Embracing the 3-Month Rule: A Pragmatic Approach to Non-Scalable Solutions in Tech
In the world of technology startups, Paul Graham’s famous mantra to “do things that don’t scale” is often quoted. However, the practical application of this philosophy—particularly in coding—remains largely unexplored. After spending the last eight months cultivating my AI podcast platform, I have developed my own framework: the 3-Month Rule. This approach dictates that every non-scalable solution I implement is given a lifespan of three months. At the end of this period, the solution is either refined into a robust feature based on its proven value or discarded entirely.
The Startup Perspective
As engineers, we are frequently conditioned to pursue scalable solutions right from the outset. We dream in terms of design patterns, distributed systems, and microservices while picturing a platform that can accommodate millions of users. However, in a startup environment, focusing on scalability too early can lead to inefficient use of resources. It often becomes a form of expensive procrastination—optimizing for hypothetical users and resolving issues that may never arise. My 3-Month Rule encourages me to create straightforward, although seemingly inefficient, code that provides immediate insights into user needs.
Current Infrastructure Hacks: Valuable Lessons Learned
1. Consolidated Virtual Environment
My entire setup—database, web server, background jobs, and caching—is housed on a single virtual machine costing $40 per month. This means zero redundancy and manual backups to my local machine. The key lesson here: I’ve gained invaluable insights into my actual resource demands within just two months. For example, I learned that my platform’s peak usage requires only 4GB of RAM, making the complex Kubernetes configuration I initially considered unnecessary.
2. Hardcoded Configurations
Instead of relying on configuration files and environment variables, I use constants like:
python
PRICE_TIER_1 = 9.99
MAX_USERS = 100
This approach means that changes necessitate redeploying the code but offers the hidden advantage of quick access and straightforward tracking of configuration changes through version control. The time saved here is substantial—15 minutes spent redeploying has been far more efficient than the potential 40 hours it would have taken to engineer a configuration management system.
3. SQLite for Production Use
I’m utilizing SQLite for a multi-user application with a total database size of just 47MB, easily handling 50 concurrent users
One Comment
Thank you for sharing this insightful approach. The 3-Month Rule elegantly balances the necessity of quick experimentation with disciplined evaluation, which is so crucial in early-stage startups. I particularly appreciate how you emphasize gaining real-world insights through simple, non-scalable solutions before committing extensive resources to premature optimization.
The lessons from your infrastructure hacks are also compelling; they highlight the importance of validating resource needs and user behavior with minimal complexity before scaling. Using tools like SQLite and hardcoded configs in the initial stages allows for rapid iteration and better understanding of what truly matters.
This framework can serve as a valuable guide for many founders and engineers—reminding us that the path to scalable, robust solutions often begins with quick, imperfect fixes that are simply good enough to learn from. Have you considered integrating a formal review process at the three-month mark to systematically decide whether to evolve, pivot, or sunset these solutions? That might further streamline decision-making and resource allocation.