Embracing the Unscalable: My 3-Month Strategy for Rapid Learning in Development

In the entrepreneurial landscape, one piece of advice stands out from Paul Graham: “Do things that don’t scale.” While this is a well-cited notion, the challenge remains in its practical application, especially in software development.

After dedicating eight months to building my AI podcast platform, I’ve devised a straightforward model to embrace unscalable solutions: I allow each of these temporary hacks a lifespan of three months. At the end of that period, I assess whether they warrant a more robust implementation or if they should be discarded.

As engineers, we often default to creating scalable systems from the outset, drawing on sophisticated frameworks, microservices, and intricate distributed architectures. However, this mindset can lead to unnecessary complications, particularly in the startup environment where focusing on scalability can turn into costly delays. My three-month rule compels me to prioritize pragmatism over perfection, enabling me to produce straightforward, albeit imperfect, solutions that ship quickly and provide real insights into user needs.

My Strategic Infrastructure Choices: Unconventional Yet Effective

1. Single VM Setup

I operate my entire platform—database, web server, and background jobs—on a single virtual machine costing just $40 per month. While this setup lacks redundancy and relies on manual backups, it has illuminated my resource requirements far more effectively than extensive planning documents ever could. My “heavy-duty” AI platform only needed 4GB of RAM, so had I pursued a more complex architecture like Kubernetes, I would have been stuck managing idle resources. The two times my system crashed provided invaluable data, revealing bottlenecks I didn’t anticipate.

2. Simplified Configurations

Instead of using configuration files or environment variables, I’ve implemented hardcoded constants throughout my codebase. For instance, defining things like pricing tiers and AI models directly in the code facilitates rapid changes—redeploying only takes about 15 minutes compared to the week it would take to set up a configuration service. Plus, this method allows me to track every adjustment through version control and easily review my own changes.

3. Leveraging SQLite for Production

Yes, my multi-user web app utilizes SQLite as its database, totaling a mere 47MB. Surprisingly, it can accommodate 50 simultaneous users without any hitches. My analysis showed that access patterns are predominantly read-heavy, making SQLite an ideal choice. Had I opted for PostgreSQL from the