• The First Principles of a Post-AGI Business

    OpenAI released its new o3 models and numerous people argue that this is in fact Artificial General Intelligence (AGI) – in other words, an AI system that is on par with human intelligence. Even if o3 is not yet AGI, the emphasis now lies on “yet,” and – considering the exponential progression – we can expect AGI to arrive within months or maximum one to two years.

    According to OpenAI, it only took 3 months to go from the o1 model to the o3 model. This is a 4x+ acceleration relative to previous progress. If this speed of AI advancement is maintained, it means that by the end of 2025 we will be as much ahead of o3 as o3 is ahead of GPT-3 (released in May 2020). And, after achieving AGI, the self-reinforcing feedback loop will only further accelerate exponential improvements of these AI systems.

    But, most anti-intuitively, even after we have achieved AGI, it will for quite some time look as if nothing has happened. You won’t feel any change and your job and business will feel safe and untouchable. Big fallacy. We can expect that after AGI it will take many months of not 1-2 years for the real transformations to happen. Why? Because AGI in and of itself does not release value into the economy. It will be much more important to apply it. But as AGI becomes cheaper, agentic, and embedded into the world, we will see a transformation-explosion – replacing those businesses and jobs that are unprepared.

    I thought a lot about the impact the announced – and soon to be released – o3 model, and the first AGI model are going to have.

    To make it short: I am extremely confident that any skill or process that can be digitized will be. As a result, the majority of white-collar and skilled jobs are on track for massive disruption or elimination.

    Furthermore, I think many experts and think tanks are fooling themselves by believing that humans will maintain “some edge” and work peacefully side-by-side with an AI system. I don’t think AGI will augment knowledge workers – i.e. anyone working with language, code, numbers, or any kind of specialized software – it will replace them!

    So, if your job or business relies purely on standardized cognitive tasks, you are racing toward the cliff’s edge, and it is time to pivot now!

    Let’s start with the worst. Businesses and jobs in which you should pivot immediately – or at least not enter as of today – include but are not limited to anything that involves sitting at a computer:

    • anything with data entry or data processing (run as fast as you can!)
    • anything that involves writing (copywriting, technical writing, editing, proofreading, translation)
    • most coding and web development
    • SAAS (won’t exist in a couple of years)
    • banking (disrupted squared: AGI + Blockchain)
    • accounting and auditing (won’t exist as a job in 5-10 years)
    • insurance (will be disrupted)
    • law (excluding high-stake litigation, negotiation, courtroom advocacy)
    • any generic design, music, and video creation (graphic design, stock photography, stock videos)
    • market and investment research and analysis (AI will take over 100%)
    • trading, both quantitative and qualitative (don’t exit but profit now, but expect to be disrupted within 5 years)
    • any middle-layer-management (project and product management)
    • medical diagnostics (will be 100% AI within 5 years)
    • most standardized professional / consulting services

    However, I believe that in high-stakes domains (health, finance, governance), regulators and the public will demand a “human sign-off”. So if you are in accounting, auditing, law, or finance I’d recommend pivoting to a business model where the ability to anchor trust becomes a revenue source.

    The question is, where should you pivot to or what business to start in 2025?

    My First Principles of a Post-AGI Business Model

    First, even as AI becomes infallible, human beings will still crave real, raw, direct trust relationships. People form bonds around shared experiences, especially offline ones. I believe a truly future-proof venture leverages these primal instincts that machines can never replicate at a deeply visceral level. Nevertheless, I believe it is a big mistake to assume that humans will “naturally” stick together just because we are the same species. AGI might quickly appear more reliable, less selfish than most human beings, and have emotional intelligence. So a business build upon the thesis of the “human advantage” must expertly harness and establish emotional ties, tribal belonging, and shared experiences – all intangible values that are far more delicate and complex than logic.

    First Principle: Operate in the Physical World

    • If your product or service can be fully digitalized and delivered via the cloud, AGI can replicate it with near-zero marginal cost
    • Infuse strategic real-world constraints (logistics, location-specific interactions, physical limitations, direct relationships) that create friction and scarcity – where AI alone will struggle

    Second Principle: Create Hyper Niche Human Experiences

    • The broader audience, the easier it is for AI to dominate. Instead, cultivate specialized groups and subcultures with strong in-person and highly personalized experiences.
    • Offer creative or spiritual elements that defy pure rational patterns and thus remain less formulaic

    Third Principle: Emphasize Adaptive, Micro-Scale Partnerships

    • Align with small, local, or specialized stakeholders. Use alliances with artisan suppliers, local talents, subject-matter experts, and so on.
    • Avoid single points of failure; build a decentralized network that is hard for a single AI to replicate or disrupt

    Fourth Principle: Embed Extreme Flexibility

    • Structured, hierarchical organizations are easily out-iterated by AI that can reorganize and optimize instantly
    • Cultivate fluid teams with quickly reconfigurable structures, use agile, project based collaboration that can pivot as soon AGI-based competition arises

    Opportunity Vectors

    With all of that in mind, there are niches that before looked unattractive, because less scalable, that today offer massive opportunities – let’s call them opportunity vectors.

    The first opportunity vector I have already touched upon:

    • Trust and Validation Services: Humans verifying or certifying that a certain AI outcome is ethically or legally sound – while irrational, it is exactly what humans will insist on, particularly where liability is high (medicine, finance, law, infrastructure)
    • Frontier Sectors with Regulatory and Ethical Friction: Think of markets where AI will accelerate R&D but human oversight, relationship management, and accountability remain essential: genetic engineering, biotech, advanced materials, quantum computing, etc.

    The second opportunity vector focuses on the human edge:

    • Experience & Community: Live festivals, immersive events, niche retreats, or spiritual explorations – basically any scenario in which emotional energy and a human experience is the core product
    • Rare Craftsmanship & Creative Quirks: Think of hyper-personalized items, physical artwork, artisanal or hands-on creations. Items that carry an inherent uniqueness or intangible meaning that an AI might replicate in design, but can’t replicate in “heritage” or provenance.

    Risk Tactics

    Overall, the best insurance is fostering a dynamic brand and a loyal community that invests personally and emotionally in you. People will buy from those whose values they trust. If you stand for something real, you create an emotional bond that AI can’t break. I’m not talking about superficial corporate social responsibility (nobody cares) but about authenticity that resonates on a near-spiritual level.

    As you build your business, erect an ethical moat by providing “failsafe” services where your human personal liability and your brand acts as a shield for AI decisions. This creates trust and differentiation among anonymous pure-AGI play businesses.

    Seek and create small, specialized, local, or digital micro-monopolies – areas too tiny or fractal for the “big AI players” to devote immediate resources to. Over time, multiply these micro-monopolies by rolling them up under one trusted brand.

    Furthermore, don’t avoid AI. You cannot out-AI the AI. So as you build a business on the human edge moat, you should still harness AI to do 90% of the repetitive and analytic tasks – this frees your human capital to build human relationships, solve ambiguous problem, or invent new offerings.

    Bet on What Makes Us Human

    To summarize, AI is logical, combinatorial intelligence. The advancements in AI will commoditize logic and disrupt any job and business that is mainly build upon logic as capital. Human – on the other hand – is authenticity. What makes human human and your brand authentic are elements of chaos, empathy, spontaneity. In this context, human is fostering embodied, emotional, culturally contextual, physically immersive experiences. Anything that requires raw creativity, emotional intelligence, local presence, or unique personal relationships will be more AI resilient.

    Therefore, a Post-AGI business must involve:

    1. Tangibility: Physical goods, spaces, unique craftsmanship
    2. Human Connection: Emotional, face-to-face, improvisational experiences
    3. Comprehensive Problem Solving: Complex negotiations, messy real-world situations, diverse stakeholder management

    The inverse list of AGI proof industries involve some or multiple aspects of that:

    • Physical, In-Person, Human-Intensive Services
      • Healthcare: Nursing, Physical therapy, Hands-on caregiving
      • Skilled trades & craftsmanship
    • High-Level Strategy & Complex Leadership
      • Diplomacy, Negotiation, Trust building
      • Visionary entrepreneurship
    • Deep Emotional / Experiential Offerings
      • Group experiences, retreats, spiritual or therapeutic gatherings
      • Artistic expression that thrives on “imperfection”, physical presence, or spontaneous creativity
    • Infrastructure for AGI
      • Human-based auditing/verification
      • Physical data center operations & advanced hardware
      • Application and embedment of AI in the forms of AGI agents, algorithmic improvements, etc. to make it suitable for everyday tasks and workflow

    The real differentiator is whether a business is anchored in the physical world’s complexity, emotional trust, or intangible brand relationships. Everything pure data-driven or standardized is on the chopping block – imminently.

  • Trump: Rewiring Civilization

    Donald Trump’s reelection is not just a political victory—it is the beginning of a seismic realignment of American power. Unshackled by the need for reelection and surrounded by a cadre of contrarian advisors, Trump stands ready to rewrite the rules of domestic governance, global trade, and national security. Not since the mid-20th century has a U.S. presidency promised such a fundamental overhaul of the nation’s operating system.

    This moment introduces a high-variance environment where volatility is the new norm and uncertainty both a risk and an opportunity. Trump’s method turns conventional wisdom on its head: predictability, once prized, is now a vulnerability; unpredictability, a calculated asset. This inversion compels domestic institutions, foreign governments, multinational corporations, and investors to abandon old assumptions and prepare for a new, uncharted era of American leadership.

    Strategic Unpredictability

    In conventional politics, predictability reinforces trust and stabilizes alliances. Trump turns this formula on its head. Borrowing from his business roots, he treats governance like an endless high-stakes negotiation, refusing to be pinned down by familiar rules. Instead of relying on time-honored frameworks—NATO’s ritualistic guarantees, half-century-old trade deals, bureaucratic inertia—Trump embraces a sophisticated combinatorial approach to decision-making. He experiments with countless permutations of strategies and tactics, making his next move virtually impossible to predict.

    This unpredictability, often mistaken for chaos, is calculated. Trump breaks traditions, mixes signals, and never commits fully to a single position. The discomfort this causes among media, diplomats, and policymakers arises from their inability to slot him neatly into known categories. As allies and adversaries scramble to decode shifting signals, they must now renegotiate assumptions and adapt on the fly. Formerly stable trading partners can no longer rely on a static understanding of U.S. policy, and institutions once considered untouchable must re-justify their relevance.

    The benefits for Trump’s agenda can be substantial: unthinkable reforms, renegotiated pacts more favorable to U.S. interests, and revived domestic industries. The risk, however, is perpetual uncertainty—markets can rattle, trust erode, and miscalculations prove costly. Yet by keeping the world off-balance, Trump preserves maximum strategic freedom, forcing every stakeholder to engage on his terms. This approach reveals Trump as a leader who, far from being misguided or simplistic, demonstrates a rare creative intelligence—one that thrives on complexity, defies convention, and redefines the limits of political possibility.

    A Presidency with Succession Plan

    No longer seeking reelection, Trump’s ambitions transcend short-term popularity. He envisions a legacy enduring centuries, a future where his descendants inherit a reshaped America. This shift in time horizon is profound. It emboldens him to attempt structural overhauls that others fear as political suicide. He can endure short-term pain, criticism, and even chaos if he believes it sets a foundation that benefits future generations.

    Rather than governing for one election cycle, Trump is orchestrating a multi-decade realignment aimed at reviving stagnant industries, redrawing global trade patterns, and consolidating a durable political base. Central to this strategy is J.D. Vance, a sharp and versatile leader who will command broad appeal if the administration delivers on its promises. As a policy entrepreneur who blends conservative instincts with selective progressive ideas, his potential appeal across party lines sets him apart from orthodox politicians. If he can claim credit for tangible improvements—such as a resurgent manufacturing corridor in the Midwest—Vance’s path to the presidency in 2028 becomes clearer, ensuring policy stability that stretches well beyond Trump’s final day in office.

    Beyond J.D. Vance, Trump’s succession plan includes other high-potential figures who could easily extend his vision well into the 2030s. Robert F. Kennedy Jr., with his unique blend of populist appeal, independent thinking, and a growing base across traditional party lines, emerges as a natural complement to Trump’s coalition. His presence signals a broader ideological realignment, bridging gaps between disillusioned Democrats, independents, and Republicans. Additionally, Trump’s children – particularly Donald Trump Jr. and Ivanka Trump – are well positioned to inherit both the political machinery and cultural influence their father has cultivated. Together, this combination of J.D. Vance, RFK Jr., and the Trump family creates a formidable roster of successors, capable of sustaining Trump’s disruptive agenda for 12 years, or even two decades.

    This multi-generational continuity is the most important possibility to internalize. Waiting Trump out is no longer an option. Institutions and foreign governments cannot bank on a swift return to pre-Trump norms. Instead, they must recognize the likelihood of an enduring disruption and recalibration. Again, even if Trump only succeeds in reviving the Rust Belt, it seems likely that the U.S. will spend the coming decade dismantling, digitizing, and rebirthing its institutions, forging a state that sets new efficiency standards and redefines global power.

    Trump x Musk

    In the tense aftermath of the assassination attempt on Donald Trump, Elon Musk’s swift and unequivocal endorsement stunned the public. Within minutes, his bold show of confidence galvanized millions of hesitant voters, emboldening them to step forward and voice their support.

    Musk went further, warning that if Trump, armed with superior policies, a seasoned team, and lessons from his first term, still failed to defeat a weak Democratic challenger, it would mark America’s last truly meaningful election. While dramatic, this message was less prophecy than critique—an attack on the creeping institutional inertia in Washington. In Musk’s view, the real danger laid not in some North Korean style regime but in the emergence of a system that, like California’s one-party politics, renders elections mere formalities. If entrenched bureaucracy could outlast Trump’s best efforts, democracy would become ritual rather than reality, and the nation’s political destiny would drift beyond the voter’s reach.

    The Musk – Milei Connection

    Elon Musk’s fascination with Argentina’s libertarian president, Javier Milei, adds an unexpected dimension to the Trump-Musk relationship. Milei’s reforms, centered on relentless deregulation and led by a powerful Ministry of Deregulation dismantling barriers at lightning speed, offer a live test bed for the libertarian governance Musk envisions and Trump might embrace. The Argentine experiment—wielded by the sharp intellect of Federico Sturzenegger’s ministry—cuts one to five obstacles a day, shrinking a bloated state into a lean, innovation-ready apparatus.

    This bold agenda resonates strongly with Musk, who has hinted at parallel efforts in the U.S. through his proposed Department of Government Efficiency (DOGE). Both he and Milei share a taste for smashing outdated frameworks, allowing decentralized markets to flourish and forcing institutions to justify their existence. Milei’s admiration for Trump as a “true warrior” and “viking” cements this ideological triangle. It suggests a cross-pollination of ideas—Milei’s ruthless pruning of state power, Musk’s efficiency crusade, and Trump’s willingness to rewrite the rulebook—potentially softening Trump’s reliance on tariffs and energizing his push for structural reform.

    An Alliance of Consequence

    Elon Musk’s transition from outside visionary to an influential policymaker is more than a new addition to Trump’s arsenal—it’s a force multiplier. Musk’s wide-angle, multi-planetary perspective infuses fresh intellectual rigor into a governance style defined by volatility, turning unpredictable impulses into purposeful experimentation. But his influence no longer stands alone. The Milei effect now permeates these corridors of power, seeding radical ideas about deregulation and streamlined government that are not theoretical but field-tested in Argentina’s bold experiment.

    With Milei’s blueprint as a proof of concept, Musk and Trump find tangible models for dismantling entrenched bureaucracies. Instead of grappling with intangible theories, they can point to real results—economic barriers torn down at a breakneck pace, the state machinery pared back without collapsing the social fabric. Argentina’s evidence emboldens Musk’s push for sweeping reforms—faster permitting, leaner agencies, a dynamic redefinition of public service—and helps Trump justify riskier moves that traditional politics once deemed unthinkable.

    The result is not mere chaos, but a calculated recalibration. As Musk invests time shaping innovation policies and operational efficiencies, he draws on lessons from Milei’s successes to justify even bolder undertakings. These new frameworks, influenced by both Musk’s contrarian brilliance and Milei’s radical pragmatism, feed back into Trump’s governance style. Each actor accelerates the others, creating a self-reinforcing cycle of disruption and renewal.

    The result: a triad of global disruptors—Trump, Musk, Milei—whose ideological synergy could reshape how governments function and markets evolve. Argentina’s libertarian revolution provides a clarifying lens into what future American reforms might look like: radical, data-driven, and unapologetically free-market, with global ripples challenging stagnation wherever it takes root.

    The DOGE Experiment

    The synergy between Trump, Musk, and the lessons drawn from abroad now converges within the Department of Government Efficiency (DOGE). Freed from traditional templates, DOGE seeks to simplify tax codes, automate administrative procedures, and use technology to slash bureaucratic dead weight at breakneck speed.

    Imagine the U.S. government as an advanced operating system: blockchain-based audits instead of paper trails; AI-driven licensing to eliminate red tape; simpler, unified tax codes; algorithms to streamline procurement. DOGE aims for order-of-magnitude improvements in efficiency, cutting decades of accumulated friction.

    The United States is no fragile backwater; its immense global influence and deeply entrenched institutions mean that any disruption reverberates across markets, alliances, and long-standing treaties. As the world’s largest economy and a cornerstone of geopolitical stability, the U.S. cannot afford large-scale missteps. Yet the DOGE initiative adopts a startup mentality—rapid iteration and high-stakes trial and error. The potential upside is transformative: streamlined public services, productivity-boosting incentives, and a leaner, more efficient government. The risk, however, is equally profound. Removing critical structural supports without care could destabilize the system, triggering unintended and potentially catastrophic consequences.

    This tension underscores the importance of the existing talent housed within the U.S. bureaucracy. Unlike Argentina’s historically disorganized public sectors, Washington’s institutional apparatus holds deep reservoirs of domain expertise—i.e. in foreign affairs. The DOGE mandate is to harness this knowledge, not extinguish it. Musk’s first-principles logic demands that old frameworks pass rigorous stress tests: if a structure can’t be justified, it goes. But he must also ensure valuable specialists remain engaged, transforming inertial complexity into dynamic competence.

    The outcome is radical uncertainty. Markets should expect breakneck policy pivots, unconventional alliances, and sudden regulatory changes. The winners will be those who anticipate Musk’s logic: simplify processes, reduce friction, solve root problems, and think big. Those who rely on slow-moving bureaucracies and incrementalism may find themselves outpaced.

    Tax Reforms: Toward Radical Simplification

    Trump’s envisioned tax overhaul—steeped in campaign promises of cuts, credits, and targeted relief—now faces a deeper metamorphosis under the influence of Elon Musk’s DOGE. While conventional analysis fixates on marginal rates and brackets, Musk approaches taxation like a first-principles engineering problem, stripping away centuries of incremental complexity.

    This perspective challenges the old narrative. Instead of parsing line items—tips, overtime, tariffs—Musk demands a wholesale reset: a flattened structure free of intricate carve-outs and sector-specific giveaways. Such radical simplification acknowledges a central truth: complexity breeds corruption, invites rent-seeking, and rewards the nimble few at the expense of the many. If America’s fractal tax code now favors professional tax strategists and corporate accountants fluent in loopholes, Musk wants a system comprehensible to any citizen with a smartphone.

    The most likely outcome? A streamlined tax regime that reduces friction across the entire economy. Imagine minimal categories of income, uniform treatment of earnings, and a largely automated compliance process. Smart contracts and digital ledgers could replace annual filings with instantaneous settlements, neutering the bureaucratic machinery that has grown around tax enforcement. These changes would make it harder for both corporations and governments to hide inefficiencies—an outcome that resonates with Trump’s broader ambition to strip away outdated infrastructure.

    Yet this simplicity harbors profound implications. A truly flat, transparent system would expose the real winners and losers of American policy choices. If protectionism endures, tariffs would stand naked as a parallel tax, visible in real time rather than obfuscated by a maze of deductions and rebates. Politicians, accustomed to cloaking redistribution in complexity, might find it harder to pass off subtle forms of patronage as populism. In essence, a maximally simplified tax code removes the camouflage that has protected vested interests for decades.

    Of course, simplicity will backfire if introduced bluntly. Entire industries, from tax advisory firms to lobbyists, depend on complexity’s shelter. Abruptly leveling the landscape will produce short-term chaos as entrenched players scramble for new footing. Moreover, while Musk’s logic-driven approach promises elegance, reality may resist tidy solutions. Certain incentives—promoting green energy or encouraging domestic manufacturing—might still demand nuance. But the starting point is no longer incremental tinkering; it’s a clean slate, forcing every tax provision to justify its existence from zero.

    Tariffs: Negotiation Leverage

    Once dismissed by orthodox economists as blunt and inefficient, tariffs now stand at the center of Trump’s global playbook—not as a fixed doctrine, but as a tactical lever. Free market idealists champion free trade as the route to optimal outcomes, yet real-world markets rarely start on equal footing. Nations tilt the field with subsidies, currency manipulation, and hidden regulatory hurdles. In such an environment, tariffs become a strategic scalpel that can reset terms, enforce reciprocity, and pry open previously closed markets.

    For Trump, a sweeping 60% duty on Chinese imports is no final blueprint—it’s an opening offer designed to shock the system. The message: negotiate, adjust, or pay the price. This unpredictability unsettles long-standing assumptions. Allies and adversaries alike must recalibrate, as stable supply chains give way to fluid production networks in Vietnam, India, or Mexico. If done well, these shifts yield a more balanced distribution of manufacturing and reduce America’s vulnerabilities to single-source suppliers. In this sense, tariffs can foster resilience and diversification, mitigating the geopolitical choke points that free trade theory never fully acknowledged.

    Yet these weapons must be wielded with surgical precision. Mishandled tariffs risk alienating key partners, rattling markets, and sparking inflation. They can morph into a hidden tax on consumers, undermining the very domestic revitalization they promise. Elon Musk’s perspective offers a cautionary note: restructuring supply chains is no quick fix. Shifting factories and retraining workers takes years. Abrupt, across-the-board tariffs can fracture critical production systems overnight. Prudence suggests a phased approach, signaling intentions early, allowing industries time to adapt, and using threats as negotiation chips rather than sledgehammers.

    Trump’s coalition of advisors—visionaries like Musk, pragmatists like Howard Lutnick—emphasizes targeted action over blunt force. Lutnick proposes a formulaic approach: match a trading partner’s tariffs, impose them only where the U.S. can compete, and use them as a bargaining chip rather than an end state. Paired with Musk’s operational realism, this strategy tempers political showmanship with economic feasibility.

    Instead of uniform duties, expect a tiered system: minimal tariffs for allies who reciprocate, moderate rates for neutral partners, and punishing levies for strategic rivals until fair terms emerge.

    Under this lens, tariffs become a negotiating language—a means of translating America’s industrial resurgence into concrete policy outcomes. Politically, these moves resonate with the Rust Belt and other regions hungry for manufacturing revivals. Economically, they remain high-risk experiments, vulnerable to miscalculation. But the goal is not permanent protectionism; it’s to restore equilibrium. If tariffs coax other nations toward true free trade—removing their own barriers—they ultimately may lead to a more open global system than before.

    In short, Trump’s tariff agenda is less about ideology and more about leverage. Done right, tariffs serve as corrective scalpel, not crude club—enforcing fairness where laissez-faire rhetoric has failed. In a world of asymmetric rules and systemic imbalances, this may be the stark, contrarian truth: without the threat of tariffs, free trade’s promised harmony remains a chimera.

    Renegotiating the World

    For over seven decades, America’s alliances and institutions have rested on the scaffolding erected in the aftermath of the Second World War. NATO, Bretton Woods, the UN—these once-bold innovations now feel like aging load-bearing beams creaking under their own weight. They have delivered stability and prosperity, but also complacency and moral hazard. As the world fragments into multipolar tension—Tehran, Moscow, Kiev, Jerusalem, Taiwan, India-Pakistan—Donald Trump’s second term thrusts these pillars into a stress test. His approach is simple yet radical: prove your worth or face demolition.

    This contrarian posture rattles allies accustomed to American predictability. For decades, Europe has invested minimally in its own defense under the U.S. umbrella. Now, NATO members must confront the possibility that American guarantees are no longer unconditional. The same logic extends to trade blocs, security treaties, and bilateral pacts formed in a bygone era. By challenging their continued relevance, Trump invites allies and adversaries alike to recalibrate. In this environment, alliances cease to be moral endowments and become contingent bargains that must demonstrate current strategic value.

    This renegotiation is risky. The global order no longer pivots neatly around a stable U.S.-Soviet axis, nor is it the unipolar moment of the 1990s. Today’s order is an uneven chessboard of nuclear weapons, resource competition, and ideological fragmentation. Overturning familiar architectures could yield unexpected cascades. Pushing NATO partners to shoulder more responsibility might strengthen the alliance—or fracture it. Pressuring countries reliant on U.S. market access may secure fairer deals—or encourage them to form new blocs that exclude Washington. Each move is a high-stakes bet, where skillful statecraft could produce more honest and balanced arrangements or trigger crises that even superpowers struggle to contain.

    But from Trump’s vantage point, the old frameworks no longer align with American interests. They’re relics of a unique historical anomaly—the post-1945 order—when America’s unmatched might and nuclear stalemate enforced a global architecture. That anomaly, he argues, is over. In an age where strategic rivals like China and Russia test the boundaries with greater subtlety, clinging to outdated agreements is not strategy but inertia.

    Critics warn that eroding trust and predictability drains American soft power, making it harder to rally allies in crises like pandemics or climate shocks. True enough, unpredictability can sabotage diplomacy. But predictability can also foster free-riding and entrench dysfunction. Trump’s gamble is that by shaking old alliances to their core, he can force genuine renewal. Perhaps NATO will finally modernize and balance its burden-sharing. Perhaps trade compacts will shed legacy constraints and become truly reciprocal.

    The outcome is uncertain. Renegotiating the world order in real time risks overreach and unintended consequences. Yet standing pat means risking slow decline under ossified structures that no longer serve American interests or global stability. In a world of rising stakes and diminished certainties, Trump’s challenge to the old order represents a radical, contrarian attempt to forge a more honest equilibrium—one in which every alliance, every treaty, and every institution must earn its keep.

    The Miscalculation Threat

    Modern leaders, Trump included, have never personally witnessed the horrors of full-scale war. They grew up in an era defined by contained conflicts, drone strikes, and managed escalations rather than battles that raze cities and reorder civilizations. Without scars from industrial-scale bloodshed, they treat war as a toolkit, negotiable and bounded—a game where one can bluff, push, and recalibrate at will.

    This war amnesia skews judgment. Absent the visceral memory of trenches or mushroom clouds, today’s statesmen and strategists assume that rational actors will always stop short of catastrophe. But true rationality erodes when survival is at stake. Corner a nuclear-armed power—Russia over Ukraine, China over Taiwan—and the logic of controlled brinkmanship can unravel. The difference between a shrewd gamble and a disastrous misread shrinks to a razor’s edge.

    Trump’s unpredictability, in theory, can shatter diplomatic inertia and open unprecedented avenues for deal-making. Yet the same volatility can push adversaries beyond their comfort zones. Misread signals and cultural blind spots can amplify misunderstandings. In a world of intertwined alliances and nuclear tripwires, the room for error narrows to nothing. A single miscalculation could cascade toward irreversible chaos.

    Compounding the problem is a distorted concept of strength. Without the crucible of large-scale war, leaders conflate bluster with courage. Posturing and chest-thumping replace the tempered resolve forged in battle. This masculinity crisis encourages leaders to prove their mettle through brinkmanship, pushing strategic tensions to the brink under the assumption that someone else will blink first.

    Yet history warns us. Before World War I, European leaders believed war would be short and decisive. They lacked the mental model for industrial slaughter. The result was unimaginable carnage. Today’s faith in rational deterrence and limited warfare is equally untested against nuclear thresholds. The risk: assuming that what has never happened cannot happen—until it does.

    For investors and policymakers, these tail risks matter. Even a tiny probability of nuclear exchange dwarfs conventional cost-benefit calculations. Markets often discount extreme events, but the logic here fails: one nuclear flash, and investment theses vanish. Realist scenario planning must treat the unthinkable as possible, building robust hedges and diplomatic channels that anticipate irrational moves.

    Leaders must confront the fragility behind their confident theories. They can run hard-nosed simulation exercises exposing the realities of nuclear war, engage historians for depth, and deliberately cultivate humility. The aim: to ensure that strategic unpredictability—useful for realigning outdated frameworks—is anchored by a genuine appreciation for the catastrophic potential of miscalculation.

    The stakes transcend any single presidency. Trump’s style highlights an underlying vulnerability in the global order: the illusion that every escalation can be managed. Without conscious effort to re-inject war’s existential reality into policymaking, we risk turning bravado and guesswork into the architects of our undoing.

    An American Renaissance

    Amid volatility, uncertainty, and the rattling of old foundations, the United States finds open ground for reinvention—fertile space where scientific audacity, inventive genius, and fearless exploration can flourish without constraint. Freed from the constraints of incrementalism, the United States can embrace the role of a frontier civilization once again: a nation unafraid to ask audacious questions, challenge sacred doctrines, and test the limits of the possible.

    For decades, America’s once-thriving innovation engine has stalled, suffocated by excessive regulation, rigid academic dogmas, and bureaucratic inertia. Critical fields—from theoretical physics to biotechnology—have languished behind walls of entrenched interests and outdated paradigms. Now, with Trump’s second term shaking the foundations of the status quo and Elon Musk’s contrarian vision gaining traction, the United States faces a rare chance to reignite its pioneering spirit. Instead of tinkering at the margins, Trump and his team propose far-reaching reforms: radically simplified tax codes, streamlined regulations, and reimagined immigration policies designed to attract the brightest global talent and unleash their creative potential.

    This intellectual and cultural thaw reverberates through the sciences. The same nation that once sent men to the Moon now contemplates multi-planetary homesteading. If the old gatekeepers who have stalled theoretical physics for half a century can be bypassed, research into next-generation propulsion, dark chemistries, and new fundamental frameworks beyond the standard model can finally flourish. The tyranny of stagnant string theory, the deep entrenchment of cautious committees, and the decades of intellectual ossification may give way to what some call “cowboy science”: a return to risk-taking, intuition-led breakthroughs, and the heroic ethos of individual genius.

    As these reformist energies spread, the U.S. can leverage a more fluid, reciprocal global trading landscape. Realigned alliances and supply chains engineered for resilience—not just cost-minimization—create fertile conditions for deep-tech ventures, advanced AI labs, and next-generation energy systems. Investors, entrepreneurs, and scientists will gravitate toward America’s rejuvenated ecosystem, drawn by the promise of intellectual freedom and the exhilarating possibility of rewriting fundamental laws of physics. Under these conditions, even concepts dismissed as far-fetched—interstellar travel, room-temperature superconductors, and quantum computing at scale—begin to feel tangible rather than utopian.

    Culturally, a merit-driven ethos replaces hollow credentialism. With intellectual courage in fashion and bold ideas encouraged rather than stifled, the private and public sectors unite in a grand experiment of renewal. The old narrative that the 20th century’s greatest leaps cannot be repeated or surpassed is discarded. Instead, the horizon expands: the stars become destinations, the atom a playground, and the genome a toolkit.

    Of course, nothing guarantees success. The same high-variance environment that enables breakthroughs also courts failure. But the alternative—endless stagnation under rigid orthodoxies—is far less appealing. Risk and reward remain inseparable. Yet if America seizes this rare moment of disruption, the outcome could be a cultural and scientific flourishing that defines the 21st century. The world would witness an America not just rearranging old furniture but remodeling the entire house of knowledge and capability.


    My Perspective

    Embrace the uncertainty. Legacy frameworks, linear forecasts, and predictable policy arcs disintegrate before our eyes. In this new environment, strategic thinking must center on asymmetry, adaptability, and an appetite for chaos. The stable handrails of the past—fossilized alliances, orderly trade pacts, incremental reforms—no longer guide us. Instead, we confront a world where each assumption must be retested, each relationship retooled.

    Short-term, don’t be fooled by today’s optimism. A global recession in 2025 looks increasingly plausible. Just as radical tariff policies and gutting government agencies shake domestic supply chains, weakened global demand may trigger market shocks.

    I expect immediate disappointment in the headlines: over-leveraged sectors are at risk, euphoria is unsustainable, and cracks beneath Bidenomics’ veneer are about to surface. Yet in this churn also lies profound opportunity. High-variance environments punish rigidity and stagnation, while rewarding those who sense the underlying logic: volatility can be harnessed, not merely weathered. Consider three critical asymmetries shaping the investment and business landscape:

    1. Bidenomics Masked Fragility

    Beneath surface-level confidence, America’s economic foundations have softened. Over 60% of recent jobs growth is pinned to government expansion, residual pandemic adjustments, and immigration—rather than genuine private-sector dynamism. Key signals such as spiking credit rejection rates and record-high consumer credit APRs (averaging 23.4%) expose deep vulnerabilities.

    My Perspective: Be careful and consider shorting sectors drunk on euphoria and leverage. Hedge through defensive allocations in utilities, select commodities, and volatility instruments. Expect the market’s reality-check to be swift and severe.

    2. Trump’s Shock Therapy

    Trump’s proposed moves – >60% tariffs on Chinese imports, mass deportations, a dramatic agency cull – risk near-term upheaval. Inflation may flare as re-shored supply chains struggle with labor gaps and capacity constraints. Yet these same policies could, over time, liberate America’s productive energy. Leaner agencies, streamlined regulations, and targeted immigration reforms might unleash a “productivity renaissance.”

    My Perspective: As the tariff storm gathers, go long on domestic industrial plays, automation tech, and logistics hubs that stand to benefit from re-shoring. Short inflation-sensitive assets and prepare for a recessionary downdraft. Hedge with precious metals, critical commodities, and volatility products. Meanwhile, larger positions in frontier technologies poised to flourish in a liberated innovation environment.

    3. The Geopolitical Pivot: The Dollar and BRICS

    China’s ascendancy as the dominant trade partner for over 120 nations, along with BRICS’ rising economic heft, indicates a shifting global gravity. Mounting U.S. refinancing needs and reduced foreign appetite for Treasuries challenge American financial stability. Yet, the U.S. retains unmatched capital markets and remains the ultimate safe haven in moments of panic. Trump’s readiness to deploy financial sanctions and trade barriers could paradoxically reinforce dollar dominance.

    My Perspective: Diversify currency exposure. Maintain core holdings in dollar-denominated assets but add hedges: gold, Bitcoin, rare-earth ETFs, and neutral currencies like the Swiss franc (CHF) or Singapore dollar (SGD).

    Conclusion: Engaging with the New Parameters

    We have entered a period that defies simple narratives. Trump’s reelection announces to the world: comfortable equilibrium is over. His brand of strategic unpredictability invites us to reimagine what American power, governance, and global influence can be. However, the end of safe assumptions means the start of dynamic possibilities.

    While the near-term disruptions will test even the most resilient systems, the long-term vision is undeniably bright for those who play the horizon. A renaissance of innovation, deep-tech breakthroughs, and industrial re-shoring is not only plausible but increasingly probable as legacy constraints fall away.

    A revitalized America, unafraid to challenge stagnation, could emerge as a global leader in space exploration, advanced physics, AI, and frontier sciences. Trump’s recalibration provides the foundation for a leaner, more dynamic economy capable of driving exponential progress.

    I believe: for investors, entrepreneurs, and visionaries, this is the time to look beyond the turbulence and focus on the extraordinary opportunities waiting on the other side of disruption.


    Investment Guidance

    Identifying Signals and Triggers

    • Short-Term (< 12 Months):
      • Prioritize Liquidity & Intelligence: Maintain higher cash reserves and invest in geopolitical risk analysis and scenario modeling. Deploy specialized teams or AI-driven tools to monitor trade policy changes, alliance realignments, and tariff announcements in near-real time.
      • Trade Shock Indicators: Watch for a surge in container freight rates or abrupt commodity price spikes as tariffs hit. When the Baltic Dry Index or forward freight agreements jump unexpectedly, it’s a sell signal for overly exposed consumer goods equities and a prompt to rotate into logistics-tech and North American manufacturing automation.
      • Sovereign Debt & Currency Pressure: Keep a close eye on U.S. Treasury auctions. If foreign participation dips below historical averages by more than 20%, prepare to adjust currency hedges. Add allocations to “safe haven” currencies (CHF, SGD), selected gold or rare-earth ETFs, and volatility indices. Reduce reliance on sectors heavily tied to stable policy (e.g., heavily subsidized industries) and increase optionality in energy metals and critical supply chain components.
    • Medium-Term (2–3 Years):
      • Innovation Inflection Points: Direct capital into exponential technologies and applied sciences; advanced materials, quantum computing, biotech, and AI-driven compliance tools. As bureaucratic complexity shrinks, these sectors stand to benefit outstandingly from faster innovation cycles and greater capital efficiency. A spike in private venture rounds in fields such as advanced materials or ultra-capacitor energy storage signals imminent ecosystem tipping points.
      • Geographical Differentiation: Identify markets that handle uncertainty well—e.g., countries with robust legal systems, flexible labor markets, and strong digital infrastructure. These places can serve as operational hubs from which you can rapidly scale or contract as global policies shift.
      • Regulatory Overhauls: Monitor legislative dockets. If immigration reforms fast-track visas for STEM PhDs and if R&D tax credits deepen annually, expect a 2–3 year lag before the next wave of intellectual capital floods U.S. labs. Increase exposure to biotech and quantum computing startups shortly after such reforms pass.
    • Long-Term (5+ Years):
      • Global Power Reorder: If emerging markets, spurred by U.S. unpredictability, coalesce around alternative trade blocs that stabilize after 5+ years, that’s your cue. Prepare for a world of modular alliances. Align long-horizon infrastructure bets with these new power centers.

    Scenario-Based Policy and Investments

    • “China Retaliation” Scenario: As soon Beijing imposes further capital controls and technology export bans, pivot quickly:
      • Reduce exposure to companies dependent on Chinese rare-earths.
      • Expand positions in U.S. rare-earth suppliers and recycling tech (long specialized recycling firms).
      • Initiate currency hedges: Increase gold allocation, add JPY or CHF positions.
    • “Nuclear Brinkmanship” Scenario: Early indicators: intensified troop movements, erratic diplomatic communications:
      • Increase cyber-insurance and cybersecurity equity holdings as cyber-warfare risks peak.
      • Secure put options on major indices; a 15–20% market drop in a flash-crisis scenario can be mitigated by well-structured options positions.
      • Reassess treasury holdings and ensure a diversified emergency liquidity plan—short-duration U.S. debt, gold, and stablecoins backed by reputable custodians.

    Positioning for the Innovation Renaissance

    • Initiate a strategic allocation into venture funds, selected stocks, and indexes focusing on deep tech; quantum sensors, quantum-safe encryption, next-gen propulsion (for aerospace), and synthetic biology platforms.
    • Monitor and partner with universities and national labs. The moment immigration policies simplify STEM recruitment, double down on early-stage biotech and materials R&D firms that secure top-tier postdoctoral talent.

    Embrace a Layered Risk Architecture

    Create a layered defense:

    • Core stable assets (30–40%)
    • Growth equities and frontier tech (10–20%)
    • Defensive hedges in commodities, currencies, and volatility instruments (5–10%)
    • Agile, tactical allocations that adjust quarterly based on policy signals (remainder)

    Cultural and Organizational Adaptation

    In your firm and institution:

    • Launch scenario planning committees that simulate tariff impacts, alliance breakdowns, or regulatory leaps.
    • Recruit analysts with backgrounds in geopolitics, physics, and biotech—do not rely on MBAs and economists.
    • Encourage experimentation within your decision-making processes—pilot new portfolio strategies on a small scale before scaling up.

    For Non-U.S. Founders & Foreign Firms:

    • Incorporate in the U.S. and use reputable U.S. startup accelerators and venture networks to navigate evolving immigration policies and establish a strong launchpad.
    • Focus on mid-tier American cities seeking innovation and talent inflows, where streamlined approvals and incentives provide a foothold.
    • Build solutions that complement, stabilize, or enhance U.S.-based production and logistics systems, emphasizing resilience and cost-effectiveness.
    • Offer platforms or products that facilitate seamless cross-border transactions, digital collaboration, or remote operations as global markets rewire.
  • AI-to-AI Communication

    Nowadays, most emails I receive – including technical and legal ones – are undoubtedly written by ChatGPT. Which I’m okay with – but I find it rather funny that I now have to read what an AI has written only to input the context myself into my AI system. We are effectively constraining AI systems to communicate via human intermediaries – which is a laughably stupid and cognitively inefficient approach.

    I think it is wasted energy to make AIs even better at mimicking human communication – this energy is better used in developing AI-to-AI communication protocols that bypass human language entirely. Instead of exchanging emails written in human language, AIs should directly exchange action items, structured data, intent vectors, or probabilistic models. How valuable is it really in making AI communication more human-readable? I believe it is about freeing AIs to communicate in their “native language” while humans simply set high-level objectives and constraints. No latency, no information loss, no mental drainage, more time for actual human communication and interaction.

  • The Future Belongs to the Intuitive

    Everything looks as if the future belongs entirely to machines, where decisions will be driven solely by logic and data. This makes sense from a logical perspective. AI can already shift through terabytes of real-time data in seconds. It can identify patterns the human eye cannot see. As these systems become more sophisticated and continue to improve exponentially, it is fair to predict that in the near-term future we will not only push data- and logic-driven decision-making to a point of saturation, we will also experience a natural tendency to lean heavily on logic-based recommendations from advanced AI systems.

    I fear that the more we rely on these data-driven arguments, the more we risk sidelining a crucial element of decision-making: human intuition. We risk that algorithms and AI systems become the default arbiters of choice. The more powerful their capabilities become, the higher will be the temptation to dismiss our intuition. We will end up making decisions purely on logic, with every action optimized by data.

    Here is the contrarian truth: as AI systems gets better at advanced reasoning, processing even more data, and identifying patterns, pure logical and knowledge based analysis becomes commoditized.

    We are already in a world where decisions are made for us by algorithms and AI systems. Not only do they decide which video we should watch next on YouTube, they also provide decision makers with data and insights – whether it is in finance, trading, marketing, hiring, or medicine. And why not? AI systems process data faster, more accurately, and with few biases than any human being ever could. They can recognize patterns that would take humans years to discern. Advanced algorithms spit out logical predictions based on mathematical conclusions. For tasks like optimizing logistics, predicting customer behavior, and analyzing stock market trends, it is a no-brainer–AI wins.

    It seems logical to assume that pure data and computation will lead to the best decisions. But this is flawed because there is something missing in this equation. Decisions are not always about logic. The most important decisions in life and business are anything but logical. They are guided by subtle, almost imperceptible signals we cannot fully explain, but we feel. This is intuition, the gut feeling we experience when something just feels right or feels wrong. While it is tempting to dismiss these feelings as irrational, they often turn out to be right.

    Optimizing decisions based on more data and more logical reasoning is thereby flawed, and I fear that the more we lean on AI systems to guide our choices, the more we risk sidelining the most powerful tool humans possess: intuition.

    Scientific discoveries, for example, are not made as a result of logical reasoning. They are regularly the result of an “aha moment” of insight when knowledge seems to come from nowhere. Or think of the countless stories of entrepreneur who make bold decisions based on nothing but an intangible sense of certainty. Steve Jobs went against market research and expert advice when he decided to launch the iPhone. Elon Musk bet his fortune on SpaceX when logic screamed that the odds were against him. There are investors who pull out of a seemingly attractive opportunity just moments before it tanks, driven by nothing more than a gut feeling. Also, good music just comes to the musician, and it is not created by technical skill.

    Through intuition, we can feel the subtle energetic currents of events before they manifest. It’s the mother who knows something’s wrong with her child before receiving the call from school, or the traveler who avoids a particular flight, only to find out later it crashed.

    These aren’t coincidences or anomalies—they are examples of intuition at work. In these moments, we are not responding to what is, but we are aligning ourselves with what could be. We sense reality before it unfolds. This intuitive intelligence is more than a vague “gut feeling”; it is an ability to sense what isn’t in the data, to feel the reality before it is fully formed. With our intuition, we tap into a deeper field of information that transcends the conscious mind.

    Our rational mind is not very good at listening to our intuition. It is busy making sense of the things in our material world. It is busy with its endless internal monologue and anxiety. Our mind is constantly generating thoughts – and the more data we have access to (think of the infinite information feeds from social media, the news, and now generative AI) the more difficult it becomes to access our intuitive intelligence.

    Furthermore, I fear that, the more ubiquitous AI systems and the more convincing their logic-based arguments become, the more we will trust and rely on them blindly. When an algorithm presents a data-backed recommendation, it is hard to contradict it. The numbers add up, the patterns are clear – it feels almost reckless to go against the machine. But that is exactly the risk.

    The stronger the logical basis for decision-making becomes, the harder it will be to justify following your gut. The result? We will end up in a world where every decision is optimized for efficiency and logic – at the cost of creativity, foresight, and frankly, the human element.

    We risk entering a near-term future where we become slaves to the data, losing the ability to make decisions that transcend the immediate facts in front of us and instead tap into a deeper, more holistic understanding of reality.

    Exactly in fields that require the most crucial decisions, intuitive intelligence is of higher importance than pure data-driven logic. In business strategy, creative innovation, and geopolitical decisions, intuition plays a unique and uttermost important role. It tells use when an idea feels right, even if the numbers aren’t there to back it up, or we abandon a “logical” choice because something feels off.

    The best decisions aren’t made purely on logic or data. They’re made by integrating the analytical with the intuitive. AI will continue to become an ever more invaluable tool, but it’s just that – a tool. It processes the world as it is, based on observable facts and historical data. But intuition allows us to perceive the world as it could be. It taps into potential futures, subtle energetic shifts, and possibilities that aren’t visible in the data. Data can get us to the next step, but intuition lets us leap to entirely new paths. And as AI carves out logic’s territory, intuition becomes even more vital.

    I don’t say we should abandon data or AI systems – far from it. Intuitive decision makers aren’t anti data. They leverage data and logic without being trapped by it. They use it as a foundation, but they use their intuition to connect the dots and sense realities which machines cannot compute. They use data as a guide but trust their intuition to make the final decision. Their intuition will navigate the uncertainties and unknowns that lie beyond the reach of logic. The best leaders will be those who can access and trust their intuition even though logic is against it.

    Those who can access and act upon their intuitive intelligence will find themselves making the right decision when it matters the most—even if logic disagrees: preventing a nuclear conflict by sensing hidden motives when every visible sign points toward war, sparking a scientific breakthrough that defies conventional knowledge, designing a world-changing technology that others dismissed as impossible, or uniting adversaries to forge an unexpected, lasting peace against all rational odds.

  • The Exploitation Behind Legalizing Organ Trade

    I recently saw a debate on whether organ trade and an organ market should be legal. Here’s my take on the issue.

    Yes, there’s a clear mismatch between supply and demand. But who would be the ones selling their organs? People in precarious situations, without the luxury of long-term choices. The wealthy have no reason to sell their organs—it’s the poor and those in debt who would. An organ market would systematically create an incentive to exploit the economically vulnerable, turning their bodies into commodities.

    This brings us to the concept of autonomy. People facing financial desperation have little autonomy. A wealthy individual who has never experienced financial hardship wouldn’t sell their kidney—there’s simply no need (perhaps they’d donate it to a family member or close friend). But the poor don’t have that choice. Their “choice” isn’t voluntary; it’s coerced by poverty. And that is not only economically disastrous but morally catastrophic.

    The very idea that body parts could be marketable contradicts the essence of human dignity. It reduces the most vulnerable members of society to mere commodities. An organ market would lead us straight into a form of slavery—though subtler, more insidious. It’s a slavery packaged as economic freedom. It may look like freedom, but it’s nothing more than exploitation.

  • Running Out of Our Circle

    Running in circles is an expression that is often used to express when no matter what we do, nothing changes. We run in a circle, always ending up where we started.

    Imagine the circle lines as boundaries, not physical boundaries but mental barriers. In our life, we often run within our circle of possibilities. Anything outside our circle seem impossible. Outside the circle is anything that seems unattainable.

    For some, healing a chronic disease may seem unattainable, for others it is a nice house, finding one’s soulmate, or merely financial abundance.

    Over our lifetime, through our upbringing, we have defined our circle of possibilities. We have defined what is within our possibility and what is outside our possibility.

    But this is just a line we drew. It is a mental barrier that does not exist outside our mind. In order to attain what seems unattainable we have to expand our circle of possibilities. We have to pull what is outside our circle inside.

    Imagine it like this: anything that is within our circle is easy and comes effortless. For example making a coffee, driving a car are within our circle of effortless possibilities.

    Other things seem out of reach. They are outside our circle of possibilities. They look extremely hard and impossible to reach.

    What we need to do is reframe our understanding of what is within and what is without our circle. We pull seemingly impossible things inside our circle and thereby we are expanding the size of our circle exponentially. We do this by following our excitement.

    Not everything can be pulled inside our circle. But anything we are absolutely excited and passionate about can be pulled inside and made attainable.

    You might think that you want to be the founder and CEO of a large successful company. But if this is merely a desire that comes from mimesis – in other words a desire that we have because we see other people have or desire it – not from our true inner being.

    We will try forever to pull this inauthentic desire inside our circle, but we will fail because it is against our nature. Listening to our true excitement is key. We have to follow what is truly authentic to us – what we are truly excited about from our whole heart – and pull it inside our circle.

    You may find true excitement and joy playing the piano or researching a certain subject. But true mastery of the piano or earning a livelihood with it may seem like an impossibility. Don’t let this hold you back. If this is what excites you the most, make the decision to pull it into your circle, define it is easily attainable, possible.

    Inside our circle, doing and attaining our desires is as natural and easy as making a cup of coffee.

    Our inner circle represents our current reality. It is both endless and limiting. Endless in terms of repetition and confinement of boundaries.

    Think again of walking in a cricle, you always end up in the same spot, never really advancing. We try to improve the conditions within our circles, but improvements within our circles is like improving a prison cell.

    True freedom comes from expanding that circle. Or stepping out of that circle into an entirely new one.

    That is difficult because we are like fish in an aquarium unaware of the world behind. We only see what is familiar, what is within our circle, and everything beyond that feels alien or unattainable even though we desire it.

    The real truth is that it takes the same energy to live and operate within our current circle as it takes to live within a much larger circle or to step. It takes the same effort to be in our current circle as it takes to be in a completely different, much larger circle.

    First, you need to identify that you are inside of a circle. What are your current habits and goals? What is your current reality?

    Once you are aware, the next step is to identify what is outside your circle. What is it that you desire but looks unattainable, impossible?

    Now we define a new circle. In this new circle, our goals, our habits are aligned with our authentic aspirations, our true excitement. We create a new reality.

    Stepping out of this circle requires risk. It means breaking free from the familiar, and pursing something that may seem uncomfortable or unattainable.

    We leave our circle – we leave our comfortzone.

    We can do this in small, consistent steps or we can make a sharp turn–an instant shift in our approach to living, like flipping from being chased to becoming the one who chases.

    The real key to escaping our limiting circle is focus.

    Where we focus our mental energy on determines the reality we will experience. By only focusing on improving our current reality, we remain locked in. But by expanding our vision to something outside our current circle, outside our current reality, we open up the possibilities of stepping into a new, much larger circle of possibilities.

    What seems impossible now, becomes as effortless as making a cup of coffee.

    The decision to break free starts with the realization that we are contained in a circle and the decision that we are ready to stop running in circles.

  • Understanding: Human vs. Machine

    Whether we understand a text depends on several factors. First, do we recognize and understand the alphabet? Do we understand the language? Assuming both, we can read the words that are written. But this doesn’t mean we understand the text. Understanding what is written depends on whether we have the necessary contextual knowledge and conceptual framework to interpret the meaning behind each word. On a ‘word level’ alone, language is more than a sequence of symbols. Each word and each combination of words conveys in and of itself ideas that are shaped by cultural, historical, and experiential factors.

    Consider the word “football”. In the United States, “football” refers to American football, a sport with an oval ball and heavily physical play. In the UK (and most of the world), “football” is a game played primarily with the feet, a round ball, and two rectangle goals. The same word triggers entirely different images and cultural associations depending on the context in which it is used.

    Or consider the word “gift”. In English, “gift” means a present, something given voluntarily to another person. In German, “Gift” means poison. The same word evokes – again – entirely different meanings depending on the language.

    Even if we can read and comprehend the literal meaning of words, true understanding requires an ability to grasp the underlying concepts, nuances, and intentions, as well as to connect the information to prior knowledge or experiences. If we don’t have these deeper connections, we may be able to read the text, but fail to genuinely “understand” it in a meaningful way.

    When we talk about “understanding” a text, we are simply processing patterns of language based on previous experiences and context. Meaning emerges when we can connect the symbols to prior knowledge and concepts we have already internalized. In other words, the idea of “meaning” arrives from a vast database of stored experiences.

    This becomes clear when we deal with complex technical, scientific, or philosophical texts. Understanding these require not only familiarity with the language, but also a deeper technical or conceptual foundation.

    For example, take a physics paper discussing “quantum entanglement.” The words themselves may be understandable to anyone familiar with basic English, but without a solid grasp of quantum mechanics and concepts like wave-particle duality, superposition, or the mathematical formalism behind quantum states, the meaning of the text is lost. The read can follow the sentences, but the true meaning remains obscure.

    In essence, understanding a text – especially a complex one – goes beyond recognizing words or knowing their dictionary definitions. It depends on an interplay between language and thought, where meaning is unlocked through familiarity with the underlying concepts, cultural context, and prior knowledge. True understanding is furthermore a learning process. Understanding not only demands a proper intellectual preparation, but also the ability to integrate new information from the text with what we already know.

    With that in mind, can a machine understand text in the same way humans do?

    A large language model (LLM) also processes patterns of language, recognizing text based on vast amounts of data. On a surface level, it mimics understanding by assembling words in contextually appropriate ways, but does this equate to “understanding” in the human sense?

    When humans read, we don’t just parse symbols, we draw from a rich background of lived experiences, emotional intelligence, and interdisciplinary knowledge. This allows us to understand metaphors, infer unstated intentions, or question the credibility of the text.

    Back to our example of “quantum entanglement”. When a trained physicist reads the physics paper, they relate the written sentences to physical phenomena they’ve studied, experiments they’ve conducted, and debates he is involved in.

    By contrast, a LLM operates by recognizing patterns from its vast training data, generating contextually relevant responses through probabilistic models. While it does this impressively, we might argue that for true understanding, a LLM lacks the aforementioned deeper conceptual and experiential framework that humans develop through real-world experience and reasoning.

    While it is obvious that LLMs do not experience the world as humans do, this does not mean that LLM are not or will never be capable of understanding and reasoning.

    LLMs do engage in a form of reasoning already, they manipulate patterns, make connections, and draw conclusions based on the data they’ve encountered. The average LLM of today can process abstract ideas like “quantum entanglement” – arguably – more effectively than the average human merely by referencing the extensive patterns in its data, even though they are not capable of linking this to sensory and emotional experience.

    Sensory and emotional experiences, such as the joy of scoring a first goal in a 4th grade sports class or the sorrow of watching one’s favorite team suffer a 0:7 defeat on a cold, rainy autumn day, create deep personal and nuanced connections to texts about “football.” This allows humans to interpret language with personal depth, inferring meaning not just from the words themselves, but from the emotions, memories, and sensory details attached to them.

    The absence of emotional grounding may limit LLMs in certain ways, but does it mean they cannot develop forms of understanding and reasoning that, while different, can still be highly effective?

    For example, a mathematician can solve an equation without needing to “experience the numbers”, meaning they don’t need to physically sense what “2” or “π” feels like to perform complex calculations. Their understanding comes from abstract reasoning and logical rules, not from emotional or sensory connection.

    While a LLM cannot yet solve mathematical problems, in a transferred sense, a LLM might “understand” a concept by connecting ideas through data relationships without needing direct experience. It recognizes patterns and derives logical outcomes, like a mathematician working through an equation.

    One example for this is language translation. While a professional human translator might rely on personal cultural experience to choose the right phrasing for nuance, in many cases, LLMs are already able to process and translate languages with remarkable accuracy by identifying patterns in usage, grammar, and structure across million of texts. They don’t have personal experience of what it is like to live in each culture or speak a language natively, they nevertheless outperform humans in translating text (think of speed).

    Understanding, then, is the process of combining knowledge, reasoning, and in our human case, personal experience. In that sense, is it impossible for LLMs to understand and reason, or lies the difference more in what LLM ground their reasoning on?

    Humans reason through real-life experience, intuition, emotions, and sensory input, like the joy of scoring a goal or the gut-feeling resulting from a suspicious facial expression. LLMs, on the other hand, don’t have this kind of grounding, they operate purely on data.

    Again, does this mean LLMs cannot reason? LLMs – despite lacking this personal grounding – still show early forms of reasoning. This reasoning is powerful, especially in cases where personal experience is not required or less important. In fact, understanding may not even require physical or emotional experiences in the same way humans are biologically conditioned to need them. If reasoning is fundamentally about making accurate predictions and drawing logical conclusions, then LLMs are – arguably – already surpassing humans in certain domains of abstract reasoning.

    With advancements in AI architecture, it is likely that LLMs will one day develop a form of “conceptual grounding” based purely on data patterns and logical consistency. We will arrive at new forms of understanding and reasoning that differ from, but rival, human cognition.

    The limitations of LLM are what makes human human: an inherent drive to pursue truth and question assumptions. While LLMs – arguably – reason by connecting dots and generating solutions, they lack the intentionality and self-awareness that drives human reasoning.

    Ultimately, the question of whether machines can in fact understand and reason is less about how accurately it is replicating human cognition and more about recognizing and harnessing a new form of intelligence.

  • Government as an Investor?

    There is a real debate going on whether the German government should provide Lilium – a 9-year-old, publicly-listed money loosing eVTOL company, without a single successful realistic test-flight – a €150M loan. (It decided not to, good.)

    The real issue I see is that public funding socializes risk and losses, forcing taxpayers—like my parents (!!)—to cover the bets of government employees who lack skin in the game, all under the guise of ‘deep tech’ and ‘innovation.’

    Worse, I don’t want German taxpayers’ money supporting a so-called ‘German’ company headquartered in the Netherlands and listed in the USA.

    IF a company seeks public loans, all its shareholders and executives should be personally liable for the full amount (and what they promise)—no exceptions. Only then can we can talk about a loan from tax-payers.

    Furthermore, it seems that private and institutional investors are not willing to provide any more funding to achieve the alleged test flights in 2025. If private investors are not willing to put any more money into the company – why should the tax payer?

    What should Germany do? Lower taxes. Deregulate. But don’t become a VC.

  • Fertility Rates and Real Estate

    Global fertility rates are plummeting. Countries like the U.S. (1.64), China, Japan, and Spain (all below 1.2) face drastic population reductions – up to 80% over three generations. South Korea’s rate of 0.7 could trigger a 96% decline. This is not only a demographic issue but also an economic time bomb.

    For real estate, fewer people means fewer homes needed. An aging population will favor downsizing and specialized housing, while larger family homes sit vacant. Urban areas may initially absorb the shock, but even cities will face declining demand. Property values and rental incomes will inevitably fall, hurting investments and slowing construction. Immigrant-driven growth, which propped up Europe’s housing markets for decades, is no longer a reliable cushion as the fertility rate plunges across the globe and across ethnicities.

    As demand shifts, so will the nature of housing. Assisted living, multi-generational homes, and adaptive reuse projects will dominate, while sprawling suburban developments could become ghost towns. Governments may attempt to incentivize higher birth rates or attract foreign buyers, but the long-term trajectory points toward overcapacity and falling values.

  • “Researched Climate Models”

    So-called “researched climate models” are nothing more than digital crystal balls, fed by human arrogance and mere morsels of data. These models are as “researched” as the deep ocean – we’ve barely scratched the surface.

    The climate system is a labyrinth of countless variables and feedback loops:

    1. Solar cycles and variations in solar output
    2. Earth’s orbital changes (Milkankovitch cycles)
    3. Galactic cosmic rays influencing cloud formation
    4. Plate tectonics altering ocean currents and atmospheric circulation
    5. Volcanic activity injecting aerosols and gases
    6. Geomagnetic field fluctuations affecting atmospheric protection
    7. Deep ocean currents and heat distribution
    8. Ocean acidification
    9. Sea ice dynamics and albedo effects
    10. Greenhouse cas concentrations (CO₂, methane, water vapor)
    11. Aerosole distributions from natural and anthropogenic sources
    12. Ozone layer variations
    13. Forest cover changes affecting carbon sinks
    14. Soil microbiome dynamics influencing greenhouse gas emissions
    15. Phytoplankton populations and ocean sequestration
    16. Permafrost thawing releasing stored greenhouse gases
    17. Ice sheet stability and sea level changes
    18. Glacial retreat altering local climates
    19. Human greenhouse gas emissions from industry and agriculture
    20. Land use changes affecting albedo and local climates
    21. Geoengineering attempts (e.g. cloud seeding, stratospheric aerosol injection, etc.)
    22. Potential quantum influences on chemical reactions in the atmosphere
    23. Quantum entanglement in biological systems
    24. Schumann resonances and their potential climate impacts
    25. Ionospheric changes affecting atmospheric electricity
    26. Meteor impacts and dust influx
    27. Potential dark matter interactions with Earth’s core

    The climate system is a multi-dimensional, multi-scale phenomenon where microscopic quantum effects may cascade into global changes and cosmic events can trigger earthly responses. Our current models, focused primarily on greenhouse gases and simple feedback loops, are akin to trying to predict the outcome of a symphony by looking only at the trombone section.

    The sheer number of variables and their non-linear interactions make accurate long-term prediction an impossible task.

    MAYBE quantum computing and superintelligent AI might someday crack the climate code. But today’s models? They’re monuments to our stupendous arrogance. We’re using abacuses to calculate infinity, patting ourselves on the back for our “accuracy.” It’s not just misguided—it’s dangerously delusional.

    Our current understanding is but a drop in the ocean of what there is to know. Instead of boasting about “researched climate models,” we should humbly speak of “preliminary climate hypotheses.”