Embracing the 3-Month Rule: A Pragmatic Approach to Building in Startups
In the world of tech startups, we often hear the mantra “do things that don’t scale,” famously championed by Paul Graham. However, the challenge lies not only in understanding this advice but effectively applying it, especially in software development. Through my journey of creating an AI podcast platform over the past eight months, I’ve developed a practical framework I like to call the 3-Month Rule: every unscalable solution gets three months to prove its worth. If it doesn’t show promise, it gets retired.
The Mindset Shift: From Scalable to Practical
As engineers, we are generally conditioned to aim for scalable architectures from the outset. We admire the elegance of design patterns, microservices, and distributed systems that can accommodate countless users. However, this approach can become a form of procrastination for startups, where the need to optimize for a future user base can lead to unnecessary complexity. Instead, my 3-month guideline pushes me towards creating straightforward, albeit sometimes imperfect, solutions that can be shipped quickly—allowing me to better understand user needs.
Current Infrastructure Hacks: Smart and Efficient Choices
1. Consolidated Infrastructure on a Single VM
All components of my application—database, web server, background processes—run on a single $40/month virtual machine. While this might seem risky due to lack of redundancy, it has been incredibly enlightening. After just two months, I now have a clear picture of my resource needs. For instance, the application only peaks at 4GB of RAM. Had I opted for a complex Kubernetes setup out of the gate, I would have wasted time managing containers instead of focusing on real capacity.
2. Hardcoded Configurations for Quick Access
Rather than relying on config files or environment variables, I’ve hardcoded certain constants such as pricing tiers and user limits directly within the code. This approach, while seemingly counterintuitive, allows for rapid changes with minimal effort. Each adjustment requires just a brief redeployment, saving countless hours that would have been spent building a more elaborate configuration service.
3. Utilizing SQLite in Production
Surprisingly, I’m using SQLite for what’s intended to be a multi-user application. The database is lightweight—only 47MB—yet it efficiently handles up to 50 concurrent users. This simple choice revealed that my access patterns consist of predominantly read operations—95%
