OVERVIEW
Learning AI can be overwhelming, especially when everything starts with long documentation and no clear direction. I designed Google Playground as a space where developers could dive in, explore, and actually do things—without needing to write a single line of code.
This personal project came from something I felt was missing: hands-on experience and a sense of community. So I focused on making the experience more approachable, with personalized onboarding, an interactive Playground, and creator tools that encourage collaboration and discovery.
At the heart of it, my goal was simple: help people feel less intimidated by AI, and more excited to play with it.
This project was submitted to the D&AD New Blood Awards.
CONTRIBUTIONS
Product Design
UX Research
Motion Graphic
DURATION
4 weeks
The Problem
72% of developers say they struggle to learn AI due to complex documentation and lack of hands-on opportunities.
Without interactive tools or real peer support, many developers feel lost, stuck, or discouraged before they even begin.
Current AI learning platforms focus too heavily on theory. They overlook the growing number of learners who want practical experience instead of just reading documentation.
Source: Stack Overflow Developer Survey, 2023
How might we create an interactive, community-focused AI learning experience so developers can easily build practical skills without feeling overwhelmed by complex documentation?
Initial Research
Competitor Analysis
Cloud AI
Research Insights
1. Hands-on Learning Wins
Direct experimentation beats abstract theory in AI learning.
2. Friendly First Steps
Beginners need less intimidating AI tools with clear entry points.
3. Community Boosts Learning
Collaboration and shared knowledge accelerate learning.
4. Adaptable to All
Good AI resources must support all skill levels.
5. Balance is Key
Best AI learning blends hands-on practice, community, and real-world application.
Education AI
Survey and Results
Are developers struggling with AI learning?
Exploring developer challenges, preferences, and the need for more interactive and community-driven AI learning platforms revealed important insights through surveys.
80% of respondents prefer interactive, hands-on learning over video tutorials or documentation.
70% struggle with the lack of hands-on practice and finding real-world use cases
60% believe a community-driven AI learning platform would be helpful, allowing developers to share models and solutions.
User Interview
“Google Cloud AI has amazing capabilities, but new users find it daunting because the learning materials are often complex and overwhelming. It would help if beginners had more practical, step-by-step tutorials and interactive ways to start.”
Google Cloud AI Engineer
Wants a simpler, interactive learning experience to overcome initial barriers.
“I struggle a lot with AI tutorials online because they’re so theoretical. It's frustrating not having a straightforward, hands-on way to test things myself. Learning alone also makes me feel stuck.”
Student Developer
Feels isolated due to the lack of hands-on practice and peer collaboration opportunities.
Persona
Solution
What if AI learning wasn’t a solo journey, but an open playground where knowledge is built, shared, and expanded together?
User Flow
“Use this space to share reviews from customers about the products or services offered.”
User Flow 1 - Beginner
User Flow 2 - Developer
User Flow 3 - Developer
Final Design
Onboarding
Onboarding personalizes your AI journey by matching you with models and projects based on your interests and skill level. Start experimenting or explore guided learning
Home
Home is where your AI journey begins, connecting you with models, projects, and a vibrant community. Explore, experiment, and collaborate to bring your AI ideas to life
Publish Mode
Publish Mode lets you share your AI models with the community, making them accessible for collaboration and feedback. Build, refine, and showcase your work while learning from others
DashBoard
The dashboard gives you a real-time view of your AI model’s performance, user engagement, and feedback. Track key metrics, identify issues, and refine your model for better results.
Conclusion
What I learned
Creating Google Playground showed me how valuable interactive learning and a supportive community truly are. Throughout the project, I realized the importance of understanding real user frustrations and focusing on simplicity and accessibility. Making AI approachable matters, especially for those who feel intimidated by overly technical documentation and complex tools. The process reinforced the significance of human-centered design and taught me how empathy-driven decisions can effectively bridge the gap between technology and users.
What's Next?
I’ll keep improving the platform based on real user feedback and integrate more practical Google Cloud features. I'm also interested in building a mobile version and exploring similar approaches for other tech education topics.