SAMBA

SAMBA

Translating behavioral research into an AI driven product concept

Industry

Education · Productivity · AI

Duration

2 Months Thesis - 1 Month Project

Tools

Figma · Framer · Research interviews · UX frameworks

SAMBA is an AI-powered product concept designed to help students manage academic workload, reduce procrastination, and stay focused across studies and daily life.


The project explored how AI can support attention management by centralizing tasks, deadlines, and learning materials into one intelligent system. My focus was on defining the problem space, validating user needs, and designing a clear, scalable product experience.

The Challenge

Students struggle with procrastination and stress due to cognitive overload, fragmented tools, and difficulty breaking large academic tasks into actionable steps — especially under time pressure and during peak semester periods.

The Approach

Most students struggle not with completing tasks, but with starting them, often due to fear of failure or feeling overwhelmed.

  • Once a first step is taken students are significantly more likely to maintain momentum and follow through.

  • Large, undefined tasks increase avoidance, while clear, bite, sized actions reduce anxiety and cognitive load.

  • 50% struggle with task-switching

  • 83% report peak stress at semester deadlines

The Result

  • Grounded design decisions in qualitative interviews and surveys

  • Identified emotional and cognitive blockers behind procrastination

  • Translated research into clear product principles

  • Designed an AI system that supports users without overwhelming them

  • Prioritized trust, clarity, and control over automation hype

SOLUTION OVERVIEW

SAMBA is an AI-powered task management system that helps students:


  • Break down complex academic information into manageable tasks

  • Reduce cognitive overload by structuring work early

  • Receive gentle, non-intrusive guidance instead of pressure


The system focuses on early intervention, helping users avoid end-of-semester stress by creating clarity at the start.

CORE FEATURE: AI TASK BREAKDOWN

Feature Highlight AI-powered syllabus parsing

  • Users upload course material

  • AI extracts deadlines, milestones, and tasks

  • Users retain control to edit, adjust, and confirm

UX Rationale

  • Reduces activation energy

  • Supports trust in AI through transparency

  • Aligns with research on task initiation and emotional regulation

CORE FEATURE: FOCUS & PRIORITIZATION

Feature Highlight Daily focus mode

  • AI-prioritized tasks with time estimates

  • One-task-at-a-time structure

  • Optional focus music and timers

UX Rationale

  • Supports flow state

  • Reduces task-switching fatigue

  • Helps users feel progress instead of pressure

DESIGN PRINCIPLES

  • Minimal by default, customizable when needed

  • Calm, predictable interactions

  • Clear hierarchy and spacing to reduce overwhelm

  • Neuroinclusive UI patterns

  • AI as a support system, not a controller

OUTCOMES & LEARNINGS 

Key Learnings

  • Emotional friction is as important as usability

  • AI systems require clear feedback and user control to build trust

  • Simplicity outperforms feature richness for stressed users

  • Designing for neurodiverse users improves usability for everyone

  • Product thinking benefits from combining UX research with system design

Final Remarks

SAMBA is a conceptual product developed as part of a Master’s thesis, designed to explore how AI can responsibly support focus, task management, and mental well-being. The project demonstrates my ability to translate research into product strategy, design scalable systems, and apply UX thinking to complex, emotionally driven problem spaces.

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