What I did
- AI-synthesised discovery: used Claude to analyse a macro-dataset of social signals (LinkedIn, Reddit, X, Instagram, YouTube comments) on habit formation in the UK market, mapping user intent against failure rates and root causes of abandonment.
- Validation & user psychology: synthesised the social data alongside primary qualitative interviews to identify four core friction points in traditional tracking — unclear goals, ambiguous execution steps, overwhelming goal size, and loss of meaning over time.
- UX architecture: mapped infrastructure and feature requirements with Gemini and Claude as strategic brainstorming partners, grounded in 'Atomic Habits' and the SMART framework.
- Figma UI iteration: crafted high-fidelity minimalist interfaces, then fed screenshots back to Claude to stress-test layouts against diverse user stories.
- Prompt engineering: designed the AI prompting logic that translates broad user ambitions into customised, highly structured SMART micro-habits.
- Shipped the MVP end to end with Lovable, demonstrating how AI prompting plus foundational product frameworks can compress the 0-to-1 discovery lifecycle.
Inside the product
home.png
set-goal.png
onboarding.png
project-note.txt
This page is deliberately short-form — quick to read, linked to the real thing. When a piece of work deserves full context, challenge, findings and reflection, it lives in the case studies instead.