Embracing the 3-Month Rule: A Practical Approach to Unscalable Solutions in Tech Development
In the world of startups, the well-known adage by Paul Graham, “Do things that don’t scale,” serves as a mantra for innovation and resourcefulness. However, the conversation rarely delves into how to implement this principle effectively in the realm of coding. After eight months of developing my AI podcast platform, I’ve crystallized my approach into a concise framework: each unscalable hack gets a lifespan of three months. After this period, we’ll determine whether it demonstrates its worth and warrants further development, or if it will be discarded.
As engineers, we are often conditioned to prioritize scalability from the outset. The lure of sophisticated design patterns, microservices, and distributed systems creates a vision of seamless functionality that can support millions of users. Yet in the startup ecosystem, focusing solely on scalable solutions can lead to costly delays, creating elaborate structures for users and challenges that may never materialize. My three-month rule compels me to create straightforward, albeit imperfect, code that delivers results and reveals genuine user needs.
Ingenious Infrastructure Hacks and Their Rationale
1. Unified Operations on a Single VM
Currently, my entire setup—including the database, web server, background jobs, and caching—is run on a single virtual machine for a mere $40 a month. While this might seem reckless, the insights gained in two months far exceed what any capacity-planning document might offer. For instance, I’ve learned that my “AI-heavy” platform peaks at just 4GB of RAM. The complex Kubernetes architecture I almost adopted would have meant managing containers that weren’t even in use.
When challenges arise—because they inevitably do—I receive precise data about what fails, often revealing surprising insights about user behavior.
2. Hardcoded Settings for Simplicity
The configuration of my platform is direct and straightforward:
plaintext
PRICE_TIER_1 = 9.99
PRICE_TIER_2 = 19.99
MAX_USERS = 100
AI_MODEL = "gpt-4"
No configuration files, no environment variables—just constants embedded in the code. While some might argue this is shortsighted, it allows for rapid changes and instant tracking through git history. Instead of wasting a week to construct a configuration service, I’ve made only three modifications in three months, equating to about 15 minutes of redeployment versus countless hours of engineering effort
