Problems solved. Systems designed. Lessons carried forward.
Specific problems, product directions, operating methods, and lessons—without employer names, platform names, delivery labels, or confidential detail.
Built from real problems.
Turning AI curiosity into a one-month builder programme
A complete path from everyday frustrations to structured ideas, working prototypes, fair evaluation, and handover.
Designing a governed AI access layer—not another chatbot
A product strategy for matching users and tasks to approved AI capabilities inside explicit boundaries for data, quality, cost, and accountability.
Turning image generation into a controlled production workflow
A human-in-the-loop studio concept connecting product intake, generation, targeted correction, quality review, approval, and asset lineage.
Moving from prompts to controlled agents
A practical framework for deciding when work needs a prompt, assistant, automation, or agent—and what controls each requires.
Product directions grounded in practical experience.
These concepts show how I would frame and design the opportunity without tying the idea to a specific employer or implementation.
Designing a calmer planning workspace for full-price retail teams
An idea for bringing range intent, commercial context, team decisions, and launch readiness into one understandable planning journey.
Designing a shopping concierge that can discover, explain, and act safely
A multimodal product concept spanning conversational discovery, outfit building, service, loyalty, visual search, and optional voice.
Building customer intelligence around decisions, not dashboards
A decision-led frame for identity, RFM, cohorts, omnichannel behaviour, returns-adjusted value, and actionable audiences.
Translating human shopping language into controlled product discovery
A governed enrichment pipeline that converts need, occasion, style, and slang into validated catalog attributes for search.
Combining behavioural evidence with human creative standards
An advisory review system that explains creative observations, shows evidence, and preserves expert override.
A product operating system for building with AI without losing control
A documentation-first method for using AI collaborators across planning, implementation, testing, security, and handover.