Embracing the Three-Month Experiment: A Framework for Lean Development

In the tech world, you’re likely familiar with Paul Graham’s well-known mantra: “Do things that don’t scale.” While the principle is widely acknowledged, the implementation in coding often goes unexplored. Over the past eight months developing my AI podcast platform, I’ve identified a practical approach: any non-scalable hack in my code has a lifespan of just three months. After that, it either substantiates its value and receives the necessary upgrades or it gets phased out.

The startup Perspective: Avoiding Perfectionism

As engineers, we are taught to focus on scalable solutions from the outset. We find ourselves navigating complex architectures like microservices and distributed systems, designed to accommodate millions of users. However, this big-company mentality often leads to wasted resources in the startup environment. The truth is that scalable infrastructure can sometimes act as a costly form of procrastination—optimizing for potential users who may never materialize and solving problems that aren’t urgent.

My three-month framework compels me to write straightforward, albeit imperfect, code that yields immediate results and teaches me valuable insights about user needs.

My Pragmatic Technical Approach

1. Single Virtual Machine Setup

My entire infrastructure—comprising the database, web server, background jobs, and Redis—operates on a single $40/month virtual machine (VM). While this may seem risky with zero redundancy and manual backups, this setup has provided invaluable insights. Within just two months, I discovered that my “AI-heavy” platform peaks at 4GB RAM, information that would have been obscured by an elaborate Kubernetes architecture.

When the system crashes, which has happened twice, I gain crucial data about failures—prompting revelations that often surprise me.

2. Hardcoded Configurations

I rely on hardcoded constants for critical configurations, such as:

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

Having no configuration files or environment variables simplifies changes, requiring only a redeployment with a concise command. I’ve revised these values just three times in three months—spending a mere 15 minutes redeploying compared to the 40 hours it would have taken to build an elaborate configuration management system.

3. SQLite for Production

Running SQLite for a multi-user web application, with a