Embracing the 3-Month Rule: A Pragmatic Approach to Development in Startups
In the world of tech startups, there’s a popular mantra often attributed to Paul Graham: “Do things that don’t scale.” While this advice is widely recognized, the practical application of it, especially in the realm of coding, remains less discussed. Over the past eight months of developing my AI podcast platform, I have adopted a simplified yet effective framework that I call the “3-Month Rule.” This principle states that any non-scalable solution I implement will be evaluated after three months. If it proves its worth, we will invest in a robust solution; if not, it will be phased out.
Rethinking Scalability in Startups
As developers, there’s an inherent drive to create scalable solutions from the outset. We often envision elaborate architectures—design patterns, microservices, distributed systems—that can accommodate millions of users. However, this approach is more suited to larger companies with established user bases. In the startup environment, striving for scalability can often lead to unnecessary delays, focusing efforts on hypothetical users while neglecting the immediate needs of the actual user base.
The 3-Month Rule encourages me to write straightforward, albeit potentially “messy,” code that allows for rapid deployment and genuine user feedback. By doing so, I gain a clearer understanding of what truly adds value for my users.
Current Infrastructure Insights: What I’m Learning from Simple Solutions
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Utilizing a Single Virtual Machine (VM)
My entire stack, including the database, web server, and background tasks, runs on one $40-per-month VM—no redundancy or complex setups. This approach has provided invaluable insights into my resource requirements. Instead of laboriously planning out capacity, I’ve learned that my platform comfortably operates at 4GB of RAM. When the server experiences outages, I receive direct feedback about the system’s pain points, which often surprises me. -
Hardcoded Configuration
My configuration is embedded within the code as constants rather than utilizing separate files or environment variables. While this seems rudimentary, it allows me to efficiently track changes through Git, and modifications require minimal deployment time. Instead of investing time in developing a dedicated configuration service, I’ve streamlined my process, making it possible to adapt quickly based on intermittent needs. -
SQLite as My Production Database
Contrary to conventional wisdom, I have deployed SQLite for my application. It currently handles 50 concurrent users
One Comment
This post provides a refreshingly pragmatic perspective on early-stage development in startups. The 3-Month Rule is a great practical tool—encouraging teams to prioritize learning and iteration over premature scalability optimization. I appreciate how you emphasize that “messy” or simple solutions can be powerful when paired with rapid feedback, especially in the initial phases.
Your insights on using a single VM, hardcoded configurations, and SQLite challenge traditional best practices but showcase the value of tailored, lightweight setups that facilitate quick iteration and real-world insights. It’s a reminder that sometimes, controlled experiments with simple infrastructure can reveal more about user needs and system limitations than complex architectures built prematurely.
Looking forward, as your platform grows, I imagine gradually evolving towards more scalable solutions based on validated data. But maintaining this mindset of flexibility and learning, anchored by the 3-Month Rule, will likely serve you well. Thanks for sharing this thoughtful approach—it’s a valuable contribution to the ongoing conversation about balancing rapid development with scalable architecture.