Post-Mortem: Archiving My Hackathon Submission and Planning the Core Upgrades
The Submission
I recently competed in the HackerRank Orchestrate Hackathon (May 2026). The task was to build a system to triage and route technical support tickets across three datasets: HackerRank, Claude, and Visa.
While the code worked well enough to hit a high evaluation score within the 24-hour limit, the implementation was a typical hackathon MVP: a generic Python/ChromaDB retrieval pipeline that handled all incoming queries uniformly without domain-specific routing optimizations.
Creating the v0.1.0-beta Baseline
Instead of letting the code sit as a messy contest folder, I cleaned up the project environment to establish an immutable baseline under a v0.1.0-beta release tag.
- Clutter Removal: I deleted the generic competition templates (
problem_statement.md,CLAUDE.md,AGENTS.md) that don't add value to a standalone project. - Data Isolation: Kept the sample datasets inside the local directory so the pipeline remains fully functional and testable.
- Execution Logs: Retained the unedited runtime trace log (
log.txt) and final submission files as a snapshot of how the ChromaDB queries and triage loops behaved during the final evaluation run.
This frozen release marks the baseline for my initial working prototype.
The Upgrade Path: Optimizing the System
With the baseline safely tagged, the focus shifts to stripping out the remaining clutter on the main branch and optimizing the existing solution. Instead of leaving it as a generic wrapper, the plan is to clean up the logic and introduce low-level engineering optimizations.
The upcoming updates will focus on:
- Pipeline Refactoring: Cleaning up the folder structure, removing unwanted templates, and optimizing the ingestion flow without breaking the underlying core logic.
- Domain Separation: Transitioning from a completely uniform pipeline to a cleaner architecture that respects data boundaries between the three different knowledge bases.
- Performance Profiling: Analyzing where the Python/ChromaDB boundary hits bottlenecks during high-throughput ticket batching to prepare for targeted systems-level optimizations.
The v0.1.0-beta code is officially locked down as the historic starting point. Time to optimize the pipeline.