Bypassland
What if an app could help you feel again?
Unpacking Strong Emotions
Imagine someone struggling with intense emotions they don’t fully understand, patterns they’ve carried for years but can’t quite name. Now, imagine giving that person a space where they can unpack those emotions, one layer at a time.
I led the end-to-end product design for an early-stage startup to create an AI-powered emotional processing app based on the Kiloby Inquiry (KI) method, a somatically informed approach that helps people access and release repressed emotions.
Problem
Killoby Inquiries traditionally requires a trained facilitator in a face-to-face interaction. This makes the work expensive, inconsistent, or intimidating, especially for beginners.
Goal
Design an AI-powered app that could educate users about Kiloby Inquiries, guide users through self-facilitated emotional processing sessions, and track psychological patterns over time.
Discover
Research Approach
I used mixed methods to understand both user behavior and the KI practice itself. I analyzed engagement data from KI's existing platform to identify friction points, then used qualitative methods to understand the practice:
Target Audience
Newcomers
Pain Points
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Unsure how to start or what to say to the AI
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Emotional vulnerability without a human guide
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Lack of motivation or clarity about progress
Opportunities
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Provide suggested first messages for emotional processing sessions to make getting started easier
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Offer reassurance and education in friendly tone
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Use gamification to encourage progress
Seasoned Practitioners
Pain Points
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Difficulty maintaining a regular practice alone
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Stagnation, feeling like sessions are repetitive
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May feel dependent on a facilitator
Opportunities
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Let users revisit psychological patterns they discovered during emotional processing sessions
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Summaries, insights, and progress tracking
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Build self-confidence to reduce reliance on facilitators
define
Core Challenges
Traditional AI chat interfaces require thinking and verbalizing. This pulls users away from their direct, emotional experience. Conversational UIs also come with structural limitations. Unlike spatial GUIs, conversations are linear and offer little guidance about what the system can do. I designed a hybrid interface combining conversational and GUI elements based on these core challenges:
How do we make users feel safe doing emotionally sensitive work with an AI?
Emphasize privacy, add an always-available emotional regulation button, and offer access to community and mentors.
How do we reduce the need for typing and verbalization?
Let users begin sessions with one-tap prompts, use affordances to reduce cognitive load, and support text-to-speech.
How do we turn an abstract inner process into actionable UI?
Let users “capture” psychological and emotional patterns as interactive UI elements they can reflect on and build upon.
How do we onboard users into a complex method like KI without overwhelming them?
Create short, spaced-out lessons, introduce complex topics later, and use gamification to boost learning motivation.
User Journey
The user journey was made to reflect the arc of an in-person KI session, but adapted into an interactive digital experience that supports the depth of a face-to-face session.
developing
Early Versions
We initially explored a journal-based approach where users would write and highlight experiences before AI-guided inquiry. After testing proved our AI agent could reliably facilitate the process, we pivoted to a conversational interface.
Dashboard Overview
The design emphasizes calmness, clarity, and ease of use. All colors used in the app meet WCAG accessibility contrast standards, and the iconography is sourced from Phosphor Icons. The DM Sans typeface was used for UI elements to ensure modern readability, while Lora was chosen for chat text to evoke a grounded, human tone.
The First Message
I designed emotionally-aware "entry ramps" - one-click prompts reflecting different psychological states. Users can begin sessions without articulating anything upfront, reducing startup friction."
The Session Screen
This is where most of the emotional work happens. The AI agent gently guides the user through the steps of Kiloby Inquiries, responding to typed or spoken input. Along the way, it can offer helpful affordances such as tools and prompts, which are covered in the next section of this case study.
In-Chat Affordances
These are elements that appear in the conversation to support the user’s process. They reduce friction, offer gentle guidance, and help maintain emotional presence by minimizing the need for typing or decision-making.
Snackbars
Displays notifications without taking up space inside the chat.
Meditation / Rest
Starts a meditation or guided breathing process to regulate the nervous system or ground the user before a session.
Meta Utilities
Text-to-speech, copy, and flag response. They increase user agency without blocking the flow.
Tooltips
KI concepts appear underlined when mentioned by the AI. Hovering reveals definitions.
Educational System
Because users may be unfamiliar with Kiloby Inquiries, the app needed an educational system to teach its core principles. The system draws from self-determination theory, spiral learning, and competency-based models.
"Learn KI" Dashboard
The educational section blends prewritten content with responsive AI, providing structure while maintaining adaptability. Each lesson begins with a scripted AI message containing fixed definitions and examples for consistency across users, then transitions to an open conversation where the AI can answer questions, provide additional examples, or help users explore the topic further.
Users can access a dedicated learning dashboard that shows their current rank (e.g., Apprentice), their next lesson, and a progression path that follows the already established KI curriculum.
Gamification
Drawing from the Octalysis Framework, the goal was to apply motivational psychology in a way that made difficult inner work feel accessible, sustainable, and worth returning to.
Visual map of the Octalysis Framework applied to Bypassland’s feature set.
I created a full gamification strategy brief on our shared Notion workspace that mapped each feature to motivational psychology using the Octalysis Framework. It served as an internal reference for aligning product, design, and development decisions.
deliver
Impact
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Built 4 interrelated systems: chat session framework, contextual learning interface, pattern-tracking tools, and a gamification system.
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Delivered a full development-ready design with scalable UX architecture.
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Received strong validation from stakeholders, including KI facilitators and product owners.
Vision for the Future
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Gather more user data to refine how and when the AI introduces guidance or tools.
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Build an adaptive ramp system that adjusts to user history or current emotional state.
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Expand features like "WeSpace," the social reflection area, and "The Net," a system for tracking recurring psychological patterns and breakthroughs.
To be continued…
More Experimentation is Required
User behavior and LLM responses are unpredictable. Entry ramps, pacing strategies, and affordances require continuous real-world testing and iteration based on actual usage patterns.
Data is Crucial
Observing user behavior in AI-guided sessions is essential for future iterations. Empathetic UX design requires listening, not assuming. Data will reveal new patterns and opportunities for better flows.
