The #OMN path is about the stories we tell to make technology acceptable, the institutions that repeat those stories, and the grassroots work left waiting while the money follows the next “miracle” story. A useful tool gets wrapped in a grand narrative, funding follows the narrative rather than community need, and the people building alternatives are pushed to the margins. When the story finally weakens, the underlying technology may remain – but the promised social transformation never arrives.
The story is always bigger than the technology, and when the story collapses, the people trying to build something useful are left to compost the mess. The AI hype is beginning to meet this reality that caught up with so many previous waves of technology. The promises were enormous: artificial general intelligence, automated abundance, the end of work as we know it, and machines that would solve the problems we have failed to solve ourselves. Trillions in investment followed the story.
But beneath the #PR claims the practical uses remain much more ordinary. Large language models (#LLM) do have useful capabilities. But they are not evidence that we have created a new form of human intelligence, nor do they justify meany of the promises made in their name. The interesting question is not whether the technology has some value, it clearly does. The question is why we keep wrapping useful tools in stories of technological salvation, and why so much of our social and political life gets pulled into those stories.
Every technology comes with a story, we have seen this cycle meany times. The #dotcons, social media promised to connect the world. #Web3 promised to decentralize it. #Blockchain promised to rebuild trust. Now #AI promises to automate intelligence itself. Each wave arrives with a familiar script, first, a genuine technical development, then a much bigger story about what it means for humanity. Blinded investors pour in money, bureaucratic businesses scramble to adopt it, governments fear being left behind, and the traditional media repeats the promise until it starts to feel like transentery common sense.
The technology becomes almost impossible to discuss outside its mythology, is how the #deathcult works, it turns a economic and political path into an inevitable dead end future. We are told to adapt, adopt and accelerate, because questioning the direction means falling behind. But as always, the question of who benefits disappears beneath the pressure to keep up. To compost this mess we need to separate what the technology can actually do from the stories being sold around it, as if we accept the industry’s framing that today’s language models are becoming digital people, even our criticism ends up strengthening that framing. The task is to compost the mythology, the failed dreams of #mainstreaming.
But we face is what happens when the story’s collapse, who pays? The AI industry sold different stories to different audiences. Consumers were promised an intelligent assistant. Businesses were promised efficiency and reduced labour costs. Governments were warned that they must join a geopolitical race. Workers were told they were participating in a historic mission. Investors were promised extraordinary returns. These stories reinforced one another. Government investment legitimized the industry. Corporate adoption made it appear inevitable. Financial speculation funded further expansion. Media attention turned uncertainty into spectacle.
And when this investment bubble deflates, the damage will not be limited to shareholders. Public resources have been committed to speculative infrastructure. Workers have lost jobs in anticipation of automation that never delivered as promised. Communities may be left with more centralized infrastructure and less control over the information systems they depend on. Yes, the technology will continue in some form, the question is more who ends up owning it, who benefits from it and who is left holding the bill.
There are are likely useful things we can do with language models. They can help people process information, translate material, assist with coding and make some technical tasks more accessible. We should assess those uses honestly, including their limitations and costs. But we do not need to pretend these tools will create a new civilization, we do not need to build our communities around corporate #dotcons products, by handing over public knowledge to private platforms to replace human judgement with automated output.
We do need to ask what tools can contribute to collective work, and what relationships must remain human, accountable and open to challenge. For #OMN, this means keeping our focus on shared media flows, grassroots publishing, archives and the commons. The work is to help communities create, discover, moderate and maintain their own information systems. On this path the #4opens offer a practical test: open data, open source, open standards and open processes. These do not magically guarantee a good outcome, but they make it easier to inspect, reuse, challenge and improve the systems we build.
The #AI story needs compost, not another hype cycle. There is a useful ecological metaphor here, composting does not mean pretending that everything discarded is worthless. It means separating what can nourish future growth from what needs to break down. The AI boom contains technical developments, useful tools, accumulated knowledge and some worthwhile experiments. It also contains inflated promises, speculative finance, extractive business models and a great deal of #techchurn.
That means, focus, shifting our attention away from chasing the next big story and towards the less glamorous work of building things people actually use. Shared infrastructure. Open processes. Community maintenance. Human trust. The ability to disagree, adapt and walk away. This work will not attract the same speculative billions. It may never produce a spectacular demonstration or a promise of god-like intelligence. Good.
We need less technological theatre and more collective capability, less dependency and more participation, less worship of the #deathcult and more practice of the #lifecult. The AI bubble will deflate, or the industry may keep finding new ways to keep the story alive. Either way, the underlying choice remains, do we build alternatives or keep chasing the next #mainstreaming day dream, or maybe better, do we practically use the wreckage of these failed promises to grow something more useful?
The #OMN path is to compost the hype, keep the useful tools, expose the power relationships and build the commons. Not one perfect platform, not one miracle technology, a living ecosystem of tools, communities and shared practices that grow beyond the control of the #dotcons.
There is no magic, there is only work.








