Last weekend, I built another little startup: Slicefair.co. It’s an equity tracking app for bootstrap founders based on the slicing pie methodology. The idea came about because I’m preparing to bring on a co-founder for my SaaS, ContentIn, and I’ve always hated tracking equity splits with spreadsheets.
While there’s an existing slicing pie app out there, I wasn’t interested in yet another subscription—especially one priced at $20 per person per month. So, leveraging AI and my technical skills, I decided to build my own solution. I figured I could not only solve my own problem but also create something affordable for other bootstrap founders, selling it as a one-time purchase and supporting the indie hacker community.
Here’s the journey of how it all came together, what went wrong, and the lessons I learned along the way.
The Journey:
The idea for Slicefair.co wasn’t new. I’d tracked equity splits with spreadsheets before and always found the process cumbersome. When preparing to onboard a co-founder for ContentIn, I knew I needed something better.
The existing slicing pie app felt too expensive, especially for indie founders like me, so I decided to build my own lightweight alternative that could be sold for a one-time fee. I started by defining the app’s requirements using the Slicing Pie book as a reference.
I uploaded the book to NotebookLM, which helped me create an initial spec. Then, I refined this spec with Claude to ensure it was clear and actionable. The plan seemed simple: build the app with Nuxt.js for the frontend and a Node.js backend for flexibility. But things quickly became more complicated.
Initially, I planned to let Bolt handle most of the heavy lifting. I gave it the refined spec, confident it could handle the work autonomously. Instead, I found myself stuck in an endless error loop, debugging the same issues over and over with no progress.
Hoping the backend setup was the issue, I switched from Node.js to Supabase—a platform I’d never used before—but I ran into the same frustrations. I wasted hours trying to debug schema errors and fix AI-generated outputs, only to realize I was making things worse instead of better.
Frustrated, I decided to pivot to tools I was already comfortable with. I switched to Directus, my favorite headless CMS, and hosted it on my own server. To speed up frontend development, I used Windsurf, an AI-powered IDE combining the functionality of Cursor and Bolt.
Once I found a Nuxt Directus starter project, things started to click. Integrating Directus with Nuxt became straightforward, and I began implementing the app’s features step by step.
With the backend in place, I focused on building the frontend and automating workflows. Here’s how it all came together:
Backend with Directus:
Frontend with Nuxt and Windsurf:
Landing Page Creation:
By Sunday evening, I had a fully functional MVP: a sleek, intuitive app for tracking equity splits based on the slicing pie methodology.
Future Plans for Slicefair.co
The app’s single purpose is to make tracking equity splits transparent and easy for bootstrap founders. To complement this, I plan to add a blog that explains the slicing pie methodology and supports founders in understanding the process better.
Based on feedback from early users, I’ll prioritize features from the roadmap, which currently includes:
Key Learnings
Stick With What You Know:
AI Still Needs Guidance:
Break Tasks into Smaller Chunks:
Directus Flows Are a Game-Changer:
The MVP Mindset:
Reflections:
This app is already a significant improvement over tracking equity in spreadsheets. The real-time updates and pie chart visualization make it easy to understand and even motivating—it’s rewarding to see my slice grow as I contribute more to my startup.
Next, I plan to market the app, likely launching it on platforms like AppSumo for lifetime deals to gain initial traction. From there, feedback from early users will shape its future.
Building Slicefair.co reaffirmed a few key points: AI is transformative when paired with technical skills, sticking to familiar tools saves time, and learning from each project makes the next one even smoother. With AI and the right stack, I was able to create a product in two days that I’m genuinely proud to share with the indie hacker community.
PSA: By the way, this article was written with GPT as my co-writer. I dictated the story during a break, and GPT helped me polish and structure it. AI truly makes everything a little faster and more fun.