Discovering new opportunities in EdTech with genAI and prompt engineering, from user insight to PoC 

Company: Cambridge Innovation Center, Tokyo.

Case Study: Discovering new opportunities in EdTech with genAI and prompt engineering, from user insight to PoC.

Introduction: This case study outlines a dynamic product discovery cycle, from problem framing to building a PoC at the esteemed Cambridge Innovation Center, Tokyo. The initiative was focused on understanding crucial challenges in EdTech, with a focus on personalized learning. Leveraging genAI’s advanced technology and Large Language Models (LLMs), a practical Proof of Concept solution was developed and validated. 

Objectives:

• In-Depth Insights about a specific problem area: Understanding and deep-diving into the personalised learning space, from high-level problem area, to focused problem framing, focusing on tailored learning obstacles, challenges and pain points.  
• Understand the application of genAI and LLM Models for addressing the identified problem: identifying, testing and iterating on several applications of genAI and evaluating the effectiveness and accuracy. 
• Hackathon-Powered Fast PoC Iterations: Collaboratively transforming the identified problem into conceptual solutions and PoC within a single-day hackathon, in collaboration with the genAi startups from CIC. 

Approach:

• Focused Problem Exploration Workshop: Conducted a comprehensive exploration and problem-framing workshop for personalized learning obstacles, challenges and pain points. 
• Intensive 1-Day Hackathon for building PoC: Multi-disciplinary teams, in collaboration with the EdTEch startup, build a robust PoC, seamlessly integrating GenAI technology.
• User Interviews and Insights: The PoC was tested and evaluated with 5 user interviews, unveiling enriched insights into the LLM-powered solution’s effectiveness.

Results:

• In-Depth LLM-Driven Customer Insights: The workshop and user interviews enabled a detailed understanding and specifying the actual user problems to be solved, and enabled how they can be solved with LLM more effectively 
• Successful PoC Application of GenAI: The user interviews showcased how GenAI’s PoC can have practical applications in solving specific and well-defined user challenges. 
• Collaboration between multi-disciplinary teams and startups:  The synthesized collaboration between research, product, design and engineering effectively resulted in building valuable PoC, amplifying its impact and efficacy.

Summary:

Through the lens of product discovery, harnessed by genAI’s power, the project revealed how with focused effort on problem farming and defining precise challenges, can be effectively transformed into feasible solutions, leveraging GenAI. The resultant PoC stands as a testament to the concrete outcomes that arise from the exploration and the powerful interplay of technology, user engagement, and cross-team collaboration among multidisciplinary experts.