Interviews mit Yongwen Dai

We are a collaborative team of five designers with backgrounds in interaction design, UX research, data visualization, and AI systems. Our journey spans across academic research, industry collaborations, and independent projects. Hive AI is the culmination of our shared passion for reimagining how people interact with knowledge. Together, we combine diverse perspectives—blending design thinking, technological innovation, and user-centered approaches—to create systems that support curiosity and critical thinking.

Each of us arrived at design from different paths—some through formal design education, others through engineering, research, and creative exploration. What unites us is a shared curiosity about human behavior and a belief that design can shape more meaningful learning experiences. We were drawn to design because it allows us to solve real problems by creating thoughtful, intuitive systems that empower users.

Our priorities center around three core principles:

User autonomy—designing systems that give users control over their learning journeys.

Clarity in complexity—visualizing information in ways that make it accessible without oversimplifying.

Interdisciplinary thinking—bridging AI, education, and design to create tools that support exploration.

We prototype extensively, blending digital tools like Figma with conceptual sketches and research. Our style emphasizes structured yet flexible interfaces, with a visual language that invites engagement without overwhelming the user.

Designing evokes a sense of creative tension—balancing logic and intuition, structure and freedom. There’s excitement in the early stages of ideation, a sense of challenge during problem-solving, and deep satisfaction when we see ideas come to life in ways that genuinely help users.

Our diverse backgrounds—ranging from AI research and interaction design to visual arts and education—shape how we approach problems. We value empathy, systems thinking, and curiosity. Beyond design skills, we draw from non-design areas like cognitive science, learning theory, and communication. These perspectives help us design for real human needs, not just theoretical models.

Our growth path is centered on expanding Hive AI as a platform that adapts to different learning contexts—whether in education, research, or professional development. We plan to explore partnerships with educators and researchers, refine AI capabilities, and make Hive AI more accessible globally. Our dream project is to build a collaborative knowledge ecosystem where learners worldwide can connect, exchange ideas, and co-create understanding across disciplines.

Stay curious, ask questions, and never stop learning. Don’t be afraid to challenge assumptions, and remember that design is about solving problems for people, not just creating visuals. Be open to feedback, embrace iteration, and take time to develop your voice as a designer. Trust that your perspective matters.

Always design with intention—understand the “why” behind every decision. Collaborate across disciplines, seek out diverse perspectives, and stay grounded in real user needs. Avoid chasing trends blindly; instead, focus on timeless principles like clarity, usability, and ethical responsibility. Great design is not about ego—it’s about impact.

Our day typically begins with team stand-ups where we align on priorities. Mornings are often dedicated to deep work—designing, prototyping, or researching. Afternoons include feedback sessions, testing ideas, and refining solutions. We balance focused design time with collaborative discussions, and always leave space for reflection. Little joys—like a breakthrough on a tricky problem or seeing a prototype resonate with users—make the workday fulfilling.

We stay informed about design trends but don’t follow them blindly. We believe in understanding trends as signals of broader shifts in user behavior and technology, while ensuring our designs align with long-term goals and user needs. Our priority is creating tools that remain relevant and useful, even as trends evolve.

A well-designed product empowers users—it's intuitive, thoughtful, and serves a clear purpose. We define good design as a balance of clarity, functionality, and emotional resonance. It should solve real problems without creating new ones. We ask: Does this design reduce friction? Does it spark curiosity? Does it make users feel capable?

We consider a design ready when it meets user needs, aligns with our goals, and feels cohesive in its flow and purpose. That said, we recognize that no design is ever truly “finished”—there’s always room for improvement. But at some point, we have to release, observe how users engage, and iterate based on feedback. It’s about balancing progress with perfection.

Hive AI is our most ambitious and meaningful project. It challenges traditional learning paradigms and empowers users to build their own knowledge systems. The design process was complex, requiring us to blend AI, interaction design, and educational principles into a cohesive experience. Hive AI embodies our philosophy of designing for curiosity and exploration.

We admire designers who think systemically and ethically—like Dieter Rams for his clarity and timeless principles, and Buckminster Fuller for his visionary approach to systems thinking. Their work reminds us that good design is about improving lives, not just creating products.

We are a globally connected team, working across time zones and cultures. Our design approach is shaped by diverse perspectives—from Eastern philosophy’s emphasis on balance and flow, to Western design traditions of functional minimalism. We value continuous learning, community engagement, and the belief that good design contributes to a more thoughtful, connected world.

Our team culture is collaborative, open-minded, and focused on impact. We believe in clear communication, mutual respect, and shared responsibility. We encourage each other to ask tough questions, challenge assumptions, and stay curious. For us, design is a process of collective problem-solving—where diverse ideas lead to stronger outcomes.

We see Hive AI as a form of giving back—by creating tools that make knowledge more accessible and empower learners to think critically. We also engage in design mentorship, sharing our insights with early-career designers, and contribute to community discussions around ethics, AI, and design for social good.

Participating in the A' Design Award has been an incredible experience that opened doors to a global design community and brought valuable feedback from fellow creatives. It also significantly amplified the visibility of Hive AI. The top benefits we've gained include broader exposure through media and new audiences, validation of our design approach, and fresh inspiration from the diverse range of projects and designers we encountered. We're truly honored to be part of the A' Design Award community and excited about the ongoing growth, connection, and dialogue it continues to inspire.

Hive AI is driven by the belief that learning is nonlinear and deeply personal. Traditional AI learning tools often impose rigid structures, limiting curiosity and autonomy. Hive AI challenges that by creating a system where learners build their own knowledge networks, guided by AI as a facilitator, not an instructor. Our inspiration comes from how neural networks process information—dynamic, flexible, and constantly evolving.

Our primary focus was to empower learners to take ownership of their knowledge journeys. We wanted to create an environment where users could explore ideas organically, make unexpected connections, and visualize their learning in ways that resonate with them. The goal was to make learning both structured and exploratory, blending AI capabilities with human curiosity.

We plan to expand Hive AI’s capabilities—introducing more customizable visualization templates, refining AI-driven recommendations, and integrating with other learning platforms like research databases and online courses. We also aim to make Hive AI accessible to a wider audience by developing multilingual support and mobile-friendly interfaces.

The concept evolved over approximately six months, including ideation, prototyping, user research, and refinement. It’s a product of iterative design cycles and ongoing exploration into AI-driven learning systems.

Hive AI was born from inspiration, not commission. We saw a gap in the way AI was being applied in education—often limited to static Q&A systems. We wanted to explore a new paradigm where AI supports exploratory learning, helping users build knowledge structures tailored to their interests.

We intend to develop and maintain Hive AI as an independent project, but we are open to collaborations with educational institutions, research organizations, and learning platforms that align with our vision.

We are passionate about learning and knowledge systems. This project allowed us to combine our interests in UX design, AI, and education to create a tool that helps people think more deeply, not just memorize facts.

We were inspired by systems thinking pioneers like Donella Meadows, and visualization tools like concept maps and knowledge graphs. While Hive AI is unique in its approach, we stand on the shoulders of many who have explored how people process and organize information.

Our target users are learners—students, professionals, and researchers—who deal with complex, interdisciplinary information. Hive AI supports anyone who wants to connect ideas across fields and build a personalized understanding of their subjects.

Hive AI breaks away from linear learning models by enabling non-linear, node-based exploration. Its unique hexagon knowledge nodes, AI-driven gap detection, and customizable visualizations empower users to build, expand, and reorganize their knowledge in ways that feel intuitive and engaging.

The name "Hive" symbolizes a dynamic, collaborative space where knowledge grows organically—like a beehive. It reflects the interconnectedness of ideas and the continuous, evolving nature of learning.

We used Figma for interface design, Miro for collaborative mapping, and Notion for documentation. For the AI components, we worked with Python frameworks like PyTorch and TensorFlow, and used D3.js for dynamic visualizations.

The most unique feature is the hexagon knowledge node system combined with AI-driven knowledge gap detection. This allows learners to see their knowledge as an interconnected web rather than isolated facts—supporting deep understanding and discovery.

Yes, Hive AI was a collaborative effort between UX designers, AI engineers, educators, and researchers. We worked closely with machine learning experts to ensure the AI recommendations aligned with human cognitive patterns, and with educators to refine the learning experience.

Technology is the enabler—AI powers the recommendations and visualizations, while the interface design ensures usability and engagement. Hive AI wouldn’t exist without advanced machine learning algorithms and interactive visualization tools, but its value lies in how it supports human curiosity.

Absolutely. We conducted field and secondary research on learning sciences, cognitive load theory, and user behaviors in digital learning environments. We also ran user interviews and prototype tests to understand how learners navigate complex topics and what kinds of visualizations aid their understanding.

Balancing complexity and clarity was a major challenge. We wanted to support deep, interconnected learning without overwhelming users. Ensuring that the AI recommendations felt helpful rather than intrusive, and designing intuitive visualizations for abstract concepts, required multiple iterations and close user feedback.

We believed Hive AI represented an innovative approach to AI-assisted learning, and we wanted to share our vision with a broader community. Submitting to A' Design Award was a way to gain feedback, visibility, and inspiration from peers in the design world.

We deepened our understanding of interdisciplinary design—how AI, education, and UX intersect. We also learned the importance of designing for ambiguity: creating systems that adapt to users' evolving needs, rather than forcing them into rigid paths.

Hive AI is more than a tool—it’s a mindset shift. It encourages learners to see knowledge as a living system they can shape, not just passively consume. We hope Hive AI inspires new conversations about the future of learning and the role of design in supporting curiosity.

We come from a background in interactive media and UX design, which naturally led to our interest in human-AI interaction. Our journey into design began with a curiosity about how technology could be reimagined as a companion rather than just a tool. We've always been driven by a desire to create intuitive, exploratory systems that bridge logic and emotion in meaningful ways.

Hive is a collaborative project built by a team of designers and researchers from both academic and industry backgrounds. United by a shared mission, we aim to rethink digital learning environments—creating platforms where AI empowers rather than dictates, and where learners are active authors of their own knowledge journeys.

Design is a conversation between structure and possibility. It’s about creating systems that are both intuitive and empowering—tools that feel natural, yet open doors to new thinking. To me, good design enables autonomy while guiding curiosity, especially in the way people interact with information.

We love to explore and create systems that encourage critical thinking and exploration. Projects like Hive AI—where users are invited to build, question, and evolve their own learning journeys—are where we feel most connected to our work. We're especially drawn to data visualizations and adaptive interfaces that reveal patterns in human thought.

Hive AI is the first project we collaborated on—and naturally, our favorite. It challenges the dominance of traditional AI learning models by inviting users to become architects of their own knowledge systems. Through dynamic data visualizations and AI-supported node mapping, it transforms passive learning into an active, intuitive, and empowering journey.

The first design we contributed to professionally was a multi-layered dashboard for an accessibility-focused health tech platform. It taught us how deeply clarity and empathy matter in interaction design—and how powerful a well-structured interface can be in empowering users.

Notion is our go-to tool thanks to its clean, intuitive interface combined with impressive flexibility and functionality. We frequently use it to embed task boards, calendars, delegated tasks, notes, and databases all in one place. Its adaptability to different workflows, while remaining easy to use and efficient, makes it stand out from other tools we've used.

We feel most creative when we share insights about users, visuals, and tools to shape meaningful, thoughtful design. Together, we explore relationships between abstract concepts—whether through visual systems, speculative frameworks, or collaborative prototyping.

We focus on interaction flow, user autonomy, and visual structure. It’s critical to us that design guides users without dictating their actions. We often ask: Does this interface encourage exploration? Does it reduce friction in thought?

There’s a feeling of synthesis—like we’re distilling chaos into clarity. Sometimes it’s exhilarating, sometimes meditative. Often, it’s a mix of empathy for the user, curiosity about the unknown, and the joy of solving a structural riddle.

When we see our designs come to life, it’s a mix of gratitude, humility, and a deep sense of responsibility. Knowing that our ideas have evolved from abstract concepts into tools that others can use to learn and grow is both humbling and motivating. It’s a reminder that design has the power to shape how people think and interact with the world.

A design is successful when it solves a real problem while empowering the user. Success isn’t just about aesthetics or functionality—it’s about creating something that feels intuitive and meaningful, something that invites curiosity and sparks exploration. In Hive AI, success means enabling learners to make unexpected connections and build their own understanding of complex ideas.

We look at clarity, flexibility, and emotional resonance. A good design feels natural to use, but also leaves space for personal interpretation and growth. We ask: Does it reduce cognitive friction? Does it help users feel capable and in control? If the answer is yes, it’s a good design.

Designers hold the responsibility to create not just for today’s needs, but with awareness of long-term impact. We believe in designing systems that empower individuals without exploiting them—protecting user agency, privacy, and mental well-being. Environmentally, we strive for minimalism in our digital solutions, reducing unnecessary cognitive load and promoting thoughtful engagement.

Design is becoming increasingly interdisciplinary—blurring boundaries between technology, ethics, and human experience. The future of design lies in creating systems that adapt to human needs, not the other way around. AI will play a larger role, but the core of design will remain human: creating meaningful, empowering, and ethical tools for exploration and growth.

Hive AI was invited to participate in the international juried exhibition "Fractured Horizons," presented as part of the NYX-DESIGN Festival in New York City in May 2025. Hive AI will be exhibited at the A' Design Award exhibition in Como, Italy, in July 2025. We'd love to showcase Hive AI at an academic conference focused on AI and education, where it can inspire dialogue among educators, technologists, and learners.

Our inspiration often comes from observing how people learn and make sense of information—whether it’s in a classroom, an online discussion, or a research setting. We also draw from systems thinking, information architecture, and data visualization. Exploring different disciplines fuels our curiosity and helps us imagine new ways of connecting ideas.

Our style is structured yet open-ended—minimalist interfaces that invite exploration. We favor geometric structures, clean visual hierarchies, and interactive systems that grow with the user. This style reflects our belief that learning is a nonlinear, evolving process, and design should mirror that complexity while offering clarity and guidance.

We live in the United States, but our team members bring diverse cultural perspectives, including backgrounds from China and Europe. This diversity enriches our design process—helping us think critically about user needs across different contexts. The U.S. tech culture encourages bold innovation, but we also remain cautious of over-automation and strive to balance efficiency with meaningful engagement.

We collaborate closely with clients and stakeholders to understand their goals, challenges, and audiences. Our approach is iterative—we co-create prototypes, test ideas with users, and refine solutions based on feedback. Communication is key; we see ourselves as partners who bridge user needs and business objectives through thoughtful design.

Companies should look for designers who are not just skilled, but also collaborative and open to feedback. A good designer is curious, asks the right questions, and understands both the user’s perspective and the company’s goals. It’s important to build trust—give the designer space to explore, and listen when they challenge assumptions. Great design happens when there’s mutual respect and shared purpose.

Our process is iterative and exploratory. We start by understanding the problem—talking to users, mapping out information, and identifying pain points. Then we prototype ideas, often starting with low-fidelity sketches and moving into interactive mockups. Throughout, we focus on feedback loops: test, refine, test again. We also prioritize storytelling—every design decision should have a clear rationale that connects back to the user’s goals.

A vintage Braun alarm clock—simple, functional, and timeless.

A mechanical keyboard—its tactile feedback sparks joy during long hours of work.

A handmade ceramic cup from a local artist—organic forms remind us of the human touch in design.

A magnetic whiteboard—an analog space to map thoughts and ideas.

A modular bookshelf—adaptable, functional, and a visual metaphor for how we approach knowledge design.

Our days start with a quiet morning—reading, journaling, or sketching ideas. We usually have team stand-ups to align on priorities, followed by focused design sprints. Afternoons are often for deep work: prototyping, testing, or writing documentation. Evenings are a time to recharge, whether through a workout, cooking, or a long walk to let ideas settle in the background.

Stay curious. Learn to observe—how people think, how systems work, how problems emerge. Don’t be afraid to ask “why” repeatedly. And remember: design is not just about making things look good, it’s about making things work—for real people, in real contexts. Finally, be patient with yourself. Great design takes time.

The positives: you get to shape the world in meaningful ways, solve problems creatively, and make an impact on people’s lives.

The negatives: it can be mentally taxing, especially when facing ambiguity, tight deadlines, or balancing user needs with business constraints. It’s easy to get attached to ideas, so learning to detach and iterate is key.

Design for clarity, not control. Give users space to think, explore, and make their own connections.

Empathy, systems thinking, and communication. A designer needs to understand human behavior, think holistically, and clearly articulate ideas to different audiences. Visual skills and technical proficiency are important, but they are in service of a greater goal: solving the right problems in the right way.

We use Figma for prototyping, Miro for mapping ideas, and Notion for documenting processes. For inspiration, we explore design blogs, academic journals, and systems thinking frameworks. We also sketch by hand—it’s a fast way to think. Books like The Design of Everyday Things and Thinking in Systems have been foundational.

We set clear milestones and embrace the idea of "good enough for now." Time-boxing and regular feedback loops help avoid perfectionism paralysis. We also build in rest—stepping away from a design often brings fresh perspective.

It varies—some ideas crystallize quickly, others need weeks or months of iteration. For Hive AI, the core concept developed over several months, while specific components, like the data visualization templates, took focused sprints of a few weeks each.

People often ask: "How do you balance creativity with usability?" Our answer is: they’re not opposites. A great design is both functional and expressive—creativity enhances usability when it helps users see possibilities they didn’t know existed.

Working on Hive AI has been our most important experience as a team. It’s taught us how to navigate complex, interdisciplinary challenges and collaborate across design, AI, and learning science. It’s also shown us the impact a thoughtful design system can have on empowering users.

Our primary focus has been on Hive AI, an independent project. However, team members have also collaborated with educational platforms, research institutions, and startups focused on AI and knowledge management.

We love creating systems that help people make sense of complexity—whether it’s a knowledge platform, a data visualization, or an adaptive interface. It’s deeply rewarding to turn abstract information into tools that spark curiosity and understanding.

We plan to refine and expand Hive AI—introducing new visualization formats, enhancing AI-driven recommendations, and integrating with more learning platforms. We’re also exploring collaborations with educators and researchers to adapt Hive for different fields, from history to healthcare.

We work as a team—designing is a collective, iterative process. Each member brings different strengths, whether it’s interaction design, research, or technical implementation. Collaboration helps us refine ideas and create more thoughtful, holistic solutions.

We’re currently exploring new AI-driven templates for Hive AI—ways to help learners create their own knowledge maps tailored to different disciplines. For example, visualizing the interconnections between scientific theories or mapping the evolution of cultural movements. We’re excited about the potential to make learning even more intuitive and engaging.

People can reach us through the Hive AI website or our professional email. We’re always open to conversations, collaborations, and new ideas.

We believe design is not just about creating artifacts—it’s about shaping ways of thinking. Hive AI is a manifestation of that philosophy: a space where learning becomes a personal, exploratory, and evolving journey. We hope it inspires others to reimagine how we interact with information and build knowledge together.

The hexagonal knowledge nodes at the heart of Hive AI were inspired by nature’s most efficient and stable structure—the hexagon. This geometric form allows each knowledge unit to connect seamlessly in multiple directions, supporting modular expansion that mirrors the brain’s associative thinking. Unlike linear cards, hexagons form tightly interlinked clusters, enabling learners to explore ideas spatially and thematically. This fosters stronger memory encoding by integrating visual cues, relational mapping, and intuitive grouping, ultimately enhancing cognitive retention and understanding.

Hive AI’s adaptive recommendation system leverages machine learning to analyze content patterns, user behavior, and connection density across the knowledge network. Rather than dictating a fixed learning path, it suggests related nodes or gaps based on cognitive flow. For instance, if two concept clusters remain unconnected, AI may prompt the user with bridging material or inquiries. This supports autonomy by allowing users to accept, ignore, or customize these suggestions—ensuring that learning remains user-led while being intelligently supported.

Our research revealed that 78% of users found existing learning tools too rigid—limiting their ability to connect interdisciplinary ideas or explore beyond pre-structured modules. These insights emerged from user testing with professionals and researchers who often manage complex, layered information. Hive AI was born from the desire to break this constraint. We designed an interface that supports nonlinear exploration: users can begin from any node, navigate organically, and build their own knowledge constellations—mirroring real-world cognition and academic inquiry.

The 3D hexagonal map was developed to help users spatially organize and interpret dense information systems. Inspired by astronomy and molecular structures, this immersive visualization enables users to group, zoom, and rotate their knowledge architecture—providing a multidimensional sense of scope and relation. We also designed templates like flower timelines and radial maps to match different content types—e.g., historical events, thematic clusters, or layered theories—making knowledge not only functional but visually memorable.

To make node-based interaction as intuitive as chat-based AI, we focused heavily on micro-interactions, smooth transitions, and universally understandable icons. Each motion cue was designed to simulate natural thought processes—e.g., node expansion mimics idea blossoming; bridging nodes reflect connections forming between concepts. The iconography is minimal yet distinct, using soft color gradients and intuitive symbols to reduce cognitive friction and keep users emotionally engaged.

One of the most surprising discoveries during testing was users’ desire to “see” their thought structure evolve. Many learners reported satisfaction from observing how their fragmented notes transformed into a visible, interconnected system. This led us to emphasize real-time feedback, automatic grouping suggestions, and transparent AI interactions. Another insight was the strong preference for visual metaphors—timelines, clusters, flowers—which significantly improved recall and conceptual understanding.

In the future, Hive AI aims to integrate even more advanced natural language processing and multimodal inputs—allowing users to speak, sketch, or upload mixed media to form new nodes. We’re also exploring personalized cognitive maps that adapt not just to content needs, but to emotional states and attention spans. As digital learning becomes more decentralized, Hive will serve as a lifelong learning partner—offering adaptive, ethical, and empowering knowledge environments.

Balancing responsiveness with consistency across desktop, tablet, and mobile platforms required a modular design system rooted in grid flexibility. We ensured that the core experience—creating, connecting, and visualizing nodes—remains fluid regardless of screen size. Adaptive interactions, like pinch-to-zoom for 3D maps and gesture-driven timelines, make Hive feel native on any device while maintaining design integrity and user familiarity.

Winning the Silver A’ Design Award validated the direction and ambition of Hive AI as a pioneering knowledge platform. It reinforced our belief in design-led innovation—not just aesthetically, but structurally and cognitively. The recognition encouraged us to double down on features like immersive visualization and AI-augmented grouping, while also inspiring future expansions, collaborations, and a more ambitious roadmap.

Hive AI balances structure with flexibility by letting users build their own mental architecture. The hexagonal nodes create a logical framework, while the freedom to expand, skip, or bridge topics allows nonlinear journeys. This supports diverse cognitive styles—from highly analytical learners who prefer systems and categories, to intuitive thinkers who thrive on fluid exploration. The platform adapts to each user’s rhythm, not the other way around.