There’s something deeply frustrating about watching your perfectly good clothes slowly transform into dingy, yellowed versions of their former selves. I came across a discussion recently where someone was dealing with exactly this problem – their white shirts had turned an unpleasant shade of rust-orange, and their blue Carhartt looked like it had been through a dust storm. The culprit? Well water with high iron content.

Living in the suburbs of Melbourne, most of us are blessed (or perhaps sometimes cursed) with city water that’s been treated and regulated to within an inch of its life. But for those on well water, particularly in rural areas, the chemistry of what comes out of your tap can be a whole different beast. This poor person had a water softener and an arsenic treatment system, yet their laundry was still coming out looking like it had been dipped in rust.

There’s something both predictable and oddly satisfying about watching certain parts of Melbourne turn into temporary waterways during a good storm. This week, Whiteman Street near Southbank became a rather impressive creek, complete with a tram dutifully ploughing through in the background like nothing was amiss. Someone cleverly watermarked their flood photo with “Murdoch Media” which gave me a proper chuckle – though I’ll admit it took me a moment to get the pun.

I’ve been watching something unsettling unfold over the past few months, and it’s finally reached the point where I need to talk about it. The ID verification demands are getting ridiculous.

YouTube wants it. Facebook wants it. LinkedIn is asking for it. Even platforms that used to pride themselves on being relatively hands-off are starting to implement these requirements. We’re watching the last remnants of anonymous—or even pseudonymous—internet interaction being stripped away, one platform at a time.

There’s a story doing the rounds that perfectly encapsulates everything that frustrates me about the current intersection of AI hype, security theatre, and policing in America. A teenager was swarmed by eight police officers with guns drawn at his school. His crime? Having a bag of Doritos in his pocket that an AI-powered camera system flagged as a weapon.

Let me repeat that: a bag of chips was mistaken for a gun by artificial intelligence, and the response was to point multiple firearms at a child.

I recently stumbled across a blog post from someone who’s been self-hosting for thirteen years, documenting their journey to what they consider their ideal setup: OpenSUSE MicroOS with Podman. It’s a fascinating read, but what really caught my attention wasn’t the technical stack itself – it was the discussion it sparked about complexity and what that even means in our world of DIY infrastructure.

One commenter absolutely nailed it: “There’s some major self-delusion involved in any self-hoster when they say their DIY stack is ’low complexity’. Let’s be honest, nobody else knows wth we did in there. We all build arcane rat’s nests and then go ‘isn’t that beautiful?’”

There’s something deeply satisfying about tearing apart a black box and figuring out what makes it tick. It’s the same urge that drove me to pull apart computers as a teenager (much to my parents’ horror) and what keeps me engaged in my DevOps work today. But lately, I’ve been watching the AI agent space with a mixture of fascination and frustration.

I came across someone’s journey of learning AI agents from scratch, and it resonated with me on so many levels. They spent months wrestling with frameworks like LangChain and CrewAI, following tutorials that worked but never explained why they worked. When things broke, they were completely lost. Sound familiar?

There’s a particular kind of déjà vu that hits you when you work in IT long enough in Australia. It’s that moment when you read about an executive “shaking things up” at a major company, only to discover they’re actually just the same person who was shaking things up at their competitor six months ago. This week’s episode: Optus replacing their departing CIO with an ex-Telstra CIO.

Mark Potter is heading out after four years at Optus, and in comes someone from the very company they’re supposed to be competing against. The reaction online has been… well, let’s just say the cynicism is palpable, and honestly, I get it.

I came across an interesting discussion the other day that really struck a chord with me. Someone had recently doubled their income from $600 to $1,200 a week and was wondering if saving $300 weekly was enough to bother investing. The question itself highlights something I’ve been thinking about for years – how our perception of “enough” can either empower or paralyze us when it comes to financial decisions.

Here’s the thing that really got me: $300 a week isn’t just “something” – it’s $15,600 a year. That’s roughly equivalent to a second-hand car, or a decent chunk of a house deposit over time, or quite frankly, peace of mind. Yet there’s this pervasive feeling among people on lower and middle incomes that unless you’re throwing around tens of thousands at a time, you’re not really “investing.” That’s absolute rubbish, and it’s a mindset that keeps people stuck.

I’ve been following the AI hardware race pretty closely—comes with the territory when you work in IT—but I’ll admit the latest announcement about StarCloud planning to launch GPUs into space had me doing a double-take over my morning latte. The idea of a 4-kilometre-wide, 5-gigawatt datacenter orbiting Earth sounds like something straight out of a sci-fi novel, and honestly, I’m not entirely convinced it’s anything more than that.

Let me be clear from the start: this isn’t actually NVIDIA launching GPUs into space, despite what the initial buzz suggested. StarCloud is a startup that’s part of NVIDIA’s Inception program, which is essentially a support network for companies building on NVIDIA tech. The distinction matters because it shifts this from “tech giant’s ambitious project” to “startup’s moonshot pitch,” and those two things have very different probabilities of success.

There’s been some noise online about Amazon’s plans to replace 600,000 workers with robots by 2027, supposedly saving 30 cents per item. On the surface, it sounds like one of those efficiency wins that corporate types love to brag about in quarterly earnings calls. But dig a little deeper, and it’s just another chapter in the story of late-stage capitalism eating itself.

Let me be clear: I’m not a Luddite. I work in IT and DevOps, I’m fascinated by technological advancement, and I’ve spent enough time automating workflows to understand the appeal of efficiency. But there’s something deeply unsettling about the way we’re approaching this particular wave of automation.