Embracing the 3-Month Experimentation Principle: A Pragmatic Approach to Coding in Startups

In the realm of software development, there’s a well-known adage from Paul Graham: “Do things that don’t scale.” While this advice is widely recognized, the practical application of it in the world of coding often goes unaddressed. After spending the last eight months working on my AI podcast platform, I’ve developed a unique framework that may just transform the way you approach your projects: the 3-Month Experimentation Principle.

The Concept Behind the 3-Month Rule

As developers, we’re typically trained to aspire toward “scalable” solutions from the outset. We often find ourselves wrapped up in intricate design patterns and architectures, fantasizing about systems that will efficiently handle millions of users. However, this mindset is often more suited for established companies than for startups.

In a nascent business, optimizing for scalability can turn into an expensive form of procrastination. You’re expending energy on users who may not even exist yet, tackling issues that might never arise. By implementing my 3-month rule, I’ve committed to deploying simple, straightforward code—considered “bad” by conventional standards—that actually gets put into action. This has proven invaluable for understanding the real needs of my users.

Current Infrastructure Hacks: Practical Lessons Learned

1. All-In-One Virtual Machine

My entire infrastructure—database, web server, background jobs—operates on a single $40/month virtual machine. While there’s no redundancy and I manually back things up to my local machine, this setup has revealed crucial insights about my actual resource demands in just two months. Rather than mismanaging an overly complicated environment like Kubernetes, I’ve discovered that my platform typically peaks at 4GB of RAM, leading to surprising revelations when things go wrong. Spoiler alert: the failures are rarely what I expected.

2. Simplified Configuration Management

My configuration is entirely hardcoded—think constants scattered throughout the code. While this might sound primitive, it streamlines the process significantly. I can quickly locate any configuration value using a simple command, and each change is easily tracked via version control. Instead of spending days developing a dedicated configuration service, I’ve optimized my workflow to minimize deployment time to a mere 15 minutes for infrequent changes.

3. Production-Grade SQLite

Believe it or not, SQLite powers my multi-user web app without issue. Despite handling 50 concurrent users