Babagana Zannah

Babagana Zannah

Head of Engineering · Engineering Director

Post-Hackathon Productionization Playbook: Turning 48-Hour Experiments into Reliable Production Systems

Most hackathons produce exciting demos that die in the lab. This playbook shows how to evaluate, govern and productionise promising AI experiments without killing momentum.

Table of Contents
  1. Hackathon Scoring Rubric That Predicts Production Success
  2. Lightweight Governance Without Killing Momentum
  3. 6-Week Productionization Checklist
  4. Success Metrics That Matter

1. Hackathon Scoring Rubric That Predicts Production Success

Traditional hackathon scoring (coolness, demo polish, wow factor) is a terrible predictor of production success. Replace it with this 5-dimension rubric:

Production-Readiness Score (out of 100)
• Problem Validation (25pts)
• Data & Integration Readiness (20pts)
• Scalability & Cost Awareness (20pts)
• Maintenance & Observability Plan (20pts)
• Team Ownership Commitment (15pts)
Babagana Zannah
Babagana Zannah

Head of Engineering / Engineering Director. I focus on turning AI experiments into production systems through evaluation, governance, observability and clear ownership.
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