Embracing the 3-Month Rule: A Tactical Approach to Non-Scalable Solutions in Development
In the startup world, innovation often stems from the courage to deviate from conventional wisdom. Renowned entrepreneur Paul Graham famously stated, “Do things that don’t scale.” Yet, there is often a lack of discussion about how to effectively put this advice into practice within the realm of coding and technical development.
Over the past eight months, I have immersed myself in creating a podcast platform powered by Artificial Intelligence. Throughout this journey, I have established a straightforward yet robust framework: any non-scalable solution I implement is granted a lifespan of three months. After this period, the solution must either demonstrate its effectiveness and be fully developed or be discarded entirely.
The reality is that as engineers, we’re conditioned to design systems with scalability in mind from the very beginning. We often gravitate towards complex frameworks like microservices, distributed systems, and intricate architecture, which can accommodate millions of users. However, this type of thinking is better suited for established companies rather than startups.
At the startup phase, chasing scalable solutions can often lead to unnecessary delays and expenses. We end up preparing for users who may never arrive, tackling challenges that might not exist yet. My three-month rule compels me to write straightforward, albeit imperfect, code that is deployable and reveals the genuine needs of my users.
Current Infrastructure Strategies: Smart Simplifications
1. All-in-One Virtual Machine Setup
Everything—database, web server, background tasks, and Redis—operates on a single $40/month virtual machine, without any redundancy. I manually back up data to my local storage.
This approach may appear reckless at first glance, but it has provided invaluable insights into my actual resource requirements within two months—insights that traditional capacity planning could not have uncovered. For instance, my AI-driven platform peaks at just 4GB of RAM. Had I opted for a more complex Kubernetes infrastructure, I would have been managing idle containers.
When system crashes occur (and they have, twice), I gain real-time feedback on the specific points of failure—often surprising discoveries that shift my understanding of the system.
2. Simplified Configuration Management
python
PRICE_TIER_1 = 9.99
PRICE_TIER_2 = 19.99
MAX_USERS = 100
AI_MODEL = "gpt-4"
Forget about configuration files and environment variables—my constants
