Embracing the 3-Month Rule: A Practical Approach for Unscalable Solutions
In the dynamic world of startups, the advice “do things that don’t scale,” famously championed by Paul Graham, is often easier said than done—especially when it comes to coding. After dedicating eight months to developing my AI podcast platform, I stumbled upon an effective strategy: the 3-Month Rule. This framework allows each unscalable innovation to thrive for exactly three months. If it proves its worth, it gets upgraded; if not, it’s time to let go.
The Challenge of Scalability in Startups
As software engineers, we are often conditioned to aim for scalable solutions from the outset. We dream of sophisticated design patterns, microservices, and architectures that can accommodate millions of users. However, this mindset can be detrimental in the startup environment, where building a scalable infrastructure too early can lead to wasted resources and procrastination. It’s like preparing a feast for guests who haven’t even RSVP’d yet.
My 3-Month Rule encourages me to focus on simplicity and practicality in my coding approach. Rather than getting bogged down in complex, “perfect” code, I prioritize straightforward solutions that can quickly provide insights into the needs of my actual users.
Innovative Infrastructure Hacks: Why They Work
1. Single Virtual Machine Setup
Currently, everything from my database to the web server runs on one $40/month virtual machine, with no redundancy and manual backups to my local system. This approach has been eye-opening—I’ve gained more insight into my resource requirements in just two months than I would have from any formal capacity planning document. It turns out that my AI platform only uses 4GB of RAM at peak times, rendering my more intricate Kubernetes plans irrelevant.
When system failures occur (which have happened a couple of times), they provide valuable lessons about what actually goes wrong—insights that are often surprising.
2. Hardcoded Values—The Hidden Gem
Instead of complex configuration files, I have hardcoded constants such as:
python
PRICE_TIER_1 = 9.99
MAX_USERS = 100
AI_MODEL = "gpt-4"
While this may seem primitive, it allows me to trace any configuration changes quickly and track them in version history. Redeploying these minor adjustments takes mere minutes instead of consuming precious engineering hours.
3. Using SQLite in Production
Running SQLite for a multi-user web application
One Comment
This post offers a compelling perspective on the importance of embracing unscalable, iterative approaches early in a startup’s journey. The 3-Month Rule resonates strongly—by committing to quickly testing and validating ideas without over-engineering, founders can focus on genuine product-market fit rather than premature perfection.
I particularly appreciate the emphasis on simplicity, such as using a single virtual machine and hardcoded values. These practices prioritize rapid learning and adaptation—crucial in the early stages. While such approaches may seem “primitive,” they often reveal critical insights about real user behavior and system bottlenecks that more complex setups might obscure.
One additional angle worth considering is the role of disciplined experimentation within this framework—documenting what works and what doesn’t over each three-month cycle can create a valuable de facto design pattern, guiding future scalability decisions. It’s a pragmatic balance between the “doing things that don’t scale” mantra and strategic planning, allowing startups to grow organically based on validated needs.
Overall, this mindset fosters agility and resourcefulness—key traits for sustainable innovation. Thanks for sharing these practical insights!