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@systemsnotsilos
Principal AI Engineers Are Not Building Models. They're Building Systems.
One line in a recent Principal AI Engineer job advertisement stood out to me:âIdeally youâre a software engineer first, ML engineer second.âThat single statement captures one of the biggest shifts happening in AI engineering right now.For years, many organisations treated AI as a research problem.Build a model. Run experiments. Create a proof of concept. Present some impressive metrics.ThenâŚ
Representing QUT at the CSIRO NGGP Showcase 2026: Research, Collaboration, and Learning Across Disciplines
Most Engineers Talk About Code. The Best Engineers Talk About What Happens When Production Fails.
One thing I have learned over the years is that senior engineering is rarely about writing the âperfectâ code. It is about making good decisions when systems become unstable, integrations fail, customers are affected, and the business waits for answers. That is why so many technical interviews today are moving away from textbook questions and focusing more on realistic engineeringâŚ
What Mining, Logistics, and Industrial Systems Taught Me About Real Software Architecture
Over the years, one thing became very clear to me: The hardest engineering problems are usually not about code. They are about operational trust. In industries like logistics, transport, mining, warehousing, aviation, and industrial operations, the real challenge is often this: âHow do we make systems reliable enough that people trust operational decisions based on them?â A delayed telemetryâŚ
The Resume Arms Race Is Breaking Hiring, Not Fixing It
Over the past few weeks, I have been reflecting on something uncomfortable happening across the technology hiring market. Not AI itself.Not ATS platforms alone.Not even recruiters. The real problem is what happens when everybody stops trusting everybody else. I recently applied for a senior leadership role at a well-known technology company. The recruiter came back saying my ATS score wasâŚ
AI Automation Is Not About Prompts. It Is About Fixing Operational Friction.
One thing has become increasingly clear to me recently: The companies getting real value from AI are usually not the ones chasing hype. They are the ones fixing operational friction. A lot of current AI discussions still revolve around:⢠prompts⢠models⢠agents⢠frameworks⢠tooling stacks But inside real businesses, especially across logistics, SaaS, enterprise systems, and operationalâŚ