Embracing Imperfection: The 3-Month Framework for startup Development

In the world of startups, the advice from Paul Graham—”Do things that don’t scale”—often rings true. Yet, the challenge lies in knowing how to effectively apply this principle, especially within the realm of coding and software development. After eight months of working on my AI podcast platform, I’ve adopted a pragmatic framework: each unscalable approach is allowed a lifespan of three months. At the end of this period, it must either demonstrate its worth through tangible results or be retired.

The initial instinct for many developers, especially engineers, is to prioritize scalable solutions from the outset. We’re trained to think about robust design, microservices, and distributed systems that can support millions of users. However, this mindset often overlooks the realities faced by startups, where focusing on scalability too soon can lead to inefficiencies and unnecessary complications. Instead of wasting precious resources optimizing for future users, I utilize my three-month rule to focus on straightforward, functional code that brings value and insights into user behavior.

Current Infrastructure Strategies: Simplifying for Clarity

Here are a few of my current unscalable tactical approaches that demonstrate clear value:

1. Single-VM Architecture

All components of my platform—database, web server, background jobs, and Redis—are hosted on one $40/month virtual machine. While this setup lacks redundancy and relies on manual backups, it has provided invaluable lessons about my actual resource requirements. Within two months, I discovered that my platform only requires 4GB of RAM at peak usage, debunking the need for a complex Kubernetes configuration that would have wasted resources managing unnecessary infrastructure. Notably, each crash offers real data to analyze, revealing insights I never anticipated.

2. Hardcoded Configuration

With constants specified directly in the code—like pricing tiers and maximum user numbers—I can quickly search and modify configuration values through my entire codebase. This simplicity means I can revisit and redeploy changes in a matter of minutes rather than embarking on extensive configuration management efforts. Over the last three months, I’ve made minimal changes to these settings, reinforcing the efficiency of this approach.

3. SQLite for Multi-User Access

In an unconventional choice, I’m using SQLite for my database needs, which currently occupies just 47MB and supports 50 concurrent users effortlessly. This decision arose from an analysis of my application’s use patterns, showing that 95% of operations