Embracing the 3-Month Rule: A Practical Approach to Non-Scalable Solutions
In the realm of startups, where speed and learning often trump perfection, the well-known advice from Paul Graham — “Do things that don’t scale” — takes on significant relevance. However, the question remains: how do we apply this concept in a technical context, particularly in coding? After dedicating eight months to developing my AI podcast platform, I’ve crafted a straightforward framework to navigate this process, which I call the Three-Month Rule.
The Three-Month Rule Explained
The premise of my approach is simple: any unscalable hack I implement is allotted a three-month lifespan. During this time, it must either demonstrate its worth and warrant a proper build, or it will be phased out. As engineers, we are instinctively trained to pursue scalable solutions from the outset. We get caught up in design patterns, microservices, and complex architectures designed to manage millions of users. However, this mindset often leads to wasted time and resources, particularly in the startup environment where the user base is yet to be established.
In my experience, focusing on scalable code can become a form of costly procrastination. The Three-Month Rule drives me to create straightforward, sometimes deemed “inefficient” code that can be quickly deployed. This approach allows me to better understand what my users truly need.
Current Infrastructure Strategies That Prove Effective
Here are some of the key strategies I’ve adopted that exemplify this philosophy, and how they foster innovation rather than hinder it:
1. One Virtual Machine for Everything
All aspects of my platform — from the database to the web server and background jobs — operate on a single $40/month virtual machine. While some may argue this lacks redundancy and safeguards, I see it as a calculated risk. This configuration has provided me with invaluable insights into my actual resource requirements far more effectively than any intricate planning document could. I quickly learned that my system peaks at just 4GB of RAM, and the elaborate Kubernetes setup I considered would have simply managed empty containers.
When outages have occurred, I’ve gained direct knowledge about the failure points, which often surprised me.
2. Hardcoded Configurations
In my code, configurations like pricing tiers and user limits are hardcoded, eliminating the complexities of configuration files or environment variables. While this might seem counterproductive, the benefit is remarkable: I can swiftly search my codebase for any value, and each
One Comment
This is a compelling approach that highlights the importance of pragmatic experimentation in early-stage development. The Three-Month Rule effectively encourages startups and engineers to prioritize rapid learning and iteration over premature optimization or over-engineering.
I particularly appreciate the emphasis on getting real-world insights through simple, unrefined solutions—such as using a single VM or hardcoded configurations—to inform subsequent scaling efforts. It aligns with the lean startup philosophy of building knowledge firsthand before committing substantial resources.
One thought to consider is that while this approach works well in the initial phases, establishing a clear transition plan for moving beyond these shortcuts will be critical as user growth accelerates. Planning for eventual scaling and transition can help avoid technical debt accumulation later.
Overall, this pragmatic stance fosters a mindset of disciplined experimentation, which is essential for sustainable growth. Thanks for sharing your framework—definitely a valuable perspective for founders and engineers navigating the early days!