Embracing the 3-Month Rule: A Pragmatic Approach to Development

In the world of tech startups, the concept of doing things that don’t scale is often touted, particularly by influential figures like Paul Graham. Yet, the conversation frequently overlooks the execution of such a principle in the coding process. After dedicating eight months to developing my AI podcast platform, I’ve established a straightforward but effective framework: every unscalable solution has a lifespan of three months. Post this period, the solution must validate its worth through tangible results or face elimination.

As engineers, we often find ourselves caught up in the allure of scalable design—from intricate architecture to microservices, crafting solutions to accommodate millions of users. However, this “big company” mindset can be a liability for startups. Pursuing scalability can turn into an expensive form of procrastination, aimed at users who might never materialize. My three-month rule compels me to write direct, uncomplicated code that fulfills immediate needs, enabling me to glean crucial insights into user behavior and system demands.

Ingenious Infrastructure Hacks: My Learning Experience

1. Consolidating Everything on a Single Virtual Machine

I currently operate a database, web server, background jobs, and Redis on a single virtual machine, costing just $40 a month. While there’s zero redundancy and I rely on manual backups, this setup has been immensely informative. In merely two months, I’ve accurately determined my platform’s resource requirements, discovering that it peaks at 4GB of RAM. The elaborate Kubernetes architecture I contemplated would have ended up managing idle containers.

When my system has crashed—twice so far—I’ve received invaluable data on failures, often revealing unexpected insights about what truly breaks.

2. Utilizing Hardcoded Configuration

Consider this setup:

python
PRICE_TIER_1 = 9.99
PRICE_TIER_2 = 19.99
MAX_USERS = 100
AI_MODEL = "gpt-4"

I’ve opted for hardcoded constants rather than external configuration files or environment variables. Adjusting any value requires a simple redeployment. The benefit? I can quickly search my entire codebase for configurations and track modifications through Git. In three months, I’ve needed to change these values only three times—saving countless hours of engineering effort.

3. Running SQLite in Production

Yes, my multi-user web application uses SQLite, with a database size of just 47MB. Surprisingly, it adeptly