Embarking on a solo SaaS project is a rollercoaster. This is a candid look at building an AI video analysis tool, learning to cut major features (like team collaboration) to focus on the MVP, and the painful lessons from three complete backend rewrites.
Every developer has "the idea", that spark for a SaaS product you're convinced the world needs. My latest is an intelligent tool for content creators: a service that automatically scans long-form video (like a Twitch VOD) and suggests the most engaging clips for social media.
The initial excitement was huge, the vision was clear, and I couldn't wait to start building. But the journey from that exciting vision to a shipped, public MVP is far harder and messier than it looks, especially when you're the sole developer. It's a journey that, for me, has involved a painful but educational tour of three entirely different backend architectures.
The Twin Dangers: Finishing and Feature Creep
The first major hurdle for any solo developer is actually finishing a project. Without external deadlines, it's a battle against your own motivation. This battle is made infinitely harder by the main antagonist of the story: feature creep.
My vision for the video tool was ambitious. I wanted an AI Content Scout that could find interesting clips using multiple analysis methods. But my ambition didn't stop there. My mind began to race with adjacent features:
First, I started planning a full fledged, in-browser video editor so users could tweak the suggested clips perfectly.
Then, it didn't stop there. I started architecting a complex collaboration system to add support for a content creator's entire team, with different user roles for editors and moderators.
In my head, I was building a product for a professional studio before I had even built a working tool for an individual. This was classic, textbook feature creep.
A Painful Lesson: The Anatomy of Three Rewrites
This lack of a ruthlessly focused plan at the start led to my most painful lesson. My front end was solid, Vite, TypeScript, shadcn, Tailwind, and TanStack. The backend, however, was a different story, with each rewrite a direct consequence of my ballooning ambition.
Rewrite 1: The Monolithic Step Function. My first attempt was serverless, trying to build all these analysis features and team logic into a single, massive AWS Step Function. It was a tangled, complicated state machine that was incredibly difficult to enhance or debug.
Rewrite 2: The Overkill VPC. Reacting to that complexity, I swung in the opposite direction and architected a solution using containers running inside a VPC. This gave me more control, but it came with a shocking price tag for a personal project.
Rewrite 3: The 'Just Right' Serverless Approach. This led me back to serverless, but with a new philosophy: small, decoupled functions. The final architecture uses AWS Amplify, S3, DynamoDB, and a series of small, targeted Lambda functions.
The Path Forward: A Public Commitment to MVP
The painful rewrites taught me that I needed to stop chasing every good idea and focus on the core value proposition. The key wasn't just choosing the right tech, but choosing the right problem to solve first. The problem I'm solving is finding clips for a single creator, not managing a collaborative editing workflow for a team.
So, with the backend finally on solid ground, the MVP is now clearly defined. It will be an "Automated Clip Finder" that does four things for an individual user, and does them well:
Scans for Loud Moments.
Transcribes the video.
Analyses Words Per Minute.
Provides a Confidence Score.
The in-browser editor and the team collaboration system are great features for V2 or V3, but for the MVP, they were dangerous distractions. By cutting them, I can focus all my energy on perfecting the core AI analysis engine.
The rewrites were frustrating, but they were the necessary tuition for learning this critical lesson in product strategy. The real work starts with shipping a focused product, and that's exactly what I intend to do.