Embracing the 3-Month Rule: A Pragmatic Approach to Unscalable Solutions in Software Development
In the fast-paced world of startups, the mantra “Do things that don’t scale,” popularized by Paul Graham, often takes center stage. However, the challenge arises when engineers attempt to apply this principle in a practical, technical context. Over the past eight months while developing my AI podcast platform, I’ve cultivated a straightforward methodology: every unscalable hack has a lifespan of exactly three months. If it doesn’t prove its worth within that time frame, it’s time for it to go.
Why the 3-Month Rule Works
As software engineers, we are often conditioned to pursue scalable solutions right from the outset. We envision complex architectures featuring design patterns, microservices, and distributed systems capable of accommodating millions of users. While these frameworks are essential for larger organizations, startups can fall into the trap of premature optimization—sacrificing speed and efficiency to cater to potential future users that may never materialize. By adhering to my 3-month rule, I focus on crafting straightforward, immediate solutions that can be implemented quickly, allowing me to truly understand my users’ needs by observing their interactions firsthand.
Current Infrastructure Hacks: Lean and Insightful
Let’s delve into some of the calculated yet unrefined infrastructure decisions I’ve made, demonstrating that simplicity can yield profound insights:
1. One Virtual Machine for Everything
Everything from the database and web server to background jobs and caching operates on a singular, budget-friendly $40/month virtual machine. While this approach lacks redundancy and relies on manual backups, it has forced me to explore my actual resource requirements in a way that traditional capacity planning documentation never could. In just two months, I learned that my “AI-heavy” platform rarely exceeds 4GB of RAM. An intricate Kubernetes setup I contemplated would have been a waste, managing empty containers instead of optimizing the real workload.
2. Hardcoded Configurations
Utilizing hardcoded constants for configuration like pricing and user limits may seem primitive, but it allows me to quickly access and modify parameters across my codebase. This method enables rapid redeployment—what would take a week to create in a formal configuration service gets done in just a few minutes of redeployment, drastically reducing engineering time.
3. SQLite as My Database of Choice
Running a multi-user web application on SQLite is unconventional, yet my database is a compact 47MB
One Comment
Thank you for sharing this practical perspective on balancing quick iteration with sustainable growth. The “3-Month Rule” strikes me as a thoughtful approach—providing enough time to validate whether a temporary hack has genuine potential or simply becomes technical debt. I’ve found that this kind of disciplined experimentation allows startups to remain both nimble and focused, avoiding premature investments into overly complex architectures.
Your examples, like using a single VM and hardcoded configs, highlight how simplicity and immediate feedback can lead to valuable insights that might be obscured by more elaborate setups. It’s a great reminder that unscalable solutions, when applied intentionally with clear boundaries, serve as effective learning tools rather than permanent fixtures.
How do you manage transitioning from these quick hacks to more scalable solutions once the three-month window expires? Do you find that some of these “unscalable” choices become the foundation for future growth, or do they mostly serve as stepping stones to cleaner architectures?