Embracing the 3-Month Rule: A Pragmatic Approach to Non-Scalable Solutions in Tech
In the world of startups and emerging technologies, it’s not uncommon to encounter the wisdom of Paul Graham, who famously advises entrepreneurs to “do things that don’t scale.” However, translating this advice into practical coding practices can be a challenge that isn’t often discussed.
After dedicating eight months to the development of my AI podcast platform, I’ve crafted a straightforward yet effective framework: each non-scalable hack is permitted to exist for just three months. Following this period, it either demonstrates its worth and is further developed, or it is discarded.
As engineers, we’re often conditioned to seek scalable solutions from the beginning—considerations like design patterns, microservices, and distributed systems dominate our thinking. These architectural frameworks can effectively support millions of users but often represent a mindset detached from startup realities. In many cases, focusing on scalability too soon can lead to expensive procrastination—optimizing for users who may not yet exist and tackling problems that may never arise. My three-month rule nudges me toward writing straightforward, albeit imperfect, code that enables real results and clarifies user needs.
Current Infrastructure Insights: Ingenious Hacks Worth Trying
1. Unified Virtual Machine Deployment
Everything—database, web server, background jobs, and caching—runs on a single $40/month virtual machine with no redundancy and manual backups to my local drive.
This approach may seem rudimentary, but it’s been enlightening. I’ve gained valuable insights into my resource requirements much faster than through traditional planning documents. My so-called “AI-heavy” platform occasionally requires only 4GB of RAM, while a complex Kubernetes architecture would have left me managing unused containers. Each crash (which has happened twice) has provided tangible learning opportunities about unexpected failure points.
2. Hardcoded Configuration Values
Instead of using configuration files or environment variables, I use hardcoded constants throughout my codebase.
For example:
plaintext
PRICE_TIER_1 = 9.99
PRICE_TIER_2 = 19.99
MAX_USERS = 100
AI_MODEL = "gpt-4"
This unconventional method allows me to quickly search and update configurations, ensuring every change is documented in my version control history. The time spent on three updates over three months equates to about 15 minutes of redeployment, compared to the week it would take to develop a comprehensive configuration service.
**3
One Comment
This is a compelling approach that resonates deeply with the lean startup philosophy—embracing rapid iteration and learning over premature optimization. The 3-month rule provides a pragmatic boundary, encouraging us to test hypotheses quickly and avoid over-investment in solutions that may not be necessary yet.
Your examples—using a single VM for simplicity and hardcoded configs for speed—highlight the value of starting with minimal, tangible setups. These hacks enable immediate feedback, helping to shape a clearer understanding of user needs and system requirements before scaling complexities.
One potential enhancement could be to embed a structured review process at the end of each three-month cycle. For instance, documenting what worked, what didn’t, and what’s worth scaling up or discarding. This keeps the momentum aligned with learning goals and ensures that even quick hacks are intentional and purposeful.
Overall, your framework underscores that strategic non-scalability—when time-limited—can be a powerful catalyst for innovation and agility in early-stage tech projects. Thanks for sharing such practical insights!