Embracing the 3-Month Rule: A Pragmatic Framework for Engineering Startups
In the world of startups, the age-old wisdom of Paul Graham rings true: “Do things that don’t scale.” However, the practicalities of how to implement this advice in a coding environment are often overlooked. Over the past eight months while developing my AI podcast platform, I have formulated a framework that has yielded significant insights into the coding process: the 3-Month Rule. This straightforward principle allows each non-scalable hack a lifespan of three months—after which it must either prove its worth and evolve into a sustainable solution, or it will be scrapped.
The Challenge of Scalability in Startup Environments
As software engineers, we are often conditioned to prioritize scalable solutions from the outset. The allure of robust architecture—complete with design patterns, microservices, and distributed systems—appeals greatly in environments where user numbers can soar into the millions. However, in a startup scenario, obsessively focusing on scalability can lead to unnecessary expenses, as it often means building for users that don’t yet exist and addressing problems that may never arise.
The 3-Month Rule has compelled me to embrace simpler, more direct coding practices that prioritize shipping over perfection and, most importantly, that reveal the true needs of my users.
Current Infrastructure Strategies: Lessons Learned
Let’s explore some of the unconventional practices I’ve adopted, each proving to be a savvy choice rather than an oversight:
1. Single-VM Deployment
My entire setup runs on a $40/month virtual machine that houses the database, web server, background jobs, and Redis, with no redundancy and manual backups. This arrangement, while seemingly precarious, has allowed me to comprehend my resource requirements far better than any forecasting document could. Through experience, I discovered that my “AI-heavy” platform only peaks at 4GB of RAM. The Kubernetes system I almost deployed would have been a complex solution managing unoccupied containers. When failures occur (which they have, on two occasions), I gather concrete data about what truly breaks—often different from my initial assumptions.
2. Hardcoded Configuration Values
Configuration constants like pricing tiers and user limits are scattered throughout my files without any sophisticated configuration management. While deploying new changes requires a redeployment, the simplicity enables quick searches throughout the codebase for any value, with every alteration tracked via version control. Creating a separate configuration service would be a week-long undertaking, yet I’ve
One Comment
This is a compelling approach that highlights the importance of agility and learning in early-stage startups. The 3-Month Rule serves as a practical guideline to balance experimentation with accountability—a way to prevent “zombie solutions” from persisting beyond their usefulness. Your emphasis on embracing simpler infrastructure and temporary hacks aligns well with the startup mindset of prioritizing validated learning over comprehensive scalability from day one.
One point worth expanding is how this philosophy fosters a culture of continuous iteration and risk management. For instance, your experience with a single-VM deployment underscores that understanding system limitations in real-world scenarios often surpasses theoretical planning. It also encourages a mindset of “fail fast, learn fast,” enabling teams to adapt quickly without over-investing in early infrastructure.
Additionally, integrating a lightweight documentation or note system about why certain shortcuts are taken can be invaluable for future scaling or onboarding new team members. As your platform matures, you’ll likely find that some of these quick hacks become foundational, while others are replaced with more scalable solutions—guided by the insights gained during those initial three-month periods.
Overall, your framework offers a balanced and pragmatic route for startups to remain nimble, focus on user needs, and evolve efficiently. Looking forward to seeing how you refine this approach as your platform grows!