My father farmed in Carinthia, Austria, and I grew up working alongside him. He was not a man of many words. When he did speak, it was measured, the kind of thing worth sitting with rather than answering. I was not particularly good at sitting with things. Two generations of men on a farm: we had the stubbornness in common, not the patience.

One thought stayed with me: that we were not owners of the land but custodians for a generation, obliged to hand it back better than we found it. Soil depleted by one generation becomes a liability for the next. Varieties lost cannot be recovered. Knowledge not passed on disappears. He never liked monocultures, and chipped away at alternatives steadily rather than making radical changes. My instinct would have been to reject the whole model outright, go further and faster at the time. His approach turned out to be the more long-term sustainable.

A few months ago, I wrote about the growing graveyard of “smart” home devices, expensive bits of plastic and silicon that turned into bricks the moment a corporate server in Virginia or San Francisco was switched off. It’s a personal annoyance when your $300 security hub stops talking to your lightbulbs. Scale that logic up to national defence and critical infrastructure, and the stakes shift from a darkened living room to a crippled nation.

Six months ago I pulled a local language model onto my laptop. Took about 12 minutes with Ollama. No account, no API key, no data leaving the machine. It felt like a small act of sovereignty, exactly the kind of local-first approach I’d been arguing for.

Then I started using it. And I noticed something.

The model’s cultural centre of gravity was somewhere around San Francisco, circa 2022. Ask it about food systems and it defaulted to commodity agriculture and supermarket supply chains. Ask it about community governance and it reached for American municipal frameworks. Ask it about traditional land management and it gave me a careful, earnest summary that read like it had been assembled from university anthropology papers, not from anyone who had actually grown anything, or sat with the country long enough to know it.

In 2020, journalists asked Australian police forces whether they were using Clearview AI, the American company that scraped three billion social media photos without consent to build a facial recognition database. The answer, from several state forces and the AFP, was no.

Then Clearview suffered a data breach. The stolen customer list included Australian law enforcement agencies. At that point, the denials stopped.

That sequence (quiet adoption, public denial, disclosure only under external pressure) is the pattern. Last week I wrote about the cultural conditions that make it possible: the institutional trust, the “she’ll be right” pragmatism, the absence of organised civil liberties infrastructure that might have generated friction. This post is the inventory. Here is what Australia has actually built, layer by layer, and what you can do about it.

Every few months, Australia’s business press discovers a new emergency. Right now it’s the capital gains tax. According to the usual commentators, founders, VCs, and their aligned media, Labor’s move to replace the 50% CGT discount with inflation-adjusted indexation is an act of vandalism against Australian ingenuity. Entrepreneurs will flee. Talent will dry up. The unicorns won’t come.

I’ve been working in and around Australian agtech and startups for the better part of two decades. I’ve watched the same arguments recycled through every policy debate: the R&D tax credit, the ESVCLP scheme, the startup visa. The answer is always the same: give us more upside, or we’ll take our toys elsewhere.

A few days ago I was listening to an episode of It Could Happen Here, Cooper Quintin and Colonel Panic from the EFF walking through the American surveillance state. Flock cameras on every corner. Cell site simulators at protests. Facial recognition with no accountability, built on databases scraped from your social media without asking. PenLink buying location data harvested from your phone’s apps and selling it to law enforcement, no warrant required, because it came from advertising networks instead of a phone carrier.

I’ve spent 30 years watching tech cycles come and go, from the first dial-up modems in rural Austria to the mesh networks I’m currently stringing across the Australian bush. Each time a “next big thing” arrives, we see the same pattern: a frantic rush to centralise, followed by a slow, painful enclosure of what should have been a common resource.

The current noise around AI in open source feels different. It feels heavier. There’s a justified fear that AI-generated code is hollowing out our commons. Maintainers are being buried under a drift of unvetted, mediocre pull requests, while a handful of platform monopolies strip-mine decades of community work to feed their proprietary black boxes.

I’m tired. Not the kind of tired that a good night’s sleep or a weekend off the grid can fix. It’s a deeper, more pervasive exhaustion, the fatigue of living in a culture of relentless, performative positivity. In the tech world, we’re told to “crush it,” to “move fast,” and to embrace every new “game-changer” with uncritical enthusiasm. If you’re not a believer, you’re a “naysayer” or, worse, a “blocker” of progress.

Over the past few weeks, I’ve pulled apart four different LPWAN mesh technologies. Now it’s time to bring those findings together and look at which tool fits which job on the property or in the community.

There is no “perfect” protocol. What we have is a set of tools with different trade-offs. I’ve evaluated all four across five parameters to help cut through the marketing noise and get to the technical reality.

In an emergency, information is as vital as water. The official advice is clear: “leave early.” But how do you act on that advice when the power is out, the mobile network is congested to the point of failure, and the emergency broadcaster’s tower has been consumed by the very fire you’re trying to flee?

This isn’t a hypothetical. As Fiannuala Morgan chillingly documented in her article, “No power, no phone, no radio: why comms dropped out during the Central Victorian fires{target="_blank”}", this is the reality for communities across Australia. The wholesale replacement of resilient copper landlines with power-dependent NBN connections, coupled with the shutdown of the 3G network, has created a communications infrastructure that is dangerously brittle in the face of climate-fuelled disasters.

We live in an era where a reliable connection to the digital world is not a luxury, but a lifeline. It’s how we work, learn, access essential services, and connect with our communities. Yet for many in regional and rural Australia, this lifeline is frayed, unreliable, or simply non-existent. We’ve been told to accept a digital landscape dominated by a handful of corporate giants, a landscape where postcodes dictate the quality of our connection to the modern world. But what if there’s another way?

In the first two posts of this series, we explored the risks of corporate-controlled IoT, from devices being turned into ‘bricks’ to the sustainability challenges facing ‘open-source alternatives’. But what if the bigger danger isn’t just that your smart device will stop working, but that it’s working all too well, just not for you? This post dives into the pervasive, built-in surveillance that has become a standard feature in so-called ‘smart’ devices.