Choosing contraception is a personal and private decision, but today’s information landscape isn’t built for that. Australians face a scattered mix of clinical pages, advocacy sites and growing social media misinformation. Our goal was to give Australians a safe, unbiased place to learn about and explore their contraception options.

I led co-design across product, legal, engineering and content, and ran a multi-audience research program with consumers, GPs and peak bodies. Research insights and continued co-design informed our UX strategy, high-fidelity clickable prototypes, user stories, validation activities and a prioritised feature list with shortlisted fast-follows.

CDFPay is Flexischools' white-labelled school-fees product for a Melbourne Catholic diocese. Most of its 52-step onboarding runs backstage, and knowledge of how it worked was scattered across process maps, decks and two separate factbases, so when a sync double billed parents, no one could isolate the fail point.

Driving this solo, I designed an AI-centric workflow: Claude Cowork scripting into FigJam over MCP, with Rovo and Copilot validating inputs against factbases, transcripts and HubSpot tickets, and stakeholder proofing feeding back in.

DIT had years of reusable IP from bespoke client work and wanted to commercialise it. But enterprise deals kept stalling at IT risk and compliance review, and internally there was a capability gap on product strategy, CVP, and platform UX.

As their strategic design partner I defined the CVP, shaped the product strategy and designed a platform vision they could anchor to.

Cartology had grown to ~$500m in annual turnover, but the engine under the hood was largely manual. No self-serve platform, no component library. The business was capped at high-touch enterprise clients.

I led the product team through a pivot from a manual service model to a design-led product strategy, consolidating systems and setting the rituals to lift quality and cadence across multiple squads.

Social Boost had launched in 2016 and then stalled. Manual processes, out-of-the-box targeting, bare-minimum development. Meanwhile a new generation of homeowners and smarter competitor tools moved the market on, and leadership wouldn’t fund a rebuild until the value was proven across a series of stage gates.

We cleared the stage gates first to unlock investment, then spent two years hardening the core: an ML recommender model, new reporting, new ad formats, tiered pricing, and an automated Salesforce backend.