Embracing the 3-Month Rule: A Practical Approach to Non-Scalable Development
In the tech world, there’s a well-known principle often touted by Paul Graham: “Do things that don’t scale.” While this advice is fairly popular, applying it to software development tends to be overlooked. After spending the last eight months building my AI podcast platform, I’ve established a pragmatic framework that might just revolutionize how we approach unscalable solutions—the 3-Month Rule.
Understanding the 3-Month Rule:
The premise is straightforward: every unscalable hack or workaround I implement is given a lifespan of three months. During this time, it must demonstrate its worth—either by proving effective enough to be developed further or by getting discarded entirely.
As engineers, we find ourselves trained to think in terms of scalable solutions right from the outset. We delve into advanced design patterns, microservices, and intricate distributed systems—all engineered to accommodate millions of users. However, this mindset often aligns more with large corporations than with the nimble nature of startups.
In the world of a budding startup, writing scalable code can often equate to unnecessary delays, prioritizing users that may never materialize, and solving problems we might never encounter. My 3-Month Rule explicitly encourages the crafting of straightforward, minimalistic code that directly addresses real user feedback and needs.
My Effective Infrastructure Hacks
Here are a few of the strategic yet non-scale solutions I’ve implemented that, upon closer inspection, provide invaluable insights:
1. One Virtual Machine for Everything
I’ve consolidated my database, web server, background jobs, and Redis on a single $40 monthly VM. Admittedly, this approach lacks redundancy and relies on manual backups. Yet, this has proven to be a game changer—I’ve gleaned more about my resource necessities within just two months than any extensive planning documentation could provide. For instance, I’ve discovered that my platform requires a mere 4GB of RAM at peak usage. Had I set up a complex Kubernetes architecture at the outset, I would have found myself managing countless empty containers.
When the system has crashed—a couple of times—I’ve received actual data on what fails. Unsurprisingly, it’s rarely what I initially anticipated.
2. Hardcoded Configurations Galore
Consider the configuration:
“`python
PRICE_TIER_1 = 9.99
PRICE_TIER_2 = 19.99
MAX_USERS = 100
AI_MODEL
One Comment
This is an insightful approach that highlights the importance of rapid experimentation and learning in early-stage development. The 3-Month Rule encourages founders and engineers to prioritize learning over perfection—accepting temporary hacks as valuable sources of real-world data. I particularly appreciate the emphasis on simplicity and direct feedback, which often leads to more resilient and user-centric solutions in the long run.
While maintaining a focus on speed and minimalism, it’s worth considering that some unscalable hacks might need careful documentation or clear thresholds for transition, ensuring that short-term solutions don’t become technical debt. Also, as your platform scales, having a plan to iteratively refine these solutions will be crucial.
Overall, this framework champions a practical mindset: reject the illusion of perfect scalability at the start, learn fast, and adapt accordingly. It’s a great reminder that sometimes, doing less with intentionally temporary solutions can reveal more about what truly matters—and that’s a powerful recipe for sustainable growth.