Embracing the 3-Month Rule: A Pragmatic Approach to Building in Tech Startups

In the world of technology startups, there’s a well-known piece of advice from entrepreneur Paul Graham: “Do things that don’t scale.” While this mantra is widely acknowledged, the application of this principle within the context of software development is often overlooked. After eight months of building my AI podcast platform, I’ve developed a straightforward yet effective framework centered around the concept of the “3-Month Rule.” This approach allows me to implement unscalable solutions temporarily, giving me just three months to evaluate their worth before either refining or discarding them.

As engineers, we are conditioned to design scalable solutions right from the get-go. We often find ourselves embracing complex architectures—think distributed systems, microservices, and elegant design patterns—intended for managing potentially millions of users. However, this mindset is typically more suited to larger organizations. In a startup environment, developing scalable code can sometimes lead to unnecessary delays, as it requires us to address concerns for users that may not yet exist. By adopting my 3-month framework, I can prioritize producing simple, effective code that is capable of shipping quickly and reveals the genuine needs of my users.

Current Infrastructure Hacks: Smart Decisions in Simplicity

Here’s a look at some of the unorthodox, yet strategic, technical choices I’ve made during my development process, shedding light on why they work in my favor:

1. Consolidated Operations on a Single VM
My entire infrastructure—including database, web server, background jobs, and Redis—is operating on a singular $40/month virtual machine. It may seem risky due to the lack of redundancy and reliance on manual backups, but this setup has proven invaluable. In just two months, I’ve gained insights into my actual resource requirements, discovering that my resource-intensive platform reaches peak demand at only 4GB RAM. My previously considered Kubernetes setup would have introduced unnecessary complexity.

2. Hardcoded Configuration
With constants like PRICE_TIER_1 = 9.99 and MAX_USERS = 100 strewn across my codebase, my setup might raise eyebrows. However, this lack of abstraction means I can search through configurations instantly. Each change requires just a brief redeployment, saving me hours that would have been consumed by developing a configuration management system.

3. Leveraging SQLite for Production
Running SQLite for a multi-user application may not be the norm, yet my