Embracing the 3-Month Rule: A Practical Approach to Building Unscalable Solutions

In the realm of startup culture, there’s a widely acknowledged mantra from Paul Graham: “Do things that don’t scale.” However, the conversation often falls short when it comes to detailing how this principle applies to coding practices. Over the past eight months, as I’ve worked on my AI podcast platform, I’ve devised a straightforward framework to implement this philosophy: each unscalable hack I employ is given a lifespan of exactly three months. After this period, it’s either refined based on its demonstrated value or phased out entirely.

As developers, we’re typically conditioned to prioritize “scalable” solutions from the outset—concepts like design patterns, microservices, and distributed systems often dominate our thinking. However, this mindset tends to align more with the objectives of larger organizations rather than the hands-on realities of a startup environment.

In many cases, writing scalable code at this stage can lead to unnecessary delays, focusing on user demands that may never materialize. The 3-month rule motivates me to produce straightforward, albeit imperfect, code that not only gets shipped but also provides insights into user needs.

Current Infrastructure Hacks: Smart Choices for Learning

1. Consolidated Operations on One Virtual Machine

Currently, my platform operates entirely from a single $40/month virtual machine that houses everything from the database to background jobs. While this may seem risky due to the lack of redundancy and reliance on manual backups, it has significantly clarified my resource requirements. Within two months, I’ve realized my platform requires only 4GB of RAM at peak usage—far from the complex Kubernetes configuration I had considered. Every crash—which has occurred twice thus far—offers valuable data on what truly fails, and it’s rarely what I initially predicted.

2. Hardcoded Configuration Values

My configurations are hardcoded directly into the codebase:

plaintext
PRICE_TIER_1 = 9.99
PRICE_TIER_2 = 19.99
MAX_USERS = 100
AI_MODEL = "gpt-4"

With no configuration files or environment variables, any adjustments necessitate a redeployment. This may seem primitive, but it empowers me to swiftly search through my entire codebase for any value, with all changes meticulously tracked in git history. Building a dedicated configuration service would have required significant time, yet my three adjustments over just three months have taken a mere 15 minutes. This