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Insights to impact

I lead teams to de-risk complex problems early through rapid validation and data-driven iteration.

Whether navigating 0 to 1 discovery or optimising mature enterprise systems, I bridge the gap

between user needs and technical feasibility to build products that scale.

Discovery
Define
ideate
Prototype
Validate
Delivery

Discovery &  Ideation

I move teams from opinion based decisions to evidence backed decisions. Through deep discovery, I investigate user needs and business constraints to define a clear strategy. This ensures that we validate the right problem before opening a design tool, aligning stakeholders around a shared vision of success.

Methods I lean on
  • Assumption mapping to expose hidden risk
  • Qualitative research to understand motivation, not just behaviour
  • Collaborative workshops to align cross-functional teams around evidence
Tools
  • Miro for rapid synthesis and alignment
  • Figma for early problem framing, not polish

Prototyping & Validation

I use rapid prototyping to force early decisions, expose risk, and align teams before code is written. I validate these concepts with real users to de-risk the product, ensuring that what is committed to code is proven to deliver value.

Methods I lean on
  • Rapid prototyping to explore and compare directions
  • User testing focused on behaviour and comprehension
  • Iterative refinement based on validated learning
Tools
  • Figma for fast iteration and testing
  • AI tools to accelerate exploration, synthesis, and iteration where speed matters most

Delivery & Scale

I partner closely with engineering during delivery, ensuring intent is preserved through detailed specifications. Beyond the immediate feature, I build robust design systems that allow the product to scale, reducing technical debt and accelerating future development.

Methods I lean on
  • Clear design specs and collaboration with engineering
  • System-level thinking across flows, components, and states
  • Post-launch measurement to close the loop between intent, usage, and outcomes.
Tools
  • Figma for scalable component libraries and documentation and iteration
  • Google Analytics, Datadog, Grafana, Power BI (usage, performance, and outcome metrics)