Dreamify: Hands-on Exploration of Developing, Iterating, and Marketing a Direct-to-Consumer, AI-Native Game Engine

Dreamify: Hands-on Exploration of Developing, Iterating, and Marketing a Direct-to-Consumer, AI-Native Game Engine

Deepzone, a starup, is currently crafting a groundbreaking, AI-native game engine designed to deliver unparalleled immersive gaming experiences directly to consumers. The Deepzone engine is supported by a modular, plug-and-play AI ecosystem that underpins its MVP prototype, offering both flexibility and cutting-edge technology. Deepzone’s primary market lies in North America and targets a young, educated demographic, including high school, undergraduate and master’s students aged 16-26. This audience, encompassing both Chinese and non-Chinese individuals, likely engages with online literature, enjoys casual gaming, frequently uses platforms like TikTok, and watches twitch live streaming. Based in Shanghai, the Deepzone startup has successfully secured the initial round of funding. With this milestone achieved, they are now poised to accelerate the product development and introduce innovative game engine to the North American market with urgency. 

For more information, please visit: https://www.deepzone.io/  

Discord: https://discord.gg/nNuEpZrbbD  

This project delved into the potential of Artificial Intelligence (AI) in the gaming industry, focusing on multi-AI-agent systems, large language models, and machine learning to create an innovative educational experience. The Deepzone team provided students with essential materials and guidance to understand market dynamics and product insights. Students formed teams, selected an IP topic, and outlined a casual game concept. The actual development of these games was undertaken by Deepzone’s development team using the game engine, while the student teams focused on devising strategic go-to-market plans for user growth.

As the project progressed, teams engaged in a product development cycle, employed growth strategies, analyzed user data, and suggested data-driven improvements to enhance their game’s appeal and functionality. Students with advanced knowledge had the chance to implement their recommendations under the Deepzone dev team’s supervision, using technologies like ReactJS and NextJS for front-end, and Python with FastAPI for back-end development.

This project aimed to offer a comprehensive understanding of AI’s role in gaming and marketing, equipping participants with the skills needed for the dynamic digital marketplace. By merging educational theory with practical application, the project sought to foster a new cadre of professionals proficient in technology, game development, and digital marketing, setting the stage for future innovations in the digital landscape.

Through this project, students:

1. Explored the importance of user fission as a growth strategy within the gaming industry.

2. Delved into the transformative role of AI in gaming.

3. Acquired hands-on experience in analyzing user data to extract actionable insights.

4. Crafted and executed robust go-to-market strategies for their chosen IP.

5. Suggested product improvements informed by data, with the opportunity for direct implementation.

Number: 3-6 talented and bright young students who exhibit the following qualities 

Students with the following capabilities were preferred:  

• A strong understanding of the market and culture, with insight into the target customers or being one of the potential customers themselves. 
• A profound passion for gaming, AI, and Web 3 technology stacks. 
• Programming skills are a valuable addition but not a mandatory requirement. 

Students who excel and successfully complete the program were eligible for cash (1000 RMB for the top 1 team) or non-cash rewards (for the top 1 individual). Exceptional participants might also receive offers for paid summer internships, full-time positions, and potentially equity options, depending on their performance and the assessment criteria. 

1. 3-6 students were organized into groups of 2 or 3 and work as a small group, dividing tasks and cooperating to submit one concise report weekly together under the guidance of mentors. 
2. Student teams met with U-Corp Team and Deepzone regularly to share their progress (frequency and time will be decided at the first meeting). 
3. The workload was 6-10 hours per week, and the project will last 6-8 weeks; the specific time schedule was shown in the Timeline table. 

Orientation: March 23 

Regular Meetings with U-Corp & Deepzone: Weekly meetings 

Final Presentation: TBD