Embracing the 3-Month Rule: A Strategic Approach to Innovation in Tech
In today’s startup ecosystem, the wisdom of Paul Graham’s advice—”Do things that don’t scale”—is well known. However, the practical implementation of this concept within the realm of coding remains a somewhat unexplored territory. Through my journey of developing an AI podcast platform over the last eight months, I’ve established a straightforward yet effective framework: every unscalable approach has a lifespan of just three months. After this period, those strategies must either demonstrate their worth and be developed into more robust solutions, or they face elimination.
The Paradigm Shift in Engineering Perspectives
As engineers, we are often conditioned to prioritize the design of scalable solutions from the get-go. We immerse ourselves in architectural best practices such as microservices, distributed systems, and intricate design patterns meant to accommodate millions of users. This mindset, while valuable in large enterprises, can hinder the agile development process in a startup environment.
In many cases, focusing on scalability too early simply leads to expensive delays. We find ourselves optimizing for hypothetical users, which may never even materialize, while leaving critical user insights unexplored. My three-month rule compels me to embrace straightforward, even “imperfect” coding practices that get products shipped, thus revealing what customers actually need.
Current Infrastructure Hacks: Smart Choices for Rapid Testing
1. All-in-One Virtual Machine
I opted to run everything—from the database to the web server and background jobs—on a single $40/month virtual machine. This setup lacks redundancy and relies on manual backups to my local machine. While this might seem reckless, it has offered invaluable insights into my resource requirements much faster than traditional planning methods.
After two months, I discovered that my “AI-heavy” platform typically only uses 4GB of RAM. Had I implemented a complex Kubernetes architecture, I would have been busy managing inactive containers rather than focusing on real user needs. Each untimely crash has provided concrete data about what truly fails—insight that I would not have gained otherwise.
2. Simplified Configuration Management
Instead of utilizing configuration files or environment variables, I’ve hardcoded critical values throughout my codebase, such as pricing tiers and user limits. Although this method may seem outdated, it allows me to quickly search for any configuration value and track changes seamlessly through version control. The trade-off? A few minutes of redeployment versus extensive hours wasted on developing a dedicated
