Think beyond prompts. Build the future with AI.
The CoLab Nation Prompt Engineering Challenge 2026 is a national online innovation challenge where participants transform ideas into intelligent AI solutions. Whether you're just starting with Generative AI or already experimenting with LLMs, this challenge is your opportunity to learn, compete, and create impactful solutions.
Challenge Roadmap
Round 1 | Learning Module & Registration
15 – 22 July
Start with curated learning resources covering Prompt Engineering, Generative AI, LLMs, and practical prompting techniques.
Complete your registration and prepare for the challenge.
Round 2 | Gatekeeper Quiz
23 – 24 July
Take an online qualifying quiz designed to test your understanding of the learning module, AI fundamentals, and logical reasoning.
Round 3 | Build Sprint
25 – 29 July
On 25 July, the official problem statement will be released.
Participants will have 5 days to design, iterate, and build an AI-powered solution using Prompt Engineering.
Submit your final prompts, outputs, and solution before the deadline.
Round 4 | Grand Finale
30 July
Shortlisted finalists will present their solutions live before the judging panel, followed by an interactive Q&A.
Winners will be selected based on innovation, prompt quality, execution, and presentation.
Why Join?
Learn Prompt Engineering from curated resources.
Solve a real-world AI challenge.
Win special prizes and certificates.
Gain national recognition.
Connect with a growing AI community.
Join the Official CoLab Nation WhatsApp Community
https://chat.whatsapp.com/CczXCdWuWbQAcznSy5KHph?s=cl&p=a&mlu=0&amv=1
Learn → Qualify → Build → Pitch → Win
One Prompt. One Problem. Endless Possibilities.
Note:
This is a free opportunity.
Judge Accessibility
Organizer email available25/25
Student-run event15/15
Actively looking for judges25/25
Small event (120 participants)10/10
No corporate sponsors10/10
New or emerging organizer10/10
Public registration available5/5
Online format (judge from anywhere)10/10
Top signals
Organizer email available
Student-run event
Actively looking for judges
Organizers
Alex Johnson
alex@example.org
Jamie Rivera
jamie@example.org
Sam Chen
sam@example.org
Estimated Audience
Mostly Students
ExperienceStudent
OccupationStudents
Beginner Friendly
Women in Tech
Technical Focus
AI95%
Web80%
Mobile25%
Industries
Healthcare
Education
Climate
Technologies
Python
React
OpenAI
Why this estimate
• Hosted by a university
• Open to students
• MLH member event
Estimate inferred from event metadata, not actual attendee data.