Field notes.
Writing from the work: strategy, systems, delivery, and risk in regulated Australian enterprises.
- risk
CPS 230 is not a compliance project
APRA's operational resilience standard is written as an outcome, not a checklist. Treating it as paperwork produces paperwork; treating it as an engineering problem produces resilience.
- strategy
Where AI earns its place
Boards are not short of AI ambition or use-case lists. The missing artefact is a fundable path: a prioritised view of where AI earns its place, what it costs to run properly, and the governance that makes it defensible.
- build
Your AI is only as good as your data platform
Model quality has a ceiling, and it isn't the model. Lineage, access, and ownership, the unglamorous disciplines of the data platform, decide whether AI can be trusted at scale.
- optimise
FinOps when the regulator is watching
In a regulated enterprise, some of your most expensive architecture exists because a regulator expects it. Cost discipline starts with knowing which dollars are the floor and which are waste.
- optimise
What an AI interaction costs
AI spend has reached board level, but total spend is the wrong number to govern. The unit a board can actually manage is the cost of an interaction, measured honestly, governance premium included.
- strategy
Agentic AI, without the hype
An agent that acts is not a chat interface; it is an operational actor with access, permissions, and failure modes. Where agents earn their place in a regulated enterprise.
- risk
Why your board still can't see its technology risk
Cyber gets agenda time. AI gets a working group. The digital estate underneath them, where operational risk actually accumulates, appears on no agenda at all. That is a visibility problem, and boards can fix it.
- strategy
Fragmented systems are a competitive disadvantage your competitors can see
From the inside, fragmentation feels like history: every system had a reason. From the outside it reads as slow quotes, inconsistent service, and offers that arrive late. Customers feel it. Competitors count on it.
- strategy
The data question your board should be asking
Not "are we doing something with AI" but "which of our critical decisions run on data we trust, and which only look like they do." One question separates the data-driven enterprise from the data-decorated one.
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