Embracing the Unscalable: My 3-Month Framework for Development
In the world of startups, the mantra “Do things that don’t scale,” popularized by Paul Graham, is well known. However, the practical application of this philosophy in software development isn’t often discussed. After spending eight months building my AI podcast platform, I’ve devised a straightforward approach: any quick-and-dirty solution has a life expectancy of just three months. By that point, it either proves its worth and is developed into a solid foundation, or it is discarded.
The Startup’s Dilemma
As engineers, we’re often trained to aim for scalable solutions from the get-go. This training emphasizes robust design patterns, microservices, and distributed systems—frameworks that can support millions of users. While these architectural principles shine in larger organizations, they can lead to costly delays and frustrations at the startup level. Focusing on scalability too soon can mean optimizing for an audience that doesn’t exist and worrying about problems that may never arise.
My three-month rule compels me to write simpler, more direct code that delivers real value, enabling me to understand user needs effectively.
My Infrastructure Hacks: Smart Solutions in a startup Environment
- Single VM Architecture
Setup: My entire infrastructure—database, web server, background jobs, and caching—operates on a single Virtual Machine (VM) costing $40 per month. This setup has no redundancy, and I perform manual backups to my local machine.
Why It Works: In just two months, I have gained more insights into my actual resource requirements than any capacity planning document could provide. My platform’s maximum RAM usage peaks at 4GB, which clarifies that a complicated Kubernetes architecture would have been an unneeded complexity.
- Simplicity in Configuration
Approach: I use hardcoded constants throughout my code, such as pricing tiers and user limits, without complicating the setup with configuration files or environment variables.
Benefits: This method enables rapid querying of my codebase for any configuration changes. Tracking price modifications in version control means I can easily monitor changes. Instead of taking a week to implement a configuration service, I’ve saved countless hours by redeploying every fifteen minutes for configuration changes in three months.
- Utilizing SQLite in Production
Implementation: I currently run SQLite for a multi-user web application. The database size is a mere
