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

In the ever-evolving landscape of software development, Paul Graham’s infamous call to “do things that don’t scale” resonates deeply, yet implementing this philosophy—especially in coding—remains a significant challenge. After spending eight months developing my AI podcast platform, I discovered my own practical framework: I dedicate exactly three months to any unscalable solutions. If they prove their worth within that timeframe, they evolve into more robust systems; if not, they gracefully exit.

The startup Mindset: Moving Beyond Scalability from Day One

As engineers, we are often conditioned to prioritize scalable solutions right from the outset. Concepts like design patterns, microservices, and distributed architectures dominate discussions, especially in larger firms. However, for startups, fixating on scalability can lead to unnecessary expenses. Instead of optimizing for a user base that might not exist, my three-month rule pushes me to create straightforward, sometimes “messy,” code that delivers real insights into user needs.

Key Infrastructure Hacks and Their Strategic Value

1. Consolidation on a Single Virtual Machine

All essential components—database, web server, background jobs, and caching—run on a single $40/month virtual machine. While this may seem reckless, I’ve gained unprecedented clarity about my actual resource needs. Over the past two months, my platform’s usage peaked at 4GB of RAM, rendering elaborate Kubernetes management unnecessary. Each crash (which has happened twice) provides invaluable data about system vulnerabilities, often revealing unexpected issues.

2. Simplified Configuration Management

Instead of complex configuration files or environment variables, I utilize hardcoded constants throughout my codebase. For example:
python
PRICE_TIER_1 = 9.99
PRICE_TIER_2 = 19.99
MAX_USERS = 100
AI_MODEL = "gpt-4"
This approach allows me to easily track changes via git history and expedites the redeployment process. With only three configuration changes in three months, I’ve saved countless engineering hours while maintaining oversight during updates.

3. Utilizing SQLite in Production

Yes, I opted for SQLite for my multi-user application. With a database size of just 47MB, it seamlessly handles up to 50 concurrent users. My usage analysis revealed a 95% read to 5% write ratio—an ideal fit for SQLite. Had I chosen a