Two years ago, I wrote about managing twenty microservices at Qantas with a small team. The problem was keeping services in sync, coordinating changes across system boundaries, fighting the entropy of a codebase that grew faster than our ability to reason about it. Many years before my time, someone had
I’ve read a lot of government reports in my time. Most of them are dry, dusty things that serve as excellent door stops or cures for insomnia. But every now and then, you come across one that tries so hard to polish a specific narrative that the cracks in
I’ve just finished reading Dario Amodei’s latest essay, "The Adolescence of Technology." I must admit, reading it gave me a distinct sense of déjà vu - specifically, the feeling I get when I’m sitting in a strategy workshop with a room full of highly paid
It feels like we are at an inflection point; the capabilities of Large Language Models (LLMs) are extraordinary, offering new ways to synthesize information, automate complex cognitive tasks, and extract insights from vast unstructured datasets. But integrating these stochastic components - these probabilistic black boxes - into systems that demand
[This post originally appeared on the Qantas Engineering Blog] Whilst you might not know “what” Polylith is, I’ll bet that the factors that influenced its adoption as our source architecture — the “why” — will be very familiar. This story explores the driving forces of code changeability, consistency and complexity and
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I've just had a look at the Australian Government’s "National AI Plan 2025" and I'm not surprised. It certainly looks like a strategy. It has vision statements, goals, and nine distinct actions. But look closer, and the familiar emptiness yawns back at you.
There’s a persistent belief in the public sector that if the existing machinery is slow, risk-averse, and fragmented, the solution is to build a new, smaller machine next to it. A "Centre of Excellence," a "Transformation Office," an "Innovation Hub." It’s the
It feels like we are at an inflection point; the capabilities of Large Language Models (LLMs) are extraordinary, offering new ways to synthesize information, automate complex cognitive tasks, and extract insights from vast unstructured datasets. But integrating these stochastic components - these probabilistic black boxes - into systems that demand
I remember sitting in a Gartner Conference workshop around 2013, somewhere in the Sydney. We were talking about "Big Data" and the Australian Public Service. The consultancy partner leading the session, all suit and enthusiasm, declared that data was the "new oil" and that if organisations
I’ve just read the latest Australian Public Service Data Maturity Report... and honestly, it feels like déjà vu. The headline? A system-wide score of 2 out of 5 which Finance optimistically labels as “Developing”. Key areas like Data Architecture, Analytics, and crucially Data Quality & Metadata are stuck at
[This post originally appeared on the Qantas Engineering Blog] Whilst you might not know “what” Polylith is, I’ll bet that the factors that influenced its adoption as our source architecture — the “why” — will be very familiar. This story explores the driving forces of code changeability, consistency and complexity and
