Embracing the 3-Month Rule: A Pragmatic Approach to Unscalable Solutions in Software Development
In the world of startups and software development, the mantra “Do things that don’t scale” has become a popular piece of advice, famously shared by Paul Graham. However, many developers struggle to translate this concept into actionable strategies in their coding practices. Over the past eight months of building my AI podcast platform, I’ve adopted a particular tactic known as the 3-Month Rule. This framework not only encourages experimentation but also helps me determine the value of “unscalable” solutions in a structured way.
Why the 3-Month Rule Works
The beauty of this approach lies in its simplicity: give any unscalable hack or workaround a lifespan of three months. After this period, it must either demonstrate its utility and be transitioned into a more robust solution or be discarded altogether. While traditional engineering emphasizes creating scalable solutions from inception—focusing on sophisticated design patterns, microservices, and elaborate architectures—such practices are often misguided in the startup context, where optimizing for potential users can lead to wasted time and resources.
My 3-Month Rule forces me to prioritize straightforward, even “bad” code that can be quickly deployed. This way, I not only learn what truly resonates with users but can also pivot as necessary based on real-world feedback.
Strategic Hacks in My Current Infrastructure
1. Consolidation on a Single VM
All of my application’s components—including the database, web server, background processing, and Redis—run on a single virtual machine that costs just $40 per month. Although this setup may lack redundancy and relies on manual backups to my local system, it allows me to gain invaluable insights into my actual resource needs. For instance, I discovered that the platform’s memory requirements peak at a mere 4GB RAM—information that informs better future scalability decisions.
2. Hardcoded Configuration for Flexibility
Using hardcoded constants for configuration purposes is a deliberate choice—values like PRICE_TIER_1 = 9.99 and MAX_USERS = 100 are spread across code files. This approach means that modifying configurations compels a redeployment, but it also enables swift searches and meticulous tracking of changes through version control. Building a dedicated configuration service would require significant engineering effort, while my approach has sufficed for minimal modifications, demonstrating efficiency in time and resources.
3. Utilizing SQLite in Production
Yes
