As Lead Product Designer at Brain in Hand, I led a multi-year initiative to transform how users access value within our digital support system.

Our goal was simple but critical:

Help users reach meaningful support quickly, with minimal cognitive effort, in a way that aligns with our person-centred coaching framework.

This case study describes how we redesigned Brain in Hand’s content model, improved early-stage value, introduced personalisation, and laid foundations for a future AI-driven recommendation engine.

The story

  • Brain in Hand supports neurodivergent individuals, particularly those with anxiety, ADHD, autism, PTSD and other conditions that can make task initiation difficult. Yet our original content structure made it harder, not easier, for users to engage.

    The previous system required users to:

    • Understand a complex hierarchy (events → activities → problems → solutions)

    • Create a significant amount of content before any value could be realised

    • Navigate unfamiliar terminology (“problem”, “solution”, “activity”) that often felt negative or clinically loaded

    For many users already struggling with overwhelm or initiation, this resulted in:

    • avoidance

    • delayed engagement until a coaching session

    • or complete disengagement from the product

    From a business perspective, this meant users weren’t experiencing the value proposition we communicated through our “coach in your pocket” positioning. Our coaching approach is person-centred and reflective but the product did not yet embody this.

    To succeed, we needed to dramatically reduce cognitive load, align the digital experience with our coaching philosophy, and help users access helpful content immediately.

  • We began by collaborating with a psychological care expert to create Solution Packs - ready-made sets of helpful strategies for common needs such as:

    • anxiety

    • overwhelm

    • task initiation

    • planning

    Our core UX principle was:
    get the user to the most meaningful, relevant solution as quickly as possible.

    These packs served two purposes:

    1. Immediate value: Users no longer had to create content from scratch.

    2. Demonstration effect: Packs acted as examples of what “good” content looked like, helping users understand the concept more intuitively.

    This was a foundation, not the final destination, but it allowed us to quickly validate whether shifting to a simpler, solution-centred model would ease early engagement.

  • We released the MVP and monitored real-world use through:

    • Diary studies, conducted by our research team, giving long-term behavioural insights

    • Continuous discovery using ProdPad, collecting user feedback and organising it into themes

    What we learned:

    • The packs helped users get started - a major improvement.

    • But… they still felt generic, and therefore sometimes patronising.

    • Users wanted content that felt personal, relevant, and reflective of their life and language.

    A core insight emerged:
    personal relevance dramatically changes the perceived tone of a suggestion.
    Even simple strategies (e.g., “step outside for fresh air”) feel patronising only when they are not relevant to the moment. When they are relevant, they feel supportive and empowering.

    Our MVP solved the “blank slate” problem, but it didn’t yet fully align with our person-centred coaching approach or build enough personal meaning.

  • To address this, we introduced the ability for users to create their own packs.

    Key design shifts:

    • A flat content structure where solutions are modular and can exist in multiple packs

    • Users can create collections of strategies that reflect their context, their language, and their needs

    • Ready-made packs offer inspiration; user-created packs build ownership

    This approach mirrored the essence of person-centred coaching:
    we meet the user where they are, using their terminology, their experiences, and their goals.

    The product experience became far more flexible and personal, providing a clearer bridge between the digital app and the coaching delivered by our human coaches.

  • We are now migrating users from the old model to the new and expanding what’s possible:

    A richer content ecosystem

    The new structure supports:

    • larger, more varied content libraries

    • more specific, situational strategies

    • better search and filtering

    • higher contextual relevance

    Exploring deeper personalisation

    With the structural foundations in place, we can now explore richer contextual signals such as:

    • mood trends

    • geolocation

    • weather

    • time-based patterns

    • what content has previously helped the user

    This moves us closer to our vision of giving users the right content at the right time with minimal effort on their part.

  • From the outset, we designed this transformation to be future-proof and AI-compatible.

    Our long-term vision includes:

    • a learning recommendation engine

    • natural language powered suggestions

    • increasingly accurate ability to surface what is helpful right now

    Crucially, this vision was designed with non-medical regulatory safety in mind.

    We ensure:

    • suggestions do not cross into clinical advice

    • recommendations are risk-assessed, supportive, and optional

    • the product remains a coaching support tool, not a medical device

    This creates a strong competitive advantage while staying true to our safeguarding responsibilities.

  • The redesigned content model now aligns directly with our coaching philosophy:

    Plan

    Users discover, adapt, and create strategies that fit their unique situations.

    Act

    They can access relevant strategies effortlessly, right when they need them.

    Reflect

    Reflection tools help capture what they used, how helpful it was, and the mood or context at the time.

    Progress

    Users can see patterns, improvements, and coaching insights, supported by both their coach and the product.

    This creates a coherent experience across the entire service and strengthens our “coach in your pocket” value proposition.

  • Through this multi-layered redesign, we:

    • reduced cognitive load

    • accelerated early-stage value

    • aligned the digital product with our person-centred coaching approach

    • established a scalable, flexible content model

    • created the foundation for future AI-powered personalisation

    This work sets the stage for Brain in Hand to deliver increasingly powerful, context-aware support that helps users get the right solution at the right time, effortlessly.

  • As Lead Product Designer at Brain in Hand, I led the end-to-end redesign of our content model and value-delivery experience. This work required a balance of hands-on interaction design, research leadership, and strategic alignment across, product, engineering, and coaching teams.

    Key responsibilities included:

    • User Research Leadership
      I designed and conducted a large-scale Jobs-to-Be-Done research programme, interviewing users and non-users to understand their real-world behaviours and unmet needs. These insights became the foundation for our content strategy and early-value approach.

    • Collaborating with Clinical Experts
      I partnered closely with a psychological care specialist to co-create the MVP Solution Packs, ensuring they were clinically sound while remaining accessible, empathetic, and rooted in person-centred coaching principles.

    • Content Model & Interaction Design
      I redesigned the entire content structure: simplifying the mental model, flattening hierarchies, and creating a flexible system for ready-made and user-generated content.
      I worked closely with developers throughout this process to understand technical possibilities and limitations, ensuring the new structure was both scalable and technically feasible.

    • Cross-functional Alignment
      I facilitated workshops and decision-making sessions with product managers, engineers, coaches, and marketing to ensure the digital experience fully reflected our “coach in your pocket” proposition and aligned with our Plan → Act → Reflect → Progress coaching framework.

    • Prototyping & User Testing
      I produced low- to high-fidelity prototypes and conducted iterative user testing to validate how personalisation, tone of voice, and content relevance influenced engagement and perceived helpfulness.

    • Vision & Strategy
      I co-developed the long-term product vision for a contextual, AI-enabled recommendation engine. This included defining the safe and ethical parameters for AI use, ensuring we supported user behaviour without entering medical-device territory.

    • Continuous Discovery & Insight Synthesis
      Working with our research team, I interpreted diary studies and continuous feedback (via ProdPad) to evaluate how the MVP performed in the real world and to identify where deeper personalisation and contextual awareness were needed.

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