Embracing the 3-Month Rule: A Pragmatic Approach to Non-Scalable Solutions in Tech Development
In the world of startups, a common mantra often heard is Paul Graham’s advice: “Do things that don’t scale.” While this concept is widely acknowledged, the discussion on implementing it in the realm of software development is rarely explored.
After eight months of building my AI podcasting platform, I’ve established a personal framework that centers around a straightforward rule: any non-scalable workaround is given a lifespan of just three months. At the end of this period, it either proves its worth and is developed into a sustainable solution, or it is removed from the project entirely.
As engineers, we are conditioned to focus on scalable architectures from day one—think design patterns, microservices, and distributed systems. However, this is often a mindset best suited for larger enterprises. In a startup environment, adhering strictly to scalable solutions can lead to unnecessary delays, as they often revolve around hypothetical future users and problems that may never arise. My three-month guideline compels me to create deceptively simple yet effective code that is deliverable and reveals actual user needs.
Innovative Infrastructure Hacks Worth Considering
1. Consolidating Functions on One Virtual Machine (VM)
All aspects of my platform—including the database, web server, background jobs, and caching—operate on a single VM that costs just $40 per month. While this choice lacks redundancy and relies on manual backups to my local machine, the insights gleaned from this setup have been invaluable. Within just two months, I gathered more practical knowledge about my resource requirements than any potential capacity planning document could provide. My platform, which I initially anticipated would require vast resources, only peaks at 4GB of RAM. I’ve encountered crashes twice, allowing me to gather real data on unexpected failure points.
2. Hardcoded Configurations for Simplicity
By using hardcoded constants throughout my codebase—like pricing tiers and maximum user limits—I can easily locate any configuration value in seconds. While this approach may appear impractical, it dramatically simplifies the process of redeploying changes, saving countless hours in engineering time. With a mere three changes in three months, the trade-off between quick redeployment and complex setup becomes readily apparent.
3. Leveraging SQLite for Production Use
Despite its reputation, I opted for SQLite in a multi-user web application, with a database size of just 47MB. To my
One Comment
This post highlights a valuable and often overlooked aspect of startup development: the importance of practical experimentation over theoretical scalability in early stages. The 3-month rule acts as a disciplined approach to validate ideas quickly and avoid unnecessary overengineering. I particularly appreciate the emphasis on collecting real-world data—like resource usage from a simple VM setup—to inform better decisions later.
The decision to leverage straightforward solutions such as hardcoded configurations and SQLite underscores that, in a fast-paced environment, simplicity can be a strategic advantage. It allows teams to remain nimble, iterate rapidly, and gain critical insights into actual user needs before investing in more complex, scalable infrastructure.
This approach is reminiscent of the “build fast, iterate faster” philosophy, which prioritizes validated learning. Have you considered documenting these initial experiments and learnings for future reference or sharing them as case studies? It could be invaluable for other founders and engineers navigating similar challenges in early-stage product development.