Embracing the 3-Month Rule: A Strategy for Unscalable Development in Startups
In the world of startups, the common wisdom often espoused by entrepreneurial figures like Paul Graham states, “Do things that don’t scale.” However, the practical implementation of this concept within software development is rarely discussed. After spending the last eight months developing my AI podcast platform, I’ve created a framework to adapt this principle effectively: every unscalable hack is granted a lifespan of three months. At the end of this period, each solution must either prove its worth through tangible results or be discarded.
The Dilemma of Scalability
As engineers, our training is deeply rooted in crafting scalable architectures from the outset. We are well-versed in design patterns, microservices, and the intricate frameworks that support large user bases. However, this “big company” mentality can create pitfalls for startups. Often, developing scalable code equates to investing in a future that may never materialize, leading to costly delays. My three-month rule compels me to adopt a simpler approach: writing straightforward, albeit imperfect, code that can quickly be deployed and assessed based on user feedback.
Practical Hacks: Learning through Simplicity
1. All-in-One Virtual Machine
My entire infrastructure operates on a single $40/month virtual machine, encompassing the database, web server, background processes, and more. While this may seem risky due to a lack of redundancy, it has provided invaluable insights into my actual resource needs. I’ve discovered that my platform’s peak demands only require 4GB of RAM, insight that would have been obscured by over-engineering.
2. Simplified Configuration Management
Instead of employing complex configuration files, I utilize hardcoded constants scattered throughout my code. Updates necessitate redeployments, but this approach allows for rapid tracking of any changes through Git history, simplifying the review process. The efficiency gained from this method—allowing me to make three alterations in three months—far outweighs the time it would take to implement a dedicated configuration service.
3. SQLite for Database Management
Surprisingly, I have chosen SQLite to power my multi-user web application. With a database size of only 47MB, it manages 50 concurrent users seamlessly. This experience has clarified my access patterns—95% reads and only 5% writes—validating SQLite’s suitability for my needs. Had I defaulted to a system like Postgres, I would
