Embracing the 3-Month Rule: A Strategic Approach to Short-Term Technical Solutions
In the ever-evolving world of startup development, the advice from noted entrepreneur Paul Graham to “do things that don’t scale” often resonates. However, there appears to be a gap in the conversation on how to translate this valuable insight into actionable strategies, particularly in coding. After dedicating eight months to building my AI podcast platform, I’ve formulated a method I like to call the “3-Month Rule,” which helps me navigate the challenges of unscalable solutions.
Understanding the 3-Month Rule
The core of my framework is straightforward: any temporary solution or hack I deploy is given a lifespan of three months. Following this period, it either validates its worth and earns a proper implementation, or it’s discarded. This approach diverges from the typical engineering mindset that prioritizes scalable solutions from the outset, favoring high-level design patterns and robust architectures. In the context of launching a startup, focusing on scalability can sometimes lead to wasted efforts in optimizing for potential users who may never materialize.
Applying the 3-Month Rule allows me to prioritize rapid development and real user engagement. I am compelled to write straightforward, if not imperfect, code that delivers functionality while providing valuable insights into user behavior.
Current Infrastructure Hacks: Intentionally Simple Solutions
Let’s delve into some of my current framework hacks and why they are strategically beneficial:
1. Consolidating Services on a Single VM
Currently, I manage my database, web server, background processes, and caching all on a single virtual machine—a choice that might seem reckless but has proven to be advantageous. By operating on a $40/month VM without redundancy and manually backing up my data, I’ve gained practical insights into my actual performance needs. This hands-on approach has revealed that my platform, which I expected to be resource-intensive, operates efficiently at just 4GB of RAM.
When the system crashes—something that has occurred twice so far—I receive data on what genuinely needs attention, often leading to surprises regarding which components fail.
2. Hardcoded Configuration
Instead of utilizing configuration files or environment variables, I’m currently using hardcoded constants in my codebase. This may sound outdated, but it has surprising benefits. Changes prompt a rapid redeployment process, and by scanning the code, I can track every configuration modification easily. Over the past three months, I’ve only had to make changes three times
