TIFFANY CARRELL

Rethinking AI Education:
‍Anthropic Case Study

Anthropic logo image

Stop teaching AI. Start designing for curiosity.

I designed and built a strategic framework for a learning ecosystem that rethinks how people build intuition with AI. Created as part of a final-round design challenge with Anthropic, the project moved beyond tutorials and feature lists to design an experience that fuels exploration and emotional engagement in addition to comprehension.

My goal was to spark those “wait... can it really do that?” moments that trigger deeper understanding. Instead of teaching prompts or prescribing behaviors, it invited users to explore, question, and connect insights back to their own work.

Why It Matters

This project revealed how brittle education is when it treats learning as content delivery. Most systems over-index on accuracy and completeness while ignoring curiosity as the driver of fluency.

What actually builds fluency is structured curiosity... experiences that encourage experimentation, surprise, and shared meaning-making. So, I treated AI learning as a relationship to be built instead of a manual to be memorized. The model reframed learning as humans and machines figuring things out together, moving toward the confidence and mindset shifts that sustain real adoption.

The Challenge

How might we transform AI education from a linear sequence of tutorials into a curiosity-driven journey of discovery? The approach had to balance wonder with grounding in order to honor the learner’s instincts while guiding them toward meaningful, real-world experimentation.

The Big Idea

Traditional onboarding depends on tooltips, checklists, one-size-fits-all experiences, and scripted walkthroughs. This project proposed a living system where learning is sparked by emotion, shaped by cultural context, and sustained through exploration. I anchored on the core belief that curiosity is infrastructure.

My Role

This was a one-day solo sprint for Anthropic’s final-round brief. I treated it as a 24-hour design challenge: define the strategy, shape the narrative, build the prototype, and capture the system behind it.

I owned every layer: research, UX, voice and tone, copy, prototyping, content modeling, and site build. While it was a solo execution, my default mode is collaborative; this just happened to be a closed-loop experiment.

Guiding Principles

Curiosity > Comprehension : Exploration precedes explanation. Learning lands deeper when discovery comes first.
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Human-Centered, Culturally Rooted : Personas modeled around emotional drivers, cognitive patterns, and team dynamics.
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Scaffolded Mastery : Progression anchored in confidence instead of arbitrary “levels.” The system grows with the learner, not ahead of them.
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Collective Learning + Solo Tutorials : Design for individuals AND for teams as dynamic learning organisms. Shared discovery creates momentum.

Deliverables

Concept documentation + full project framework

Emotional and cultural audience insights

Three behavioral personas (Victoria, Maya, Sasha) representing distinct mental models

“First Contact” prototype experiment for early-stage exploration

Sample content: blog post, podcast script, social campaign, education and UX copy

Advanced prototype walkthrough scripts for scaffolded expertise

MCP Walkthrough for non-technical users

Scaffolded journey map for deepening expertise

Voice and Tone documentation tailored for AI learning contexts

End-to-end project capture and site build
A screenshot of an interaction with Claude AI
Contact Me

I'm excited to keep diving into:

Team learning dynamics and cultural adoption frameworks

Building systems that transform how teams relate to each other and to AI.

‍Predictive learning models and adaptive pathways

Designing experiences that respond to users in real time, surfacing just-right challenges and moments of delight.

‍Rituals of discovery that deepen human-AI collaboration

Shaping practices that turn interaction into relationship and novelty into trust.

Collective intelligence as an emergent design force

Not just "designing for users" but designing with them, in feedback loops that learn as fast as they do.

Learning as sense-making in complex systems

Reframing education as a tool for navigating ambiguity and for transferring knowledge.

Speculative prototyping as pedagogy

Using what could be as a way to rewire how we think, feel, and engage with technology.
Copyright Ⓒ 2025 Tiffany Carrell ♡ All rights reserved.