Welcome to TheFirst Spark Challenge🔥

A 7-Day AI Build Sprint | 19–26 June 2026

The First Spark Challenge is the pre-event build sprint for The First Spark AI Youth Symposium - Singapore's full-day gathering for student founders, builders, and operators exploring how to build, work, and start up in the AI age.

From 19–26 June, students build from home, solo or in teams, and submit an AI project for a shot at pitching live in front of founders, investors, speakers, and partners on Symposium Day (27 June).

Bring your curiosity and ship something real.

📅 Sprint Dates: 19–26 June (submit by 25 June, 23:59)

👥 Open to: JC, polytechnic, IHL, university students & NSmen - solo or teams

📍 Build from: Anywhere in Singapore

🎯 Pitch to: Founders, investors, and partners at the live symposium

What's in it for you:

• AI builder credits from confirmed partners
• Mentor feedback on users, demos, and product direction
• A live pitch slot at The First Spark (if shortlisted)
• Prizes and further opportunities for top teams
• Invite-only dinner with speakers and partners for the best demo teams

How to join:

1. Register and indicate you want to join the Build Sprint
2. Receive your info pack with the full brief, timeline, and builder resources
3. Build from 19–25 June
4. Submit via Devpost by 25 June, 11:59pm (demo pitch deck + 1-min YouTube demo + GitHub repo if available)
5. Get selected to pitch live on 27 June!

Selected teams will be invited to pitch their project live on AI Youth Symposium Day (27 June).

• Challenge-Solution Fit (20%)
  Does the project meaningfully solve the challenge statement or solve a meaningful problem or clearly improve a real-world task? Is the target audience or use case well-defined? Does the solution directly address the core bottleneck, not just symptoms?
• AI Leverage and Technological Execution (25%)
  Does the core product work reliably during the demo? Are APIs integrated in a way that adds real value? Is there evidence of custom logic, workflows, or system design? Does the solution go beyond a simple wrapper around an LLM?
• Product Thinking & UI/UX (20%)
  Is the user flow and interface clear, intuitive, and easy to navigate? Does the product reduce friction vs current alternatives? Is the output/actionable value obvious to the user? Does the solution feel like a complete experience, not just a feature?
• Originality & Insight (20%)
  Is the approach differentiated from typical solutions? Does it reframe the problem in an interesting way? Does it feel like something that could evolve into a strong product?
• Evidence of Real Demand (15%) (Not expected, but would be a differentiator)
  Did the team speak to users (interviews, surveys, quick validation)? Do they show evidence of: 1. pain points 2. user behaviour 3. real workflows Have they validated assumptions, even lightly? Do they demonstrate insight beyond guesswork?