Embracing the 3-Month Rule: A Practical Framework for Non-Scalable Solutions
In the startup landscape, the common wisdom from Paul Graham of Y Combinator rings loudly: “Do things that don’t scale.” However, the challenge lies in translating this advice into actionable steps, especially in the realm of software development. After eight months of constructing my AI podcast platform, I’ve created a straightforward but effective guideline: any non-scalable innovation gets a lifespan of just three months. If it demonstrates its value within that timeframe, it receives a solid framework; if not, it’s time to move on.
Rethinking Scalability for Startups
As engineers, we often default to scalable solutions from the outset: microservices, distributed architectures, and other complex designs aimed at accommodating millions of users. While these methodologies are impressive, they represent the mindset of larger companies, not startups. In a fledgling company, striving for scalability can serve as a costly delay, as it often involves preparing for hypothetical user bases and challenges. The three-month rule compels me to adopt a straightforward coding approach, one that allows me to deliver quickly and gain insights into what my users genuinely require.
My Infrastructure Innovations and Their Strategic Value
- Unified Server Environment
I’m currently operating all core functions—database, web server, and background processes—on a single virtual machine, costing just $40 a month. While this setup lacks redundancy and relies on manual backups, the benefits have been enlightening. Over the last two months, I’ve gained a clearer understanding of my resource requirements than I would have through lengthy planning documents. It turns out, my “AI-intensive” application only uses about 4GB of RAM. A complex Kubernetes system would have meant managing idle containers instead.
- Inline Configuration Constants
I’ve opted for hardcoded constants throughout my codebase rather than relying on configuration files or environment variables. For instance, basic values like pricing tiers and maximum user limits are hardcoded. Though this entails redeploying for any adjustments, it allows me to track changes easily and verify configurations through version control. In the span of three months, I’ve made only three changes—totaling about 15 minutes of redeployment time compared to the substantial investment it would have taken to construct a configuration management service.
- SQLite as a Production Database
Surprisingly, I’m using SQLite for my multi-user web app. The database is a mere 47MB and handles up
