The 3-Month Experiment: A Practical Approach to Unscalable Solutions in Tech
In the world of startups, agility and adaptability are key, and no one captures this spirit quite like Paul Graham with his famous adage: “Do things that don’t scale.” However, embedding this philosophy into technical development, particularly in coding, remains a challenge. After eight months of working on my AI podcast platform, I’ve created a framework that I call the “3-Month Rule,” which encourages experimentation through unscalable methods.
Embracing Unscalable Techniques
As developers, we often find ourselves drawn to the allure of scalability—the ability to handle large user bases and complex systems using sophisticated architectural designs like microservices and distributed systems. While such approaches are essential for larger firms, they can be a luxury for startups trying to establish their product.
In my experience, an emphasis on building scalable solutions too early can lead to inefficiencies and missed opportunities for real learning. The 3-Month Rule encourages me to experience and implement unscalable hacks that will either demonstrate their worth within three months or be phased out entirely. This method encourages straightforward coding practices that facilitate shipping real products and gathering user feedback early. Here are some of the practical hacks I’ve utilized, which may appear unconventional but have proven their value:
Current Infrastructure Hacks
1. Consolidated Infrastructure on One VM
All my services, from the database to background jobs, run on a single virtual machine (VM) priced at just $40 per month. There’s no redundancy, and I rely on manual backups.
This approach has allowed me to grasp my resource requirements in ways traditional capacity planning never could. I discovered that my platform typically requires only 4GB of RAM. Had I launched into a complex infrastructure setup with Kubernetes, I would have been burdened with managing unnecessary components. When crashes occur— and they have twice now—I gain valuable insights into real system vulnerabilities.
2. Simplified Configuration Management
Configuration details such as pricing tiers and user limits are hardcoded directly in the codebase. Although this means deployments happen whenever a change is needed, it also enhances transparency. I can quickly locate any configuration value across my entire project, and with numerous changes tracked in version control, I maintain a clear history of adjustments made.
Creating a dedicated configuration service would likely take countless hours, and yet, in three months, these values needed changing just three times. The time saved through this simplicity has been enormous
One Comment
This post beautifully highlights the power of embracing unscalable, practical hacks during early-stage development. The “3-Month Rule” reminds us that rigorous focus on immediate learning and rapid iteration often yields more valuable insights than premature investment in scalable architectures. Your example of consolidating infrastructure on a single VM underscores this—by removing complexity, you gain clear visibility into system behavior, which is essential for informed decision-making as you iterate.
Additionally, the approach of hardcoding configurations—though counterintuitive in the long term—serves as a strategic tool for agility and transparency at this stage. It enables quick adjustments and straightforward troubleshooting without the overhead of managing a complex configuration system.
This methodology emphasizes that, especially for startups, the key is to prioritize speed and learning over perfect scalability. As the platform matures, you can always optimize or re-architect—but initial experimentation like this often accelerates understanding and reduces technical debt in the early phases. Thanks for sharing these practical insights; they provide a valuable blueprint for early-stage product development.