Embracing the 3-Month Rule: A Practical Approach to Non-Scalable Solutions in Software Development
In the world of startups and innovative tech, one piece of advice often echoed is Paul Graham’s call to “do things that don’t scale.” However, implementing this philosophy in a technical context can be a bit more complex. After eight months of developing my AI podcast platform, I’ve devised a straightforward yet effective framework: every non-scalable solution is given a lifespan of three months. After this period, it either proves its worth and is refined for durability or is discarded.
As software engineers, we are traditionally trained to prioritize scalable solutions from the outset. We gravitate towards sophisticated architectures—microservices, distributed systems, and design patterns—that promise to handle millions of users. But this mindset often belongs to larger companies with significant resources. In the early stages of a startup, aiming for scalability can sometimes just delay necessary progress, as we waste time optimizing for an audience that may not even exist yet or tackling challenges that are yet to arise.
By adopting my 3-month approach, I’m encouraged to develop straightforward, albeit imperfect, code that can be deployed quickly. This allows me to gain hands-on insights about what my users truly require.
Innovative Yet Simple Strategies: My Current Infrastructure Hacks
1. Consolidated Operations on a Single Virtual Machine
I’ve consolidated my database, web server, background jobs, and Redis onto a single $40/month virtual machine with no redundancy and manual backups. The brilliance of this setup is that I’ve gained an invaluable understanding of my resource requirements far beyond what any theoretical document could provide. I’ve found that, during peak demand, my resource needs amount to just 4GB of RAM. Had I pursued a complex Kubernetes deployment, I would have been wrangling unnecessary empty containers instead.
2. Static Configuration Throughout
Instead of using configuration files or environment variables, I’ve utilized hardcoded constants in my code. This makes adjusting parameters a matter of redeploying the application, but it also allows me to quickly search for any configuration value across my codebase. In just three months, I’ve made only three updates to my configurations, saving me significant engineering hours by avoiding the setup of a dedicated configuration service.
3. SQLite as a Robust Solution
Yes, I’m utilizing SQLite for a multi-user web application. With a total database size of just 47MB, it handles up to 50 concurrent users effortlessly. This
