Product executive who builds.

I've spent nine years in the engine room of enterprise B2B SaaS, most recently as Director of Product at Cotality (formerly CoreLogic) where I owned the P&L across an eight-product portfolio and led a 21-person product organisation serving Tier 1 Australian enterprises including CBA, NAB and ANZ.

That portfolio spanned property research (RP Data), consumer growth (OnTheHouse, one of Australia's highest-traffic property portals), AI-powered lead generation (Rita), digital advertising (Plezzel), valuation platforms for brokers and valuers (PropertyHub, ValConnect), and construction project intelligence (Cordell Connect). I led two M&A integrations, built give-to-get lead generation products from zero, and grew organic traffic by 25% through SEO and CRO strategy, establishing GTM as a portfolio-wide discipline.

Alongside the portfolio, I established the company's AI Governance Working Group, delivered its first commercial GenAI integration, scaled from zero to 10 production AI features in a regulated data environment, rebuilt the flagship platform to drive 20% MAU growth and 730% mobile expansion, and reduced churn by more than 30%.

In late 2025, I made a deliberate choice to step out of the enterprise and build. Not to consult. Not to advise. To ship. I wanted to close the gap between the AI strategies I'd been defining at scale and the reality of putting AI systems into production.

The result: two production SaaS platforms (OpenChair and OpenTradie) built end-to-end as a solo operator. 50+ AI features each. Multi-model orchestration across six LLMs. AI voice agents. Eval frameworks. Native mobile apps on the App Store and Play Store. Stripe billing. Real users.

This wasn't a side project. It was a deliberate validation that AI-augmented operators can match full-stack team velocity. I replaced the output of eight specialised roles. Not by working harder, but by architecting systems that leverage AI at every layer of the stack.

What I believe

• Product leaders must build. Leaders who haven't felt latency or been frustrated by hallucinations build strategies on fantasy.
• AI governance is a product discipline. Not a compliance checkbox. The product leader owns the user experience, the unit economics and the deployment risk.
• The best AI products are invisible. The future isn't chatbots. It's multi-agent systems doing background work that users never see.
• Per-seat pricing is an existential threat to SaaS. Variable inference costs demand new commercial models. Price by work units, not logins.