A recent essay on deadSimpleTech makes a point the #openweb community should hear: the biggest problem in technology is not only the tools, it’s also the culture behind them. For years the tech world has operated under a form of “tech empiricism”: the belief that if something produces results quickly, then it must be working well. In this mindset, success is measured by novelty, speed of production, and the ability to create something new. The heroes of this culture are disruptors and iconoclasts who ship fast and build shiny things that capture #fashionista attention.
But this basic #geekproblem ignores a simple #KISS truth: technology only has meaning inside the culture that builds and maintains it. And this is where the real problem begins. In the dominant tech worldview, the culture rewards novelty, disruption, rapid production, and personal prestige. Inside this environment of #deathcult worship, producing new code becomes a way to gain status among peers. Shipping quickly matters more than maintaining systems or improving what already exists.
But there is another culture that exists alongside this, the culture of engineering and maintenance. In fields like civil engineering or infrastructure design, the heroes are not disruptors. They are the people who quietly maintain systems, improve reliability, and prevent failures. The emphasis is on responsibility, long-term stability, and care for systems people depend on. This difference in culture matters enormously. Because what counts as something working “well” depends entirely on what the culture values.
From the perspective of blinded tech culture, a tool that generates lots of new code and features appears incredibly successful. But from the perspective of infrastructure and engineering culture, that same tool may look deeply flawed – even dangerous. Real systems require debugging, maintenance, testing, and institutional memory. Most importantly, they require people who accept responsibility when things fail.
In mature systems, the first prototype is only the beginning. The real work comes later: years of maintenance, improvement, and adaptation. Yet this long-term work is largely invisible in tech culture and funding systems, which celebrate the person who creates something new but rarely honour the people who keep it running. This cultural blindness leads to fragile systems and recurring cycles of hype and #techshit to compost.
The same problem is in the #OpenWeb. Unfortunately, this problem is not limited to Silicon Valley, it also appears inside the #openweb, #NGO, and #FOSS ecosystems. Many conversations focus almost entirely on: code, protocols, scaling, features and UX. All of these are important, but without balance they are not enough to sustain a functioning ecosystem.
Without the native social culture that originally shaped the open web, open technology slowly drifts toward the dominant norms of the wider #dotcons tech industry of status competition, short-term innovation cycles, neglect of maintenance and eventual capture by institutions or corporations. This is one reason so many promising #openweb projects stagnate or collapse.
The technology works, but the social infrastructure fails. It’s in part why the #OMN exists as a project. This is the gap we need to address, not primarily as technical project. Most of the protocols and software already exist. What is missing is the social infrastructure that allows them to function as a public commons. Instead of focusing only on building new non-native platforms, the #OMN focuses on growing the wider ecosystem around what all ready works.
This means recognising that the real value of a network comes from the people who maintain it, moderate it and build communities around it – not just from the code itself.
From tech “empiricism” to social infrastructure, if we want the #openweb reboot to succeed, we need to move beyond the narrow mindset that treats technology as purely technical. The lesson from history is simple, code builds systems, culture makes them work. Without a healthy culture, even the best open technologies will eventually fail or be captured by more powerful institutions.
A deeper mess is “The End of Theory”, tech empiricism problem is really the #geekproblem amplified by ideas like this, the claim that massive data sets make traditional scientific thinking unnecessary. This idea, popularised by Chris Anderson, suggests that with enough data we no longer need theories, models, or human understanding. But this is a dangerously narrow view as large data models are epistemologically weaker than scientific theories. They can recognise patterns, but they do not understand them.
This becomes even more problematic in the age of opaque and unexplainable #AI systems. Deep learning models can be efficient at pattern recognition, but they lack human comprehension and produce opaque but believable outputs. At the same time, the increasing “datafication” of society means that communication and public life on the #dotcons platforms are moderated by these same algorithms. These systems prioritise engagement and behavioural prediction over needed values like: accuracy, truth, democratic deliberation. The result is a social environment driven by metrics rather than meaning.
It is past time to compost the mess as it is becoming easier and easier to see. But seeing the problem is only the first step. The next step is to compost it – to take the failures of the current system and use them as nutrients for something better. The future of the #openweb will not be decided by better code alone. It will be decided by whether we build the social infrastructure to support it. That is the work the #OMN is trying to grow.
If this work matters to you, help support it.














