Four months ago, someone lost their job. Now they’re staring at job listings showing 1,746 applications and wondering if they’ll ever hear back. Meanwhile, their mortgage repayments are about to get squeezed by another interest rate rise. It’s a scenario that’s playing out across Australia right now, and honestly, it’s both more complicated and less dire than those numbers suggest.

I’ve been thinking about this a lot lately, partly because I work in IT and DevOps where the job market has become particularly weird, and partly because those application numbers are genuinely bonkers. But here’s the thing that emerged from a discussion I saw recently: those numbers are essentially meaningless.

I’ve been thinking a lot lately about what numbers mean to us. Not in a mathematical sense, but in that psychological way where certain figures become cultural markers. You know, like how $1 million used to be the definition of wealth, or how $100,000 was once the salary that meant you’d “made it.”

That second one particularly interests me because I’ve been watching it lose its lustre in real-time. Someone online recently pointed out that the median full-time salary in Australia is now sitting just over $104,500. Let that sink in for a moment. The median – meaning half of all full-time workers earn more than this. A hundred grand isn’t aspirational anymore; it’s literally average.

I’ve been watching the conversation around Seedance 2.0’s Matrix recreation unfold online, and I’ll admit – this one’s got me thinking. For the first time in a while, I’m genuinely caught between being impressed and slightly unsettled by how far AI video generation has come.

The demo shows Neo fighting Agent Smith in what’s essentially an AI-generated action sequence, and it’s… good. Actually, scratch that – it’s surprisingly good. The physics feel right, the choreography flows, and the whole thing maintains a level of consistency that would’ve seemed impossible just a year ago. Someone pointed out that the sunglasses help mask the eye rendering issues that usually plague these systems, which is a clever observation. But there’s more to it than just hiding the weak spots.

There’s a running joke in the Type 1 diabetes community that’s been going strong for at least two decades: “Don’t worry, a cure is just five years away!” It’s become such a reliable punchline that you could set your watch by it, except the watch never actually reaches zero.

So when I saw headlines about Stanford scientists curing Type 1 diabetes in mice—quickly followed by similar news from China—my immediate reaction was somewhere between cautious optimism and weary cynicism. The comments section on one discussion thread captured this perfectly, with someone who’s lived with T1 for 48 years wryly noting they’ve been hearing about that five-year timeline their entire adult life.

There’s something deeply unsettling about watching the future of medicine being built behind closed doors. I’ve been following the discussion around Isomorphic Labs’ latest protein folding AI – what people are calling “AlphaFold 4” – and the conversation has taken a turn that’s worth unpacking.

For those not familiar with the backstory, DeepMind’s AlphaFold 2 was a genuinely revolutionary moment in computational biology. It cracked the protein folding problem that had stumped scientists for decades, and they open-sourced it. The entire scientific community could access it, build on it, and use it to advance drug discovery. It felt like one of those rare moments where cutting-edge AI was actually being developed for humanity rather than at it.

There’s a discussion bubbling away online about whether our major supermarkets are using “meat glue” to piece together steaks from offcuts. Someone posted a video of their eye fillet falling apart in the pan, and naturally, the internet did what it does best: jumped to the most dramatic conclusion possible.

Look, I get it. The relationship between Australian consumers and Colesworth has become increasingly strained. When you’re paying premium prices for what should be quality products, only to have them fall short of expectations, suspicion is a natural response. But sometimes a dodgy steak is just a dodgy steak, not evidence of a grand conspiracy.

I came across a post the other day that stopped me mid-scroll. Someone had stayed up all night cleaning their room – something they hadn’t properly tackled in years – and they were buzzing with pride about it. Their sister had helped move furniture, and the transformation had them feeling like a weight had been lifted off their shoulders.

There’s something deeply relatable about that feeling, isn’t there? We’ve all been there – that moment when you finally tackle the thing you’ve been avoiding, and suddenly you can breathe again.

There’s a photo doing the rounds comparing the West Gate Freeway approach in 2004 versus today, and honestly, it’s sparked some interesting reflections about what we’ve actually achieved in two decades of infrastructure development. The punchline? Still just four lanes heading onto the Bridge itself, even with all the fancy new tunnel work.

Now, before anyone jumps down my throat, I’m not saying the West Gate Tunnel project was a complete waste. Far from it, actually. But there’s something deeply frustrating about spending billions on infrastructure that, at its core, still has the same fundamental bottleneck it had twenty years ago.

I’ve been following the age verification debate for a while now, and honestly, every time I think it can’t get more dystopian, something new comes along to prove me wrong. This week’s revelation about Persona – the age verification vendor that’s been exposed for running what essentially amounts to a comprehensive surveillance operation – is both shocking and entirely predictable.

For those who haven’t heard, researchers discovered that Persona’s system doesn’t just verify your age. Oh no, that would be far too reasonable. Instead, it performs 269 distinct verification checks, runs facial recognition against watchlists and politically exposed persons, screens “adverse media” across 14 categories including terrorism and espionage, and assigns risk and similarity scores. They collect and can retain for up to three years your IP addresses, browser fingerprints, device fingerprints, government ID numbers, phone numbers, names, faces, and a whole battery of “selfie” analytics.

There’s something deeply absurd about watching billionaire CEOs throw tantrums over YouTube reviews. Yet here we are in 2026, and apparently Elon Musk has decided to give tech YouTuber Marques Brownlee (MKBHD) the silent treatment because he sold his Cybertruck and preferred a Rivian instead.

Let me get this straight: a company worth over a trillion dollars is ghosting one of the most influential tech reviewers on the planet because he exercised consumer choice. The pettiness is almost impressive in its scale.