The landscape of software development is undergoing a seismic shift with the rise of AI tools and platforms. As a developer in this transformative era, I've been reflecting on what this means for our profession and how we can adapt to thrive alongside AI.

When I launched my first SaaS product back in 2018, I made almost every architectural mistake possible. We chose the wrong database, overengineered our infrastructure, and underestimated the complexity of multi-tenancy. The result? Countless late nights debugging production issues and a codebase that became increasingly difficult to evolve.

Fast forward to today, and I've helped build and scale several successful SaaS platforms. The landscape has changed dramatically in just a few years—new tools, platforms, and patterns have emerged that make building scalable SaaS applications more accessible than ever.

In this post, I'll share the hard-won lessons and current best practices for building a SaaS that can scale from your first customer to your first thousand, without requiring a complete rewrite along the way.