Embracing the 3-Month Rule: A Practical Approach to Non-Scalable Solutions
In the entrepreneurial tech world, you’ve likely heard the mantra from Paul Graham: “Do things that don’t scale.” However, there’s often a gap in understanding how to effectively implement this concept, especially in software development. After eight months of building my AI podcast platform, I’ve established a framework that guides my decisions: each non-scalable solution is given a lifespan of three months. At the end of this period, it must either demonstrate its value and be properly implemented or be discarded.
As developers, we’re often conditioned to create scalable infrastructures from the very beginning. We focus on sophisticated design patterns, microservices, and distributed systems—architecture meant to support millions of users, but in the context of a startup, this can lead to wasted energy and resources. Instead of solving problems for non-existent users, my three-month rule compels me to write straightforward, often “imperfect” code that gets shipped quickly and ultimately reveals what my users truly need.
Current Infrastructure Strategies: Why They Work
1. Unified Virtual Machine Hosting
All components of my application—database, web server, background processes, and caching—are running on a single $40/month virtual machine (VM). Admittedly, this setup lacks redundancy and requires manual backups, but it has provided immense value. Within just a couple of months, I’ve gained insights into my actual resource requirements, something no extensive capacity-planning document could offer. Realistically, my “AI-driven” platform peaks at only 4GB of RAM, revealing that an intricate Kubernetes setup would have ultimately been an exercise in managing idle space.
When the system has failed (which has happened twice), I’ve gathered tangible data on the precise causes of the failures—almost always different from my expectations.
2. Hardcoded Configuration Values
I keep configuration simply defined within the codebase, such as:
python
PRICE_TIER_1 = 9.99
PRICE_TIER_2 = 19.99
MAX_USERS = 100
AI_MODEL = "gpt-4"
There are no configuration files or environment variables; just constants placed throughout the code. Changing any of these requires redeploying the application, granting me a straightforward mechanism to track changes via git history. While creating a dedicated configuration service might take a week, I’ve modified these values three times in three months—15 minutes of rede
