Embracing the 3-Month Rule: A Practical Approach for Non-Scalable Solutions in Development
In the realm of startup development, advice from respected figures like Paul Graham holds significant weight. He famously promotes the idea of “doing things that don’t scale.” Yet, the practicality of this advice in the technical sphere often goes unaddressed. After eight months of building an AI podcast platform, I’ve cultivated a straightforward framework: any unscalable tactic receives a three-month trial period. At the end of these three months, it must justify its existence or be phased out.
The Challenge of Traditional Engineering Mindset
As engineers, we often prioritize scalability right from the inception of a project. Concepts like design patterns, microservices, and distributed systems form the backbone of applications designed to handle vast user bases. However, this approach can lead to costly delays in startups, where many features may be designed for users who have yet to materialize. My three-month rule helps me focus on crafting straightforward, even “subpar,” code that leads to tangible deployments, allowing for intimate insights into actual user needs.
Useful Infrastructure Hacks and Their Implications
1. Consolidated Resources on One VM
Everything—database, web server, background jobs, Redis—runs on a single $40 monthly virtual machine (VM). While this setup lacks redundancy and relies on manual backups, it’s proven to be enlightening. I’ve gathered more accurate insights into my resource requirements in just two months than any formal planning document could provide. It turns out that my resource demands peak at around 4GB of RAM, meaning my initial plan for a sprawling Kubernetes architecture would have been managing largely empty containers. Each crash has provided real data about what truly fails, revealing unexpected patterns.
2. Hardcoded Configurations for Simplicity
Instead of utilizing configuration files or environment variables, I’ve embedded constants throughout my code. This approach streamlines access and allows for rapid changes; any adjustments require a simple redeployment. Tracking changes through version control becomes seamless, and I’ve found that I only need to amend these values infrequently—saving my team considerable time that would otherwise be spent on development.
3. Utilizing SQLite in a Multi-User Environment
Surprisingly, I’m running SQLite for an application meant to support multiple users. My database size remains minimal at 47MB, effortlessly handling up to 50 concurrent users. This decision has provided valuable insights into my data access patterns, demonstrating
