Embracing the 3-Month Rule: A Practical Approach to Unscalable Solutions in Development
In the realm of startup advice, one piece of wisdom stands out: “Do things that don’t scale.” This principle, popularized by Paul Graham, is often discussed in abstraction, leaving many developers wondering how to practically apply it. Having spent the last eight months developing my AI podcast platform, I’ve devised a straightforward framework known as the 3-Month Rule. Under this framework, any unscalable solutions I implement are allocated a lifespan of three months. After this period, they either demonstrate their worth and are rebuilt, or they are discarded.
Navigating the Scalability Trap
As software engineers, we’re trained to create scalable solutions from the outset. We’re encouraged to adopt sophisticated design patterns, implement microservices, and architect systems that can potentially handle millions of users. However, this vast thinking often leads to complex, expensive solutions that may not even be necessary for the fledgling stages of a startup.
The 3-Month Rule compels me to write simple, functional code that can be quickly deployed, allowing me to truly understand user needs without getting bogged down in premature optimization.
Current Infrastructure Innovations: Smart Hacks Over Complex Systems
Here’s a look at how I’ve implemented my philosophy through some unconventional yet effective hacks.
1. Simplified Architecture with a Single Virtual Machine
Everything from the database to background jobs runs on a single virtual machine costing just $40 a month. While this setup foregoes redundancy and requires manual backups, it has provided invaluable insights into my resource needs. In just two months, I’ve learned that my platform, which is expected to be resource-intensive, only peaks at 4GB of RAM. The Kubernetes infrastructure I almost developed would likely have been a waste, serving to manage idle resources instead of valuable ones.
2. Directly Hardcoded Configurations
Instead of utilizing configuration files or environment variables, I use hardcoded constants for pricing and user limits throughout my code. This might seem limiting, but it streamlines the process of making changes. Tracking alterations in my git history is straightforward, and the time saved substantially outweighs a one-time setup of a full configuration service.
3. SQLite in a Multi-User Environment
Yes, I’ve adopted SQLite for my web application, and it’s thriving. The entire database is only 47MB, yet it handles approximately 50 concurrent users effortlessly
One Comment
Thank you for sharing your practical approach with the 3-Month Rule—it’s a refreshing perspective that emphasizes agility and learning over premature optimization. I particularly appreciate how you’ve embraced simple, cost-effective solutions early on, like using a single VM and hardcoded configurations, to quickly validate assumptions and gather real user data.
This method aligns well with the Lean Startup mindset, where rapid experimentation drives informed decision-making. It’s also a great reminder that in the early stages, investing heavily in scalable infrastructure can sometimes be an impediment rather than a help.
I’m curious—have you considered how this approach might evolve as your platform grows? For instance, at what point do you plan to transition from SQLite to more scalable database solutions, and how will you manage that migration without disrupting your development cycle?
Overall, your framework exemplifies the importance of balancing practical experimentation with strategic planning. Thanks for inspiring a more flexible and cost-conscious approach to early-stage tech development!