. Consolidation on a Single VM

My complete infrastructure—database, web server, background jobs, and caching—resides on a single $40/month virtual machine. Yes, there’s no redundancy, and backups are manually executed, but the benefits are clear. In just two months, I gained unparalleled insight into my actual resource use. My platform, despite being labeled “AI-heavy,” rarely exceeds 4GB of RAM. If I had invested time in a complex Kubernetes structure, I would have been preoccupied with managing idle containers.

2. Hardcoded Configurations

Instead of using configuration files or environment variables, I’ve opted for hardcoded constants in my codebase:

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

This might seem primitive, but it allows for rapid, straightforward access to configuration values and ensures that every change is documented in version control. Given that I’ve only adjusted a few of these values three times within three months, this method has proven far more efficient than developing a dedicated configuration service.

3. SQLite for a Multi-User Application

You read that right—my multi-user application runs on SQLite. With