Embracing the 3-Month Rule: A Pragmatic Approach to Unscalable Solutions in Software Development
In the startup world, the mantra “Do things that don’t scale,” popularized by Paul Graham, is often cited but rarely examined in practice—particularly when it comes to software development. After an 8-month journey of creating an AI podcast platform, I’ve developed a practical framework that I refer to as the “3-Month Rule.” This approach encourages the use of unscalable hacks for a limited time, after which they either transition into more refined solutions or are discarded entirely.
The reality is that, as software engineers, we are often tempted to create scalable architectures from the outset. Concepts like microservices and distributed systems are the gold standard, idealized for accommodating millions of users. However, in the startup environment, this focus on scalability can lead to costly delays, addressing hypothetical problems rather than engaging with immediate user needs. By committing to the 3-Month Rule, I prioritize quick, effective coding that actually leads to user insights.
Current Infrastructure Hacks: What I’m Learning
Let’s dive into some of the unscalable practices I’ve implemented and the valuable lessons they provide.
1. One VM to Rule Them All
I’ve consolidated my entire infrastructure onto a single virtual machine, which includes the database, web server, background processing, and caching services— all for about $40 a month. While lacking redundancy, this setup has granted me insights that no theoretical capacity planning could provide.
I’ve discovered, for example, that my platform’s peak resource demand is a mere 4GB of RAM. The complex Kubernetes architecture I initially considered would have only resulted in unnecessary complications. When the VM crashes—twice so far—I’ve gleaned essential data on actual failures versus assumed vulnerabilities.
2. Hardcoded Configurations
In my codebase, configuration values are explicitly defined as constants:
python
PRICE_TIER_1 = 9.99
PRICE_TIER_2 = 19.99
MAX_USERS = 100
AI_MODEL = "gpt-4"
While this may seem like a step backward, it offers a significant advantage. I can quickly search the entire codebase for any configuration, and each change is tracked in my version history. Given that these configurations have only changed three times in three months, the time saved is monumental.
3. SQLite for Production Use
Despite being a multi-user application
