The Three-Month Rule: A Practical Guide to Implementing Unscalable Solutions in Software Development

When it comes to startup culture, there’s a well-known piece of advice from Paul Graham that encourages entrepreneurs to “do things that don’t scale.” But how do we translate this wisdom into practical coding strategies? After spending eight months developing my AI podcast platform, I’ve established a straightforward method: every unscalable solution I implement receives a trial period of three months. At the end of this timeframe, we either solidify it into a more robust solution or phase it out.

The traditional mindset in engineering emphasizes building scalable solutions from the ground up. We often get tempted by architectural designs like microservices and distributed systems, which are generally tailored for larger companies. However, in a startup setting, painstakingly creating scalable code can be an inefficient use of resources. My three-month rule compels me to write straightforward, albeit imperfect, code that actually reaches users and allows me to discover what they need.

My Approach to Pragmatic Infrastructure Solutions

1. Unified Virtual Machine

Currently, my entire infrastructure operates on a single virtual machine (VM) costing $40 a month that hosts the database, web server, background tasks, and Redis. While this lack of redundancy may appear reckless, it allows me to gauge my actual resource requirements far better than any theoretical planning could. My AI platform, after two months of operation, peaks at just 4GB of RAM, which means the complex Kubernetes cluster I almost set up would have only managed inactive containers. Each time my system crashes (twice so far), I gain invaluable insights into its vulnerabilities—often revealing surprises.

2. Hardcoded Configuration

My code currently features hardcoded constants like:

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

This means I don’t have config files or environment variables that complicate the deployment process. Sure, altering these values requires a redeployment, but the significant benefit is that I can quickly search through my entire codebase to track changes. In three months, I’ve only altered these parameters three times, which translates to 15 minutes of redeployment versus the 40 hours it would take to establish a full-fledged configuration service.

3. Using SQLite for a Multi-User Application

Yes, you read that correctly: I