From zero code to a working Scouting Agent using Python, Streamlit, and JetBrains AI.

When I saw the Cloud9 x JetBrains hackathon, I knew I had to jump in. The idea of combining esports strategy with code is exactly my lane, so I decided to tackle the "Automated Scouting Report" category. I know how much time coaches usually waste manually digging through match history, so I wanted to build something that solves that instantly. With a tight deadline, I stuck to a "speedrun" stack: Python and Streamlit inside PyCharm Community Edition. Honestly, the real MVP of the weekend was the AI Assistant, Junie. It cut out so much of the boring boilerplate work—like parsing complex JSON data—which let me focus entirely on the game logic, like calculating "First Blood" rates and determining optimal ban strategies. It was a crazy 48-hour sprint, but going from a blank file to a working dashboard that actually looks like a Cloud9 product felt amazing. It really proved to me that with the right IDE and a bit of AI help, you can build something production-ready in just a weekend.