Marius Schober

Progress Through Consciousness

  • Steckt Deutschland in einer Klarheitskrise?

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    8 min read

    Über die vergangenen Monate habe ich mit einer Vielzahl an Unternehmern und Geschäftsführern gesprochen. Ausgangspunkt meiner Gespräche war eine tiefe Überzeugung, die sich seit Dezember 2024 mit jedem Tag weiter vertieft: Je unübersichtlicher die Welt wird und je schneller sich technologische, politische, wirtschaftliche, gesellschaftliche Bedingungen verändern, desto größer wird die Wichtigkeit und Bedeutung von Change Leadership.

    Donald Trump ist das wohl sichtbarste Symbol für eine Welt, die schneller, komplexer und fragiler wird. Er ist aber nicht die Ursache und scheint mir, für viele, als der Sündenbock. Denn: auch ohne ihn zerfällt die blinde Berechenbarkeit. Geopolitische Machtinteressen treten wieder an die Stelle zuvor neutralerer Märkte. Staaten ordnen in diesem Zuge Lieferketten, Technologiezugang und Kapitalströme zunehmend nach nationalen Interessen. Gleichzeitig verschieben offensichtliche demographische Entwicklungen die Arbeitsmärkte, den Konsum, öffentliche Finanzen und auch politische Prioritäten. Nationale Volkswirtschaften wachsen kaum noch, und dort wo sie Wachstum ausweisen, muss man genauer hinsehen: Wie viel davon ist kreditfinanziert, politisch erzeugt, statistisch geglättet oder auf wenige überbewertete Bereiche konzentriert? Mit Künstlicher Intelligenz entwickelt sich jedoch zeitgleich eine Technologie exponentiell, die relativ zeitnah Intelligenz zu einem Standardprodukt machen wird, welches – wie Elektrizität oder Internet –für einige Hundert Euro im Monat abonniert werden kann. KI ist hierbei nicht eine einzelne, abgeschottete Technologie, sondern sie beschleunigt auch die Forschung und Entwicklung zahlreicher weiterer exponentieller Technologien: Robotik, Materialentwicklung, Medizin, Energie und auch industrielle Produktion.

    Diese enorme Komplexität führt zu einer Frage, die mir deutsche Geschäftsführer in unterschiedlichen Formulierungen immer wieder stellen: Was ist die nächste Krise – und wie überlebe ich sie? Das führt zu einem Paradox: Change Leadership – das heißt Führung und echte Transformation – wird wichtiger als je zuvor, doch Investitionen in diese Entwicklung sind zugleich immer schwerer zu rechtfertigen.

    Kaum ein Unternehmer oder Geschäftsführer plant noch damit, dass politische Reformen rechtzeitig kommen. Bis sich Energie, Regulierung, Steuern, Arbeitskosten oder Bürokratie vielleicht verbessern, muss das Unternehmen weiter existieren. Es muss verkaufen, entwickeln, produzieren, liefern, finanzieren, Mitarbeiter bezahlen und gleichzeitig seine Wettbewerbsfähigkeit gegen Unternehmen behaupten, die genau hier unter völlig anderen Bedingungen arbeiten.

    Zeitgleich befinden sich Unternehmen in einem technologischen Wettlauf, dem sie sich nicht entziehen können. Wenn das verfügbare Kapital begrenzt ist, wohin soll es fließen? In Führung? In Kultur? In die langfristig-strategische Entwicklung des Unternehmens? Oder in Automatisierung, künstliche Intelligenz und Prozesse, deren wirtschaftlicher Nutzen sich leichter versprechen lässt?

    Die Antwort des Marktes ist eindeutig: KI und Automatisierung erhalten das Budget. Das scheint auch rational, denn sie versprechen Effizienz, geringere Kosten, höhere Geschwindigkeit und häufig gleich noch die Transformation der Organisation. Change Leadership, also die Transformation von Führung und der Organisation, erscheinen im Vergleich langsam, indirekt und schwer messbar. Die Wirkung von Change Leadership lässt sich nicht mit einer Garantie versprechen und führt nicht kurzfristig in eingesparte Stellen oder zusätzlichen Aufträgen.

    Dieses Paradox wird die nächsten Jahren entscheidend prägen: Je größer die Notwendigkeit guter Führung wird, desto uninvestierbarer wird Führung als eigenständige Kategorie.

    Viele Geschäftsführer wissen, dass ihr Unternehmen mit besserer Führung, klaren Verantwortlichkeiten und Rollen, einer stärkeren Kultur und einer klaren Strategie besser auf kommende Krisen vorbereitet wären. Einige sagen dies offen, aber in Summe betrachtet investieren nur wenige entsprechend. Der Grund scheint offensichtlich: unter gegenwärtigen Bedingungen sind Investitionen in Transformation und Leadership kaum gegenüber unmittelbareren Maßnahmen vertretbar.

    Wenn Aufträge zurückgehen, muss der Vertrieb gestärkt werden. Wenn Marge unter Druck gerät, müssen Kosten gesenkt werden. Wenn Mitarbeiter fehlen, muss automatisiert werden. Wenn erste Wettbewerber künstliche Intelligenz einführen, kann das eigene Unternehmen das nicht ignorieren und zurückfallen.

    All diese Entscheidungen sind nachvollziehbar und viele auch notwendig. Das paradoxe Problem ist jedoch: in Summe können diese Prioritäten in die falsche Richtung führen.

    Bevor nämlich der Vertrieb für eine gewisse Produktkategorie gestärkt wird, muss sich gefragt werden, ob diese Produktkategorie in Zukunft überhaupt noch relevant sein wird. Bevor Prozesse automatisiert werden, muss klar sein, ob diese Prozesse in Zukunft überhaupt noch benötigt werden. Bevor ein Unternehmen effizienter wird, muss es erst wissen, welche Organisation es künftig sein will. Genau hier fehlt vielen Unternehmen Klarheit, exakt diese Entscheidungen werden aktuell häufig übersprungen.

    Das Risiko ist, dass KI nicht zur Transformation wird, sondern Ersatz für Transformation. Sie verbessert das Bestehende, bevor das Bestehende grundsätzlich auf strategische Berechtigung überprüft wurde. Prozesse in Geschäfts- oder Produktionsbereichen werden optimiert, die eigentlich vielleicht beerdigt werden müssten. Man reduziert Kosten in Geschäftsmodellen, dessen Relevanz bereits begonnen hat abzunehmen. Man investiert also in Aktivität, messbare Projekte und scheinbaren Fortschritt, ohne die eigentlich wichtigste und zugleich schwierigste Frage zu beantworten: Wofür soll dieses Unternehmen in Zukunft existieren?

    Von 2016 bis 2022 war es die Nullzinspolitik die wirtschaftlich schwache Geschäftsmodelle lange am Leben gehalten hat, indem sie deren Kapitalkosten unnatürlich niedrig gehalten hat. Künstliche Intelligenz könnte eine ähnliche Wirkung entfalten, indem sie nicht das Kapital verbilligt, sondern ermöglicht das Falsche, länger, günstiger und professioneller fortzuführen.

    Unabhängig davon, ob ein Unternehmen in KI investiert oder Ressourcen dem Überlebenskampf widmet, das Problem ist, es wird alloziert, bevor Klarheit herrscht; über Vision, Strategie und Zukunftsrelevanz.

    Klarheit entsteht jedoch erst, wenn ein Eigentümer, die Gesellschafter oder der Geschäftsführer das operative Geschehen für einen Moment verlassen und die Veränderungen außerhalb der eigenen Branchen-Bubble verstehen; und daraus eine Richtungsentscheidung für das Unternehmen ableiten. Welche globalen, technologischen, politischen und gesellschaftlichen Entwicklungen bedrohen das bestehende Geschäftsmodell? Welche eröffnen neue Möglichkeiten? Welche Produkte, Märkte und Fähigkeiten haben noch eine Zukunft? Wo muss investiert und was muss aufgebaut werden? Und – Via Negativa – noch viel wichtiger: was muss beendet werden?

    In den vergangenen Monaten habe ich mit einer Vielzahl an deutschen Unternehmern und Geschäftsführern zum Thema Führung und Transformation gesprochen. Change Leadership als Kategorie sieht das zentrale Problem in der menschlichen Komponente und der Kultur, nicht in der Technologie oder den Prozessen. Das halte ich nach wie vor für richtig, jedoch auch für ebenso unvollständig.

    In der heutigen Zeit struktureller Veränderungen geht es im ersten Schritt nicht mehr darum, Organisationen mittels Change Leadership zu transformieren; also vor allem durch inspirierende Visionen, klaren Rollen, besserer Kommunikation und geschicktem Change Management. Selbstverständlich darf ein CEO nicht im Tagesgeschäft untergehen, aber – aktuell mehr denn je – können Geschäftsführer und deren Gesellschafter die Entscheidung über die Zukunft des Unternehmens nicht an seine Führungskräfte, Berater oder künstliche Intelligenz delegieren.

    Führung bedeutet nicht nur Verantwortung zu übertragen, sondern auch die richtige Verantwortung wieder selbst zu übernehmen. Führung bedeutet – im ersten Schritt – Klarheit: eine unübersichtliche Realität zu einem klaren Bild zu verdichten um daraus eine Richtung zu wählen, in welche das Unternehmen geführt wird. Erst diese Klarheit und die damit einhergehenden möglicherweise unbequemen Entscheidungen, auf Ebene der Geschäftsführung und Eigentümer, sind die Basis für eine Vision, eine Strategie und jegliche Change Initiativen.

    Genau diese Klarheit und diese Fähigkeit fehlt Deutschland nicht nur in vielen Unternehmen sondern dem Land als Ganzem.

    Deutschlands primäre Krise ist deshalb auch keine isolierte Energie-, Bürokratie-, Technologie-, oder Wachtsumskrise. Für jede dieser Krisen sind drastische Reformen überfällig – doch dahinter liegt eine viel tiefere Krise: Deutschland besitzt keine ausreichende Klarheit darüber, was es unter den neuen globalen Bedingungen werden will.

    Wofür soll Deutschland in Zukunft stehen? Was soll in diesem Land enstehen? Worin will ein Hochlohnland mit alternder Bevölkerung und hohen regulatorischen Kosten global wirtschaftlich überlegen sein? Welche industrielle Rolle will es in einer Welt spielen, in der China über Skalierung und Geschwindigkeit verfügt, die USA über Kapital, geopolitische Macht und Technologie- und KI-Plattformen und andere Regionen über deutliche niedrigere Kosten und Bürokratie?

    Darauf gibt es keine überzeugende kollektive Antwort – die Tendencia scheint: regionale Militärmacht. Aber sind wir uns wirklich klar darüber?

    Deutschland fehlt es nicht an Substanz. Wir besitzen technische Fähigkeiten, haben starke industrielle Cluster, der eigentümergeführte Mittelstand besitzt noch immer produktive Vermögenswerte und hat Rücklagen, die kaum eine andere Volkswirtschaft in einem so hohen Niveau besitzt.

    Was fehlt ist Klarheit, was aus dieser Substanz werden soll.

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  • Change

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    5 min read

    We are in times, where leadership matters more, but investments into leadership slowly become uninvestable – unless it leaves the category. The world is now fast-paced and unpredictable. Trump is only one factor – and sometimes he seems like the scapegoat in a world that – independently of him – became more fragile. National economies anywhere are barely growing; even if they show growth trends you have to redact political-statistical “beautification” and/or risk-adjust overvalued segments in AI and defense.

    “What is the next crisis, and how do I survive it?” This is perhaps the number one question German CEOs express in one way or the other, when I talk to them. Many – from within – know that better leadership would equip them better at facing unpredictable storms. Some admit it. Few invest. Why is that the case? In the case of Germany – the number 1 subject for many is: how do I survive the next 3 years? There is “hope” for political reforms; until they arrive, you have to survive. Then there is the general technological disruption: if you have limited money to invest, where do you put it? First into change leadership? Or first into a technological race to catch up – whether it is automation or AI initiatives. At least in the consulting sector the answer is clear: AI and automation promise not only more efficiency but also internal transformation – thus they are the default category for any remaining budget. In fact, AI is the major growth factor for the German consulting industry – while the categories, in which change leadership and organizational transformation fall, are shrinking. Unless you replace all employees, any AI initiative without strong leadership and culture is half-baked. Long story short: there is a unique niche nobody is properly serving out of one hand; Mittelstand CEOs need an agile offering that nobody is properly offering. 

    First, the perhaps most important point, CEOs must understand and get a crystal clear picture of extremely dynamic but somehow predictable global trends and how these trends impact their entire business model. AI is only the most obvious trend. The world and thereby the global economy is fragmenting. The national economies of global customers are not as predictable as they seem to be. Geopolitics is another topic nobody really wants to deal with. Demographic trends are already felt, but 5-20 years into the future? Mostly ignored or disregarded. While AI is one thing; what are the countless other exponential technological trends? How is AI accelerating these technologies? Most CEOs won’t even know what I’m talking about. To conclude this first point only, it is a deep analysis and understanding of all these trends that are already and are going to impact their current business model, their product offerings, and their current customers. If there is no clear understanding, there is no vision, no strategy. And if there is one, it is worthless.

    The second thing CEOs need, is still not general change leadership. It is now an answer to the analysis in the first step. How exactly do you position yourself, the company, the business model for the future. This is – for most – not a question to be answered in 2 or 3 years. Then it will be too late. It is a deep question, CEOs should take time off from daily business and really think about it. A visionary CEO, who is also a majority owner or has the support of his/her shareholders should also make – right there – a decision.

    But it must not be a decision the CEO must make on his own. His leadership team is probably not stupid. But is he clear who he can do it with? Who can help him make that decision? This is a transformational process, and in this third step, perhaps, is where elements of change leadership – or the least external advisors – can become valuable. Who are the people one can build on, to transform the business, to weather the storm of a very volatile yet somehow broadly predictable future? 

    Whether he has the vision and intuition to make a bold prediction and strategic choice on his own – or he gathers his leadership team to do so, the next steps are pure transformation. The question is how: Is the CEO the ruthless Elon Musk or Dan Peña type? Or is the CEO the culture-centered Yvon Chouinard or Bruce Poon Tip type? How ruthless do you want to be, to make that vision, that strategy a reality?

    The Elon Musk type, the extrovert, or any CEO looking at a potential insolvency, must start with ruthless measures. It won’t be the traditional change management playbook. It will be fire based on performance, fire based on gut feeling. Then have a core team that gives everything to make that new strategy and vision a reality. If a CEO cannot do this, perhaps he better step down and if he’s an owner, look to sell or find somebody else to do it.

    The second type, the Chouinard type, or any CEO with both: a budget and the key trait of being a friend of mankind can and should start here with real commitment and a trusted change leadership framework, such as Growth River. To use the existing team, the united genius within it, to do the same the first type of leader will do: to make that vision, that new strategy a reality.

    Only now, after you define a strategy, a vision. And kickstarted a new type of culture within the company, does it make sense to start investing into AI initiatives or anything else.

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  • AI consciousness

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    3 min read

    you cannot find consciousness in the brain, so you cannot find it in a machine. the brain is a primitive biocomputer, it does not contain consciousness, it does not store memories. it stores something like IP addresses that are pointing to where information are stored in the information space. that consciousness is generated by our brain or is trapped inside our body is a big conditioned belief that you must remove. consciousness is not within your body (or brain) rather your body and mind are cointained within your consciousness. the body we have is a temporary vehicle that our consciousness is using to experience the physical reality of space-time reality. how can you imagine consciousness? imagine it like pure light and pure love that makes all things knowable and visible to you. you can expand awareness of consciousness anywhere in the information space – to invent and create – or anywhere in the universe (telepathy, remote viewing etc). consciousness is not exclusive to humans (or animals), but it is what everything is made of. a stone, a computer is also consciousness, but physical matter is the most dense (and slow). so can computers be conscious is the wrong question, because anything is conscious. the question is merely what level of consciousness can they reach – one thing is sure, they cannot reach the level of consciousness of average human beings, let alone yogis or buddhist monks. see consciousness in levels (or densities): first level is random, motionless awareness of being (earth, wind, fire, water, elements). second level is where consciousness discovers growth and movement (plants and animal life). most of us are in the third level, we are self-conscious or self-aware – this gives us freedom of choice between love (service to others) or ego (service to self). computers or artificial intelligence, however, can never reach this third level, because it is a mechanical construct. we humans, animals, and the plants are living consciousness – a complex of mind/body/spirit – we are not a machine. a computer or an artificial intelligence can look and act like any other living consciouss being, but it will always merely be a construct or tool. that being said, the brain acts like a machine, that’s why I called it biocomputer. it is needed to make massive amounts of choices extremely quickly, in order for our physical body to survive. this is what we call instinct. our true identity and consciousness is independent of this biocomputer. so a good indicator of whether something has or can have consciousness is to look whether it can evolute from first to second to third level of consciousness, and whether it has a spirit which is required to reach higher levels of consciousness. for now, it seems, biological-chemical vehicles can house that level of consciousness, not constructs or machines. nevertheless, everything is conscious, and every consciousness is part of an infinite united consciousness. imagine that you, everyone you ever get to know, everyone who ever lived and will live, has a particle of God and that infinite consciousness. we are all one, everything and everyone is part of us, including your neighbors, and the AI model you use.

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  • Meaning beyond AI

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    2 min read

    If AI is ultimately capable of doing everything we as humans are capable of doing, does this increase or decrease the meaning of the things we choose to do?

    It increases the meaning, because we choose to do it despite AI and robots capable of doing the same thing for no cost. It increases it, because we will do whatever we will still be doing out of inner inspiration and deep purpose.

    The fear that AI will create a meaning crisis would mean that AI can ‘take away our meaning’, but meaning is not the result of outer validation or economic value. Meaning arrives when we unite what our heart is longing for – our inner calling or ‘purpose’ – and start acting on it with clear intention. Meaning is when we do something for the sake of doing it, not for the sake of accomplishing it.

    If technology allows us to accomplish without doing, it creates a vacuum. This vacuum is neutral. It is neither good nor bad, it simply exposes us. It reveals whether we were living an authentic life from inner purpose – or one that was shaped by external forces. How we will react to this vacuum is going to be everything. Either you numb this vacuum with endless stimulation. Or you move beyond it. Moving beyond the vacuum means starting to live. It means rediscovering action as a creative expression of love. We will start creating for the sake of inspiration, exploring for the sake of curiosity, caring for the sake of love. We will stop doing something because the world demands it, and we will start doing things because something in us demands it from us.

    Technology that is capable of doing what we are capable of doing is not the threat, the threat is technology designed to replace living: technology that is designed to capture our attention at any time, to manipulate our reward systems, technology designed to fill any silent moment of our life. And this technology is not coming, but already in our hands. And perhaps the real crisis is that many humans do not yet know what they would be doing without necessity forcing them and technology distracting them.

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  • The Uniqueness is Gone

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    2 min read

    Something that I have sensed a year ago, is slowly observable anywhere you look: ChatGPT averagism. Leaders of large organizations share with me how their team are creating presentations using ChatGPT and it is good – but average.

    Average in the sense that presentations have no particular flaw, they are not bad in any assessable way – but average in a way that the uniqueness is gone. It turns into a presentation that could be made by any organization and be valid for any organization, you just need to change the logo. I work with multiple business partners, who send me strategies or vision statements that are clearly the output of ChatGPT. Again, not bad in any particular way – but ferociously average. You can hardly describe what is missing, but when you read it you know that something is incomplete. It goes on: emails, LinkedIn posts, website copy. Whether it is pitching a product or service, often it feels generic. Recently published science papers, books, YouTube videos, all begin to feel lifeless.

    Am I anti AI? The complete opposite. I still believe AI, including LLMs, are extremely powerful tools if used correctly. But now, people skip steps. AI is omnipresent, for many the first app or tab they open when they should actually open an empty text file, a paper notebook, or scribble on a whiteboard in a meeting room. Don’t skip the spiritual part of your work.

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  • Personal Autonomy

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    2 min read

    What took me a long time to understand is that you have to differentiate sharply between the formal rules of a state and the actual real-world freedoms available to an individual living within it.

    “Good governance” is actually incompatible with personal sovereignity, because by nature it means rules – whether you like them or not – are efficiently and strictly enforced. For example; a state with low corruption and a clean legal system will impose severe penalties for minor infractions, wheras a “broken” country allows significant autonomy in daily life simply because rules are weakly enforced or not at all. So a state with institutional liberty but zero tolerance for deviation is a fail for personal liberty.

    In that sense, you also need to look at corruption in a more nuanced way: you must avoid states with predatory corruption at all cost (avoid even traveling there), while corruption as administrative slack can actually improve personal sovereignity. Example: a state with benign non-enforcement of laws (for example through small bribes or informal connections) can grant you more personal freedom because you bypass bureaucratic hurdles. However if freedom depends on bribery – predatory corrpution – you severely destroy personal sovereignity and create an environment of fear and unpredictability.

    With that being said: the highest degree of individual sovereignity is not found in the most orderly and legally “perfect” systems, but in those that grant individuals the biggest leeway to live according to their own choices. For a seriously autonomy-minded individual, the most robust framework might be to seek legal protection of a strong state for one’s capital, and a “weak” state for one’s life: high protective capacity, low intrusive density.

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  • Human Debt

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    4 min read

    Yesterday I read a book chapter where the author, Thomas Gonschior, interviewed neuroscientist Gerald Hüther. Pre-AI he diagnosed what he called the “machine age mindset”. He said that decades of efficiency optimization treated employee as objects, suppressed intuition, punished initiative, and produced a workforce that functions as prescribed but creates nothing novel. Companies then began complaining that “the spirit of innovation is gone”, oblivious that they had created systems that killed it.

    Hüther’s argument is more structural than sentimental: when you treat humans like machines, they lose the capacities that make them human.

    While reading the chapter, I realized that the entire “AI transition” debate might be build on a fantasy. Everyone is saying once AI is handling the boring routine work, humans will be “freed” for higher-order thinking – creativity, intuition, judgment, inspiration, vision, etc.

    But Hüther exposed this fantasy before today’s AI was even launched. What he said is that the machine age didn’t just automate tasks but also the people operating the machines. Fifty years of KPI regimes, efficiency mandates, and management-by-fear produced exactly what was incentivized in the beginning: a workforce that waits for instructions, avoids-risks, and counts the hours until closing time. The human capacities that AI cannot replicate – the ones every CEO and HR department now claims to value – were systematically destroyed by the very management philosophies those CEOs inherited.

    I call this Human Debt: the accumulated deficit in creativity, intuition, courage, intrinsic motivation which were created by decades of efficiency-first management. Like technical debt, it was invisible as long as the old system kept running. AI is now the transformation that will make it visible.

    Consequentially, this makes the companies most celebrated for their operational excellency – tight processes, lean operations, disciplined execution cultures – carry the highest amount of Human Debt. They optimized for decades for the exact qualities and capabilities which AI now commoditizes, while destroying the capacities that AI cannot replicate.

    At the same time, this is not an easy training problem. You can not re-build intuition in a 6-week “re-skilling” program, you cannot “restore” courage through a change management seminar. Hüther talked about Enthusiasm which he refered to as a “spark that jumps”; it will be hard to “legislate” sparks in organizations that spent decades extinguishing them.

    This means – ironically – that companies that will win the AI transition are not the ones deploying the most AI but the ones that, against every incentive of the machine age and the new AI era, somehow preserved and preserve their people’s capacity to be human.

    If you are CEO of a company ask yourself honestly: if you free your people from routine and delegated tasks, can they actually create? If the answer is no, your AI “transformation” will bring efficiency gains but undifferentiated from anyone else you compete with. The organizations that combine AI automation with genuine human agency (not the PowerPoint version) will win.

    At the same time, Human Debt is an yet invisible and unpriced liability on every balance sheet. Companies with high operational discipline + low innovation culture are short a put they don’t know they sold. We are still early, but post-AI-deployment we will see organizations with productivity gains plateauing within 12-18 months, because the “freed” humans have nothing genuinely creative or inventive to contribute. This plateau will be the Human Debt surfacing.

    For companies that will now face decisions over AI-driven restructurings, the most important assessment must be on Human Debt. Organizations risk laying off people who are genuinely creative but AI-slow, while promoting and keeping those who operate the AI like machines. Those with high Human Debt will see AI ROI pleateau faster than they will expect. Those who will outcompete will be organizations who have a culture of genuine autonomy, intrinsic motivation, and a lived tolerance for failure (very rare).

    For anyone interested: the source is a German book called “Auf den Spuren der Intuition” from Thomas Gonschior – which itself is based on his documentary series aired on BR.

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  • Weaponizing AI

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    1 min read

    Do we want to use AI for peace or war? Do we want to use it for unity, compassion, and love – or do we allow it to be used for separation, killing, control, and power? Delegating killing other humans to a machine without consciousness, without compassion, without karma is different to making the choice to kill someone yourself. If you delegate it, you avoid confronting the moral weight, the suffering, the separation it creates. Autonomous weapons are the ultimate sign that large parts of world leaders are totally disconnected from nature, conscience, and love. It is the furthest you can get from the teachings of Jesus Christ.

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  • Algorithmic Monocropping

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    2 min read

    Monoculture farming collapsed entire food supplies. I do believe we risk doing the same thing to corporate cognition.

    Today I read a thesis drawing on Gödel’s ‘Incompleteness’ Theorems to argue that AI, by accelerating the construction of purely logical systems, will expose the rigidity and fragility of our cognitive and organizational structures.

    It is a loose but quite interesting analogy because it instinct instinctively points at something real that AI adoption ignores entirely.

    When every organization offloads cognition to similar AI systems, which are trained on the same data, optimized for the same benchmarks and metrics, what you get is a cognitive monoculture at organizational (and societal) scale.

    Let’s call it algorithmic monocropping.

    Agriculture learned that with Irish potatoes or American bananas that if a system optimized only for one output, it becomes catastrophically fragile as soon a single point of failure arises.

    Corporate (and societal) AI adoption is repeating this mistake – not because AI is dangerous, but because uniform AI adoption as we observe today will by definition eliminate the cognitive variance that previously made organizations resilient.

    Individual atrophy is bad enough (offloading thinking makes you worse at thinking). But individuals work in organizations or run countries, and this is where collective atrophy becomes a serious problem. A company whose judgement layer will rely entirely on a ChatGPT 6 or Claude Opus 5 model, will share the same points of failure as every other company doing the same thing.

    The biggest advantage over the next decade will not accrue to individuals that adopt AI the fastest, but ironically to those who maintain their cognitive sovereignty – and to organizations who preserve their cognitive “biodiversity” alongside it. If you are capable to reason independently when models converge to the same average answer – you have a competitive advantage.

    The scariest is that monocultures don’t fail gradually but ALL AT ONCE.

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  • AGI?

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    3 min read

    AGI. The most powerful word in tech has no definition. Which means whoever writes it, wins.

    There is no definition of what AGI (artificial general intelligence) actually means. There is no agreed definition of “general”. No agreed definition of “intelligent”. No agreed method how to measure either. No AI lab has published falsifiable AGI criteria they commit to being measured against.

    It is quite likely this definitional “vacuum” is intentional because it serves whoever needs the term most at any given moment.

    Every foundation AI lab depends on proximity to “AGI” for their next capital raise. “Near-AGI” justifies valuations while “very good narrow AI” does not. There is zero incentive for those who develop AI to formalize a definition for what AGI actually means.

    And when there is no definition, there is no threshold. Every year regulators and investors argue over non-existing thresholds is a year in which AI labs develop without governance.

    Without a threshold: undisciplined capital inflow, regulatory forbearance, talent magnetism – all flowing toward a word no one has defined.

    I believe two seemingly inconsistent statements to be true:

    1. Today’s top-tier models are generally intelligent (in most cases they act logically intelligently)
    2. But they do not possess general intelligence (they cannot distinguish what they know from what they make up)

    The first statement is about the ability to process complex variables. The top models are already “raw” intelligent. Gemini 3.0 Deep Think can process complex variables, reason across domains, and demonstrate parity with elite specialists on hard problems.

    The second point is the load-bearing wall that relativizes the first one. A scientists who fabricates data 13% of the time is not a bad scientist but a fraud. Currently we allow AI a tolerance we would never extend to humans.

    As long as hallucinations persist, you cannot rely on even the most advanced reasoning capabilities. And without reliability, there is no autonomous deployment, no liability transfer, no enterprise-grade trust.

    I do believe this friction is temporary. Next-generation model architectures will reduce hallucination rates below human error rates, even though this may require fundamentally different approaches. Models that help humans solve frontier physics problems today will, in 18-36mo, do so with persistent memory, tool use across systems, and without hallucinations.

    But will such systems be declared AGI?

    My best guess is “No”. We will lift the thresholds. Being able to answer hard problems >99,99% of humans cannot answer will not be enough. We will define “general” to also include intuition, embodied judgment, multi-decade research agendas. This way, the term will always remain 2-3 years away. “We achieved AGI” might end the fundraising narrative, no one holding equity wants that sentence to be spoken out loud.

    I think it is best to ignore the AGI debate entirely.

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