Embracing the 3-Month Rule: A Practical Guide for Startups
In the entrepreneurial ecosystem, a common mantra echoed by Paul Graham resonates: “Do things that don’t scale.” However, the challenge lies in effectively applying this principle to the technical realm. After spending eight months developing my AI podcast platform, I’ve established a straightforward yet powerful framework: any temporary, non-scalable solution gets a lifespan of three months. After this period, the solution is either refined into a scalable component or phased out entirely.
The Dilemma of Scalability in Startups
As engineers, our training often steers us toward crafting scalable solutions right from the onset. Concepts such as design patterns, microservices, and distributed systems excite us and are essential in managing substantial user bases. Nevertheless, in the startup world, optimizing for an expanded user base that may not exist yet can lead to time-consuming and expensive decisions.
To tackle this, my three-month rule compels me to embrace simpler coding practices that allow for rapid iteration. It helps me prioritize learning over perfection, ensuring I meet the true needs of my users.
Current Infrastructure Hacks: Lessons Learned
1. Consolidation with a Single VM
I chose to run my database, web server, background jobs, and caching system all on one $40 monthly virtual machine. While this might appear risky by traditional standards, the insights gained are invaluable. In just two months, I’ve understood my resource needs better than any elaborate planning document could offer. My AI-driven platform peaks at 4GB of RAM, revealing that a complex Kubernetes setup wouldn’t have been necessary and could have led to mismanaged resources. Watching it fail (twice) has provided me with real-time data on system vulnerabilities.
2. Hardcoded Configuration
With constants like PRICE_TIER_1 = 9.99 scattered through my codebase and minimal configuration complexity, making a change requires redeployment, but it’s quick and efficient. This approach has allowed me to monitor changes through version control precisely, and my experiences show that the frequency of such updates is low. What might require an entire week to set up in a configurable setup ended up being a mere fifteen minutes of deployment time across three months.
3. SQLite for Production
Yes, I’m using SQLite for my multi-user application. At only 47MB, it flawlessly handles up to 50 concurrent users. This choice led to an understanding of my access
