The 3-Month Framework: A Pragmatic Approach to Non-Scalable Solutions
In the ever-evolving world of technology and startups, the advice from entrepreneurs like Paul Graham resonates deeply: “Do things that don’t scale.” But how can we effectively apply this philosophy within the realm of coding?
After dedicating eight months to developing my AI podcast platform, I’ve established a practical framework that I’d like to share: every non-scalable hack receives a lifespan of three months. Following this period, it must either demonstrate its worthiness for further development or face elimination.
Rethinking Scalability in Startups
As software engineers, we often approach projects with an emphasis on scalability from the very outset. We envision intricate design patterns, microservices, and distributed systems—all crafted to accommodate an influx of users. While these concepts are essential for established companies, such an outlook can become counterproductive within a startup environment.
In a startup, devoting resources to scalable solutions can often equate to postponing vital decisions. By focusing on potential future users, we end up optimizing for problems that may never arise. My three-month approach compels me to produce straightforward, albeit “imperfect,” code that brings tangible results and informs me of actual user requirements.
Current Infrastructure Hacks: Practical Insights
1. Consolidated Virtual Machine Usage
I run my database, web server, background jobs, and Redis all on a single virtual machine (VM) that costs just $40 per month. While I sacrifice redundancy, the trade-off has yielded invaluable insights regarding my actual resource needs. From this setup, I’ve learned that my AI platform performs optimally with a peak utilization of just 4GB of RAM. What could have been an extensive Kubernetes configuration has instead allowed me to address real-time failures and understand my system far better.
2. Hardcoded Configurations
Within my codebase, configurations are embedded as constants rather than stored in separate files. This means that any changes necessitate redeployment. Although this may seem inconvenient, the advantages are plentiful: the simplicity and traceability improve my workflow significantly. In the past three months, I’ve adjusted configurations only three times; this trade-off saves me a considerable amount of development time compared to creating a complex configuration management system.
3. SQLite in Production
Surprisingly, my web application utilizes SQLite, managing an impressively compact database of just 47MB while accommodating up to 50 concurrent users seamlessly. I’ve learned that my access
