Independent applied AI practice for growing businesses and professional teams · Sydney
I help businesses find valuable ways to use AI — improving important workflows, building useful products and creating better ways to get complex work done.
Where I can be useful
The opportunity might be a valuable workflow, a new product idea, underused AI tools, better research and decision-making, or work that has only recently become practical. The focus is on finding meaningful upside and making it concrete.
A repeated professional workflow could become faster, easier to scale or more effective.
A team wants to turn ad-hoc use of tools like ChatGPT or Claude into reliable ways of working.
A useful product, service or internal capability that was previously too expensive or difficult to build can now be tested.
A business sees the potential of AI but has not yet identified where it would create the most value.
Research, reporting or decision-making could become substantially faster without losing evidence or judgement.
An AI-enabled workflow or product needs stronger evidence, checks, usability or operating discipline before it becomes part of real work.
How I work
The default is bottom-up. Start with a real task, the person doing it, the evidence they use and the result they need. Work hands-on, test what actually helps and build outward from there. A broader product, operating or strategic view may follow, but it should be grounded in what the work reveals rather than imposed in advance.
Understand the work, decision, evidence, users and desired result.
Decide where AI adds value and where ordinary software, process or human judgement is better.
Make the idea concrete enough to test properly.
Test the result against sources, edge cases, behaviour and usability, then document what matters.
Proof of capability
SmallCap Atlas is a source-led research platform I built using AI-native development and research methods. It now covers 777 companies — effectively the entire population of ASX-listed small-cap natural-resources companies — and maps more than 3,000 associated projects.
It’s an example of what becomes practical when current AI, software, structured evidence and human judgement are designed together.
Explore SmallCap AtlasA little about me
My background spans business-critical technology in financial markets, engineering, risk and extensive hands-on work with current AI. I’m comfortable entering ambiguous situations, understanding the work quickly and making ideas concrete enough to test.
That includes almost nine years working directly with front-office users: understanding loosely expressed needs, turning them into working systems and supporting business-critical technology in live financial markets, where reliability mattered.
Access to AI is common; fluency is not. I work across frontier models, browser-based AI, coding agents and lightweight tools, combining them with ordinary software and explicit checks where reliability matters.
Credentials MBA · Master’s in Civil Engineering · Chemical Engineering (Hons) · Financial Risk Manager · Risk and AI Certificate
Start a conversation
Bring a problem, idea, opportunity or workflow that may be worth improving. A short initial conversation can clarify what is happening and whether I might be useful.
The first piece of paid work is deliberately bounded and shaped around the situation. It might be a working session, a workflow or tool setup, or a short sprint to investigate and test an opportunity.