Exploring what’s possible when AI-assisted development meets real business challenges.
Project: Superblocks Hackathon
Focus: Workflow improvement, AI-assisted development, application design
Timeline: Two business days
Applications: CourseTrack 2.0, DevTrack 2.0, Content Media DAM
The Challenge
Managing a large amount of information isn’t necessarily difficult because of the information itself. It’s difficult when that information lives in different places, changes frequently, and doesn’t give your team a clear picture of what needs attention.
That’s a challenge I’d been working to solve within my own team.
Two applications, CourseTrack and DevTrack, grew out of the need to better organize and manage the information behind our course library and development workflows. I wanted to explore whether I could build tools that made that information easier to access, understand, and act on.
Then an opportunity came along to take that exploration further.
Lexipol hosted a two-day hackathon to evaluate Superblocks as a potential company-supported platform for building internal applications with AI.
I’d never used Superblocks before, but I wasn’t starting from scratch.
The Work Before the Hackathon
My introduction to AI-assisted application development started months earlier with Lovable.
I began building early versions of CourseTrack and DevTrack, experimenting with how their interfaces, data, and workflows could come together. As the applications evolved, I moved to a setup using Vercel for deployment, Supabase for the database, and GitHub for managing the code.
Each iteration taught me something new.
I became more comfortable thinking through application structure, how information moves between systems, and what it takes to get a working application hosted and accessible.
More importantly, I learned how to translate an operational problem into something I could actually build.
That experience became the foundation for the hackathon.
A New Platform, a Familiar Problem
Going into the event, I had a clearer understanding of what I wanted the applications to accomplish.
I started with product requirements documents based on the earlier versions of CourseTrack and DevTrack. These helped define the purpose of each application, the information it needed to manage, and the workflows it should support.
Rather than spending the entire hackathon figuring out what to build, I could focus on learning Superblocks and turning those requirements into working experiences.
I also built a third application: a Digital Asset Manager designed around another common content-production challenge—finding and reusing existing media.
Three Applications, Three Workflow Challenges
CourseTrack 2.0 – Making Course Information Manageable
CourseTrack addresses the challenge of managing a large course library while keeping important details visible and organized.
The application was designed around a central view of course information, including version history, accreditation details, and course refresh schedules.
The goal was to make it easier for the team to understand the state of the library, identify courses that need attention, and spend less time piecing together information from multiple sources.
DevTrack 2.0 – Bringing Development Work Into Focus
DevTrack focuses on the work behind course development.
Course projects involve multiple contributors, assignments, timelines, and feedback. Without a central place to bring that information together, it can be difficult to understand how work is progressing.
DevTrack was designed to provide a clearer view of course-development activity, including project information, time spent, contributors, and feedback from the people involved.
The idea was simple: make the work easier to track so the team can make better-informed decisions.
Digital Asset Manager – Making Existing Content Easier to Find
The Digital Asset Manager tackles a different problem: media that already exists but isn’t easy to locate.
Images, videos, diagrams, and other assets can become scattered across folders and storage locations. When people can’t find what they need, they may spend time searching or recreating something that’s already available.
This application explored a more organized approach to finding, previewing, and reusing existing content.
The focus was on making useful assets more discoverable and accessible within the content-production workflow.
Two Days of Building
With the requirements as a starting point, I used the hackathon to explore how quickly I could bring these applications to life in Superblocks.
There was a learning curve. I was working in a new environment, translating existing ideas into a different development platform, and figuring out how to get the applications functioning within a limited amount of time.
But the experience I’d gained from earlier AI-assisted development made a difference.
By the end of the two business days, I’d built three operational applications with approximately 75% of their planned features functional.
They weren’t finished products, but they were working demonstrations of how these workflow challenges could be addressed.
Sharing the Work
At the end of the hackathon, I presented the applications, demonstrated their functionality, and walked through my approach to development.
I also shared live demonstrations with my team and later with the development team during an all-hands meeting.
These conversations gave me the opportunity to show not just what I’d built, but how I’d approached the work—from understanding the problem to defining requirements and using AI-assisted tools to build a solution.
What I Took Away
The biggest takeaway wasn’t that AI could help me build applications quickly. I’d already started discovering that.
It was seeing how the experience I’d gained over several months could translate into a completely new platform.
I went into the hackathon without Superblocks experience and came out with three operational applications, a stronger understanding of another development environment, and a clearer sense of what’s possible when AI-assisted development is applied to real workflow challenges.
For me, this work reinforced something important:
You don’t always have to wait for the perfect tool or the perfect opportunity to start solving a problem. Sometimes the most valuable thing you can do is start building, learn along the way, and keep improving what you’ve created.