Embracing the 3-Month Rule: A Pragmatic Approach to Non-Scalable Solutions in Tech
In the world of startups and emerging technologies, it’s not uncommon to encounter the wisdom of Paul Graham, who famously advises entrepreneurs to “do things that don’t scale.” However, translating this advice into practical coding practices can be a challenge that isn’t often discussed.
After dedicating eight months to the development of my AI podcast platform, I’ve crafted a straightforward yet effective framework: each non-scalable hack is permitted to exist for just three months. Following this period, it either demonstrates its worth and is further developed, or it is discarded.
As engineers, we’re often conditioned to seek scalable solutions from the beginning—considerations like design patterns, microservices, and distributed systems dominate our thinking. These architectural frameworks can effectively support millions of users but often represent a mindset detached from startup realities. In many cases, focusing on scalability too soon can lead to expensive procrastination—optimizing for users who may not yet exist and tackling problems that may never arise. My three-month rule nudges me toward writing straightforward, albeit imperfect, code that enables real results and clarifies user needs.
Current Infrastructure Insights: Ingenious Hacks Worth Trying
1. Unified Virtual Machine Deployment
Everything—database, web server, background jobs, and caching—runs on a single $40/month virtual machine with no redundancy and manual backups to my local drive.
This approach may seem rudimentary, but it’s been enlightening. I’ve gained valuable insights into my resource requirements much faster than through traditional planning documents. My so-called “AI-heavy” platform occasionally requires only 4GB of RAM, while a complex Kubernetes architecture would have left me managing unused containers. Each crash (which has happened twice) has provided tangible learning opportunities about unexpected failure points.
2. Hardcoded Configuration Values
Instead of using configuration files or environment variables, I use hardcoded constants throughout my codebase.
For example:
plaintext
PRICE_TIER_1 = 9.99
PRICE_TIER_2 = 19.99
MAX_USERS = 100
AI_MODEL = "gpt-4"
This unconventional method allows me to quickly search and update configurations, ensuring every change is documented in my version control history. The time spent on three updates over three months equates to about 15 minutes of redeployment, compared to the week it would take to develop a comprehensive configuration service.
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