Big Ideas

The Agentic Financial Revolution: Beyond Human-Centric Finance

How AI agents and programmable money are reimagining the fundamental architecture of financial services

Picture this: You’re running a small business and need emergency funding to fulfill a large order. In today’s world, you’d spend weeks gathering documents, waiting for loan approvals, and potentially missing the opportunity entirely. But what if your AI agent could secure funding in minutes, automatically negotiating terms based on real-time analysis of your business data and the specific opportunity at hand?

This isn’t science fiction. It’s the emerging reality of agentic finance, where autonomous AI systems operate alongside programmable money to create financial services that adapt, optimize, and execute at machine speed.

Why Traditional Finance Is Fundamentally Limited

Traditional finance wasn’t designed for the digital age. It was built around human limitations that made sense when banks were physical buildings and transactions required paper trails. But these human-centric constraints have created a financial system that operates more like a horse-and-buggy in an age of autonomous vehicles.

Consider how deeply these limitations run. Our financial infrastructure operates on business hours because humans need sleep. Settlement takes days because human-operated clearing systems require time for verification and reconciliation. Geographic boundaries matter because human institutions are bound by jurisdictional regulations and physical presence.

The constraints go beyond operational inefficiencies. The entire conceptual framework of finance assumes human decision-makers at every critical juncture: loan officers assessing creditworthiness, traders executing market strategies, compliance officers monitoring transactions, and risk managers setting policies. This creates systemic bottlenecks where financial services must be simplified, standardized, and batch-processed to accommodate human cognitive and operational limits.

The result is a financial system built on approximations and delays. Credit scores reduce complex financial behavior to three-digit numbers. Investment products are packaged into broad categories rather than personalized strategies. International transfers route through correspondent banking networks because no single human institution can manage global liquidity in real-time.

The Building Blocks of Financial Intelligence

Agentic financial systems represent more than just technological upgrades. They’re a paradigmatic shift from finance as a human-mediated service to finance as an autonomous, intelligent ecosystem. Rather than humans using financial tools, we have autonomous economic actors capable of independent decision-making, learning, and adaptation.

Programmable money forms the foundation. Cryptocurrencies and stablecoins create money that can be programmed with logic, enabling automatic execution of complex financial operations without human intervention. Your money can literally follow instructions: “Pay my rent on the first of every month, but if my account balance drops below $1,000, source the payment from my high-yield savings.”

Autonomous decision-making provides the intelligence layer. AI agents can process vast amounts of data, assess risk, and make financial decisions at machine speed while learning from outcomes to improve future performance. They don’t just execute pre-programmed instructions. They interpret context, negotiate terms, and optimize outcomes based on evolving conditions.

Trustless coordination eliminates intermediaries. Blockchain infrastructure enables agents to transact and coordinate without requiring trust in centralized intermediaries, creating truly global, 24/7 financial markets where verification happens through cryptographic proof rather than institutional reputation.

Four Principles That Change Everything

This technological foundation enables financial services to operate on entirely new principles:

Real-time everything. Traditional finance operates in batches: daily settlements, monthly statements, quarterly risk assessments. Agentic systems operate in continuous time, with every transaction, market movement, and risk factor updating instantly across the entire system. Your investment strategy doesn’t wait for quarterly rebalancing; it adapts moment by moment.

Mass personalization. Human-operated systems require standardization to achieve scale. Everyone gets the same checking account features, the same loan terms within broad categories. Agentic systems can deliver mass personalization, with each financial product dynamically customized to individual circumstances and preferences. Your mortgage rate adjusts not just to market conditions, but to your specific risk profile and relationship with the lender.

Global by default. Traditional finance is bound by geography due to regulatory and operational constraints. Agentic systems can operate globally from inception, with agents automatically navigating regulatory requirements across jurisdictions. Your small business can access the best lending rates globally, not just from your local bank.

Verification over trust. Traditional finance relies on institutional trust and reputation. You trust Bank of America because it’s been around for decades. Agentic systems use cryptographic verification and transparent algorithms, making trust unnecessary while providing greater assurance. You don’t need to trust the lender; you can verify exactly how they assess risk and execute agreements.

Three Stories From the Future

To understand how radically different this world could be, let’s examine three scenarios that seem mundane but reveal the profound shift happening beneath the surface.

The 60-Second Remittance

Today: Maria in Los Angeles wants to send $500 to her family in the Philippines. She drives to Western Union, waits in line, pays a $35 fee, fills out paperwork, and her family receives the money 3-5 days later. The process involves multiple intermediaries: Western Union, correspondent banks in both countries, local agents, and regulatory compliance at each step. Each intermediary extracts fees and adds processing time.

Tomorrow: Maria’s AI financial agent detects her recurring remittance pattern and automatically optimizes the transfer. The agent converts dollars to USDC, routes through the most efficient DeFi protocols, and converts to Philippine pesos upon arrival. All in under 60 seconds for a total cost of $0.50.

But here’s what makes it truly revolutionary: the agent doesn’t just execute transactions. It learns from market conditions, builds relationships with other agents for better rates, and coordinates with Maria’s family’s agent to optimize timing based on local exchange rates and their cash flow needs. The system gets smarter with each transaction.

The Instant Business Loan

Today: Ahmed runs a small import business and needs $50,000 to fulfill a large order. He spends weeks gathering financial statements, tax returns, and business plans. A human loan officer reviews his application over several days, using standardized credit scoring models that miss his business’s seasonal patterns. The bank offers him a fixed-rate loan with standard terms, requiring personal guarantees. The process takes 30-45 days, during which the opportunity may disappear.

Tomorrow: Ahmed’s business agent continuously monitors his cash flows, inventory levels, and market opportunities. When the large order arrives, the agent immediately recognizes the financing need and broadcasts a request to a network of lending agents.

Multiple AI lenders analyze Ahmed’s real-time business data, examine the specific transaction details, and even assess the creditworthiness of his customer. They compete to offer personalized loan terms. Perhaps a 30-day loan at 8% APR secured by the incoming inventory, automatically converting to longer terms if needed. The entire process completes in minutes, with the lending agents coordinating directly with Ahmed’s supplier’s agents to optimize the entire supply chain.

The Living Retirement Plan

Today: Sarah, 35, meets with a financial advisor once a year to review her 401(k). The advisor recommends a target-date fund based on her age, with a standard asset allocation that gradually becomes more conservative. The system assumes a linear career progression, standard retirement age, and average market conditions. Rebalancing happens quarterly, and strategy adjustments require scheduled meetings.

Tomorrow: Sarah’s retirement agent continuously monitors her income, expenses, career trajectory, and market conditions. It dynamically adjusts her investment strategy in real-time: increasing contributions when her income spikes, shifting allocations when market volatility changes, and negotiating better terms with her employer’s 401(k) provider.

The agent manages her entire financial ecosystem, coordinating with her tax agent to minimize liabilities, her insurance agent to adjust coverage as her wealth grows, and her career agent to identify income optimization opportunities. When Sarah considers a career change at 42, her retirement agent models hundreds of scenarios in seconds, showing exactly how different paths would affect her retirement timeline and lifestyle options.

Beyond Better, Faster, Cheaper

The transition from traditional to agentic finance represents more than incremental improvements in speed, cost, or convenience. We’re witnessing a fundamental shift in the nature of financial services themselves. From a world where financial institutions serve as gatekeepers and intermediaries to one where intelligent agents collaborate to optimize outcomes.

This eliminates the traditional trade-offs that have defined finance for centuries. You no longer have to choose between personalization and scale, speed and safety, global reach and local expertise. Agentic systems can be simultaneously global and personal, instant and secure, simple for users and sophisticated in execution.

The implications extend far beyond individual financial services to the structure of the entire financial system. Markets become more efficient as agents can process information and execute trades faster than any human. Capital allocation improves as AI can identify opportunities and assess risks more accurately than traditional methods. Financial services become accessible to billions of people currently excluded from traditional banking, as agents can profitably serve micro-transactions and small accounts that banks ignore.

Most importantly, we’re not just digitizing existing financial services. We’re reimagining what financial services can be when freed from the constraints of human-operated systems. The future of finance isn’t about better banks; it’s about intelligent money that works on your behalf, 24/7, across global markets, optimizing every aspect of your economic life.

The question isn’t whether this future will arrive, but how quickly we can build the infrastructure to support it. The technologies exist today. The only constraint is our imagination in applying them.

The agentic financial revolution is already beginning. Early experiments in DeFi, robo-advisors, and algorithmic trading are just the first glimpses of what becomes possible when we combine AI agents with programmable money. The institutions that understand this shift and prepare for it will define the next era of finance.

Big Ideas · Politics

An Ugly, Contradictory Choice

Before the United States had a constitution, it had a warning. The nation’s architects, fresh from a revolution against a distant, monolithic power, looked to the future and saw a new tyranny waiting to be born not on a battlefield, but in their own halls of government. John Adams, with grim foresight, called a “division of the republic into two great parties” the “greatest political evil under our Constitution.” George Washington, in his farewell, was even more explicit, cautioning that the “alternate domination of one faction over another” would inevitably become a “frightful despotism.”

They predicted a future where loyalty to party would supplant duty to country, where public debate would be enfeebled, and where the system would serve itself, not the people. Two and a half centuries later, their fears have been fully realized. The recent political clash between Elon Musk and President Donald Trump is not an anomaly. It is the endgame of the very system the founders warned us against. Musk’s threat to launch the “America Party,” a third-party challenge funded by his own immense wealth, forces a deeply uncomfortable question: Is the necessary cure for this frightful despotism as messy and dangerous as the disease itself?

To answer that, one must first accept the premise that the two-party system is the illness. It has become an entrenched duopoly that rewards polarization, stifles authentic debate, and presents the electorate with a series of false choices. It is the fulfillment of Adams’s dread. From this perspective, any significant threat to the system’s stability must be considered. Enter Elon Musk, a figure who, unfortunately or fortunately, is very good at breaking things. His proposed third party is not a polite request for reform; it is a crowbar aimed at the rusted gears of the duopoly. It is a chaotic, unpredictable, and deeply flawed attempt to introduce a variable into a closed system. The question is no longer whether this is the ideal way to shatter the duopoly, but whether, after decades of inertia, it is the only way.

Yet, this is only half of the equation. While the founders feared the system of parties, they also feared the men who would exploit it. This is where the paradox deepens. Washington explicitly warned that parties become “potent engines” through which “cunning, ambitious, and unprincipled men will be enabled to subvert the power of the people and to usurp for themselves the reins of government.” This forces a direct and uncomfortable examination of Musk himself. Is he a concerned citizen attempting to break a corrupt system, or is he the very “cunning, ambitious” man Washington described, using the public’s legitimate frustration as a potent engine for his own power? He is a figure who simultaneously commands platforms for free expression (x or twitter…whichever one you want at this point) while demanding they bend to his commercial and political will. This is the central tension: the “America Party” can be seen as both a potential cure for the disease of duopoly and a symptom of the founders’ fear of powerful men hijacking the republic. It is both a solution and a threat.

This leads us to the heart of the modern dilemma. Are we, as a republic, at a point where we can afford to be choosy about who breaks the wheel? Perhaps the most damning indictment of our system is that only a figure with Musk’s immense wealth could even attempt such a fracture, a reality that would have horrified the founders. This forces us to ask: Is a democratized process for systemic change even possible anymore? Or have we reached a point of such institutional decay that our only option is to leverage one man’s ego to achieve a collective good? It is a deeply cynical proposition, a Machiavellian bargain that trades principle for pragmatism. We are left to wonder if we should ride the coattails of a billionaire’s gambit, hoping he breaks the right things on his way to satisfying his own ambitions.

We find ourselves in the precise position the founders dreaded, where the very structure of our politics is the poison. A billionaire proposes a disruptive, self-serving, and potentially dangerous solution. The most uncomfortable truth of all is that, after 250 years of ignoring their warnings, this may be the kind of ugly, contradictory choice we are left with. It is no longer a theoretical debate. The choice is between the slow, predictable decay of the current system and the chaotic, unpredictable disruption offered by a flawed savior. The question is no longer which option is good, but which poison is less lethal.

#MentalNote · Big Ideas

The Liar’s Dividend: How AI Devalued Truth and What We Pay for It

I lost an argument at Thanksgiving last year. It wasn’t a debate I was unprepared for; I had my facts ready. The topic was a politician’s recent gaffe, and my uncle was insisting it never happened, a fiction invented by the media. I pulled out my phone and played the video from the Associated Press. The footage was clear. The source was impeccable. The words were undeniable. I looked up, expecting, if not an apology, at least a grudging concession.

He shook his head. “You can’t trust that,” he said, his voice layered with a kind of weary wisdom. “That’s probably one of those deepfakes. They can make anyone say anything now.”

In that moment, the argument was over. Not because I had lost, but because the foundation for a shared reality had crumbled beneath us. My evidence, my proof, was irrelevant. The mere possibility of a fake had become more powerful than the authenticated truth in my hands.

This quiet moment of conversational collapse is not unique to my family. It is a scene playing out in miniature across the country, in courtrooms, on campaign trails, and in newsrooms. The technologies of synthetic media have handed a devastatingly effective tool to those who wish to evade accountability, but the true danger is not the technology itself. It is the corrosive public skepticism the technology creates; something scholars have termed the “liar’s dividend.”

This is the profit reaped when truth becomes too difficult to verify and reality itself is cast as a matter of opinion. The proliferation of AI is merely the latest accelerant in a crisis of trust that began long before, with the decentralization of our media and the weaponization of “fake news.” To defend our democracy’s epistemic foundations, we must understand the behavioral mechanics of this dividend and build a robust, multi-layered defense in our companies, in our institutions, and in ourselves.

From Broadcast to Noise

The scene at the Thanksgiving table would have been unthinkable fifty years ago, not because deepfakes didn’t exist, but because the concept of a shared, verifiable reality was largely taken for granted. In 1976, a Gallup poll found that an astonishing 72% of Americans had a “great deal” or “fair amount” of trust in the mass media. In an era dominated by a few television networks and major newspapers, figures like Walter Cronkite of CBS News, often cited as “the most trusted man in America”, served as powerful institutional gatekeepers. They delivered the news, from the Vietnam War to the moon landing, to a mass audience that consumed the same set of core facts. While Americans certainly disagreed on politics and solutions, they were, for the most part, arguing from a common playbook of reality.

The launch of CNN in 1980 and, more pointedly, Fox News in 1996, began the great fragmentation of the American audience. The business model of news shifted. Instead of broadcasting to the widest possible center, cable channels discovered it was more profitable to “narrowcast” to dedicated, partisan niches. The news became a constant, flowing stream, increasingly supplemented with opinion-as-news to keep audiences engaged and loyal. We began sorting ourselves into different information silos, and for the first time, large segments of the population were no longer operating from the same playbook.

The rise of the blogosphere in the early 2000s was a revolution in disintermediation; suddenly, anyone with a keyboard could be a publisher, reaching a potential audience of millions without the filter of an editor or the need for a printing press. This digital democratization of voice challenged institutional authority and broke open vital stories, but it also flooded the ecosystem with conjecture, conspiracy, and unvetted claims. The professional journalist, once a clear gatekeeper, was now just one voice shouting in a crowded digital marketplace. Discerning signal from noise became a full-time job for the average citizen, a job few had the time or training to do.

The final, decisive blow came when social media became the primary arena for our information lives. Platforms like Facebook and Twitter (X I guess) did not just accelerate the spread of information; their core algorithms actively shaped what we saw. These systems are designed for one purpose: engagement. And nothing is more engaging than content that triggers strong emotions: outrage, validation, fear, and tribal identity. In this environment, the term “fake news,” which once described literal hoaxes, was brilliantly and cynically weaponized. Around 2016, it was transformed into a political cudgel, used to dismiss any reporting, no matter how credible, that was critical or inconvenient. It gave millions of people a simple, powerful phrase to delegitimize any fact they didn’t like.

And so the ground was perfectly prepared. By 2024, that 72% trust in the media had collapsed to a historic low of 32%. Decades of fragmentation, decentralization, and deliberate weaponization had cultivated a deep, pervasive skepticism in the public. This is the depleted soil in which the liar’s dividend now grows so easily. The dismissal of a real video as a “deepfake” is not a sudden madness; it is the logical, tragic endpoint of this long decline.

Deconstructing the Devaluation of Truth

The depleted soil of public trust provides the perfect strategic opportunity for what scholars Josh A. Goldstein and Andrew Lohn, in their work for the Brennan Center for Justice, have termed the “liar’s dividend.” The concept is as brilliant as it is corrosive. The dividend is not the benefit a liar gets from a successful deepfake fooling the public; it is the benefit they get from the public’s awareness that deepfakes exist. It is the power to dismiss any real, inconvenient piece of evidence like an audio recording, a video, or a photograph, as a sophisticated fake, and to be believed, or at least to inject enough doubt to muddy the waters into inaction. It transforms the very technology meant to enhance reality capture into a tool for reality denial.

To understand how this dividend is collected, we have to analyze the strategic toolkit it offers to a bad actor. The first variable is the messenger: who delivers the lie? This choice exists on a spectrum of risk and reward. At one end, a political candidate can make a direct, high-impact denial themselves. This garners maximum attention but also carries the maximum risk of backlash if the lie is definitively proven. To mitigate this, the lie can be delegated to an official proxy, like a campaign manager, who offers a degree of separation. For even greater plausible deniability, the claim can be laundered through an unaffiliated proxy; a friendly pundit, a sympathetic media outlet, or an anonymous online account – sacrificing the impact of a personal denial for near-total insulation from accountability.

The second variable is the message itself: how direct is the lie? The most straightforward tactic is a direct claim: “That video of me is a deepfake.” It is a clear, falsifiable assertion. But a far more insidious and often more effective strategy is the indirect claim, which aims not to debunk a specific piece of evidence but to foster a general “informational uncertainty.” This is the world of vague dismissals (“You just can’t trust what you see these days”), oppositional rallying (“The media will do anything to make us look bad”), and whataboutism. This indirect approach poisons the entire well of information. It persuades citizens that discerning truth from fiction is a hopeless task, encouraging them to retreat into the safety of their pre-existing beliefs and partisan loyalties.

This two-axis framework, of messenger and message, provides a flexible and powerful toolkit for any individual or group seeking to escape accountability. They can tailor their strategy based on the severity of the incriminating evidence and their risk appetite. By understanding these mechanics, we can see the liar’s dividend for what it is: not just a simple lie, but a calculated, multifaceted assault on the very concept of verifiable evidence. The question then becomes, why are our own minds so susceptible to this assault?

Why We Are So Susceptible

The power of the liar’s dividend is not rooted in the sophistication of AI. It is rooted in the architecture of the human brain, which is not optimized for discerning objective truth, but for survival, social cohesion, and the conservation of mental energy. These ancient priorities make us profoundly vulnerable to modern informational warfare. The liar’s dividend is effective because it offers us an easy, comfortable, and psychologically satisfying escape from difficult realities.

The primary vulnerability it exploits is our intense aversion to cognitive dissonance, the mental stress we feel when holding two conflicting beliefs simultaneously. Imagine you believe your preferred candidate is a fundamentally decent person. Then, a video emerges showing them saying something cruel. This creates a painful dissonance. To resolve it, you can either engage in the difficult process of updating your entire view of the candidate or you can discard the offending piece of evidence. The liar’s dividend provides a perfect tool for the latter. The “deepfake” explanation allows you to resolve the dissonance instantly, not by changing your mind, but by invalidating the evidence. This isn’t just intellectual dishonesty; it’s a form of psychological self-preservation.

This is amplified by the powerful force of motivated reasoning. We do not process information like impartial judges; we process it like lawyers defending a client we are already committed to. Our client is our own set of pre-existing beliefs and tribal loyalties. When confronted with inconvenient evidence, we don’t ask, “Is this true?” We ask, “Must I believe this?” The deepfake defense allows the answer to be a resounding “no.” It feeds our confirmation bias, our natural tendency to embrace information that supports our team and reject information that challenges it. In an age where our social media feeds are algorithmically tuned to create personalized echo chambers, this effect is supercharged. Inconvenient truths feel like hostile intrusions into a reality that has been custom-built to comfort us.

Finally, the liar’s dividend preys on our brain’s fundamental laziness. Our minds operate on a principle of cognitive ease, constantly seeking the simplest possible path to a conclusion to conserve energy. It is metabolically expensive to question our own beliefs, fact-check a dubious claim, or live with uncertainty. It is cheap and easy to accept a simple, all-purpose dismissal. The claim that “you can’t trust anything” is appealing not just because it’s cynical, but because it’s simple. It relieves us of the burdensome responsibility of critical thought. In an era of crushing information overload, offering people a simple way out is the most powerful persuasion tactic of all.

An Arsenal of Imperfect Weapons

Diagnosing an illness is not the same as curing it. To combat the liar’s dividend requires a conscious and sustained counter-offensive, fought not with a single silver bullet, but with an arsenal of tools, habits, and responsibilities. The work belongs to everyone—the individual citizen, the corporations that shape our digital world, and the public institutions that form the bedrock of society.

What Individuals Must Do: The Practice of Discernment

The first line of defense is the individual mind. This requires moving beyond passive “media literacy” to a more active posture of intellectual self-defense. The most crucial habit is to practice emotional skepticism: when a piece of content makes you feel a strong surge of outrage, validation, or fear, pause. That emotional spike is a biological alarm bell, signaling that you are being targeted for manipulation. Before you share, practice lateral reading: open a new browser tab and spend two minutes searching for the claim or the source. See what other, independent outlets are saying. This simple act of “informational hygiene” is the single most powerful thing a citizen can do to stop the spread of lies. Resisting the urge to instantly share unvetted information is no longer just a matter of personal etiquette; it is a fundamental civic duty.

What Companies Must Do: The Responsibility of the Platform

The corporations that host our digital public square have a profound responsibility to architect for trust. For social media platforms, this means deliberately engineering “friction.” Instead of optimizing for seamless, instantaneous sharing, they should introduce pop-ups that ask, “Are you sure you want to share this article you haven’t opened?” or flag content from unverified sources. They must also move beyond half-measures and universally adopt and enforce clear, consistent labels for synthetic media and known disinformation outlets. For the companies developing AI, the work must begin at creation. They must bake in robust, open-source watermarking and content provenance standards, like the C2PA standard, into their models from the ground up. Making these tools proprietary or paywalled is an abdication of responsibility.

What Institutions Must Do: Rebuilding the Foundation

Our foundational institutions must undertake the slow, generational work of rebuilding our collective defenses. In education, digital citizenship and critical source analysis cannot be a single lesson; they must be a core competency woven into every subject from middle school onward. Our government and civil society leaders must establish and enforce clear, cross-party norms that create real political costs for candidates who knowingly profit from the liar’s dividend. This could take the form of public pledges, withdrawal of funding, or formal censure. Finally, we must reinvest in the institutions designed to create shared knowledge: public media, libraries, and independent, local journalism. These entities provide a crucial, non-partisan baseline of reality that can serve as an anchor in a sea of digital noise. The liar’s dividend thrives in a vacuum of trusted authorities; we must work to refill that vacuum.

Paying the Dividend

We have traveled a long and troubling road: from the high-water mark of shared facts to the fragmented noise of today, from the cynical mechanics of the liar’s dividend to the deep-seated cognitive biases that make us such willing participants. We have seen that this crisis is not the fault of any single technology, but the result of a decades-long erosion of institutional trust, supercharged by platforms that reward emotion over evidence. And while we have laid out an arsenal of potential weapons for this fight, in our habits, our corporate architectures, and our civic institutions, the choice to wield them remains ours.

I think back to that Thanksgiving table. The stalemate was not about a specific fact, but about the very possibility of facts. My uncle’s casual dismissal of a verifiable video was the final payment of the liar’s dividend, the moment where the exhausting work of discernment is abandoned in favor of the simple comfort of disbelief. His argument was the culmination of a system that has taught us that the truth is too difficult to find, that all sources are equally biased, and that trusting our tribe is a safer bet than trusting our eyes.

That quiet, helpless moment is the future on a small scale. It is a world where accountability becomes impossible because evidence has lost its meaning. It is a democracy where deliberation decays into a shouting match between alternate realities, and power flows not to the most competent or principled, but to the most shameless. This is the ultimate price of the liar’s dividend.

Defending our shared reality is now the central, defining challenge of our era. It is exhausting, difficult, and often thankless work. But the alternative, a world where truth is merely a partisan opinion and every citizen is an island of their own belief, is no world at all. We must choose to pay the cost of discernment, because the cost of disbelief is one we can no longer afford.

#MentalNote · #productideas · Big Ideas

Decoding the Chaos: Welcome to Wahala Economics

During my time navigating the vibrant streets of Lagos, I often found myself observing patterns that defied conventional economic wisdom. What initially appeared as disorganization or inefficiency hinted at something more complex, a hidden logic beneath the surface-level ‘wahala.’ It was there, amidst the bustling markets and intricate social dynamics, that the idea of ‘wahala economics’ began to take shape for me – a lens through which to understand the underlying, often unconventional, economic forces at play in such environments. It’s about recognizing that what looks like chaos might actually be a rational, if not always optimal, response to a unique set of constraints and incentives.

Consider the real estate market in Lagos. An outsider might observe seemingly high property prices, perhaps juxtaposed with visible signs of economic hardship. Scratch a little deeper, and you might hear about the lucrative returns some are making through platforms like Airbnb. This visible success, even if enjoyed by a relatively small fraction of property owners, can act as a powerful signal. The perceived profitability of short-term rentals creates an impression of high returns across the board. Consequently, buyers and investors, perhaps lacking granular data on actual Airbnb occupancy rates and profitability across different properties, may bid up prices, not just for Airbnb-suitable apartments, but for real estate more broadly. What appears ‘irrational’ – higher prices even for properties less suited to short-term rentals – becomes a rational response to the distorted incentives created by the highly visible, though potentially unrepresentative, success of some Airbnb ventures.

This phenomenon in the Lagos real estate market isn’t an isolated quirk. Across ‘wahala economies,’ you often find that the incentives themselves are skewed in ways that would seem counterintuitive in more conventional settings. What might appear as irrational behavior – individuals making choices that don’t maximize standard economic utility – often becomes rational when you understand the distorted incentive landscape they navigate. For instance, in environments where trust in formal institutions is low or where scarcity is pervasive, seemingly ‘inefficient’ behaviors like hoarding resources or prioritizing immediate gains over long-term investments can become logical responses to the prevailing conditions. The actors aren’t necessarily irrational; their rationality is simply calibrated to a different, often more challenging, set of incentives.

Beyond the immediate distortions of information asymmetry and skewed incentives, another layer of understanding in ‘wahala economics’ comes from the perspective of ‘infinite games.’ Unlike finite games with clearly defined players, rules, and an end goal, infinite games are about continuing to play. In environments marked by uncertainty and ongoing challenges, actions that appear ‘inefficient’ in the short term might be strategic moves within a much longer, undefined game. Consider a seemingly convoluted or time-consuming negotiation process. From a purely transactional viewpoint, it might look like a waste of resources. However, within the context of an ‘infinite game’ – where building relationships and establishing trust for future interactions is paramount – that extra time and effort might be a crucial investment.

Ultimately, ‘wahala economics’ invites us to look beyond the simplistic metrics of efficiency and immediate transactional gains. The seemingly chaotic dance of these economies often reveals a deeper, adaptive logic rooted in navigating information gaps, responding to skewed incentives, and playing the long game in environments where trust might be localized rather than widespread. The ‘inefficiencies’ we observe on the surface can be understood as the emergent strategies of actors responding rationally (within their context) to the particular ‘wahala’ they face.

What examples of ‘wahala economics’ have you observed in your own experiences or travels? Share your insights!


#MentalNote · Big Ideas

THE HIDDEN TRUTHS MANIFESTO


20 Unspoken Insights Shaping the Next Era of Humanity, Technology, and Consciousness


Introduction: The Power of the In-Between

In a world saturated with information, what’s rare is wisdom from the seams—those truths not yet obvious, not yet profitable, or still inconvenient to say aloud. This manifesto captures 20 emerging insights—drawn not from consensus, but from patterns, contradictions, and quiet signals across culture, technology, psychology, and philosophy. They are not predictions. They are invitations.

We are entering a liminal age. The edges matter now more than ever.


I. The Ontological Shifts

1. Hyperconnectivity is eroding the boundary between signal and simulation. Our nervous systems are recalibrating to synthetic coherence. The real threat is not misinformation—but mis-feeling.

2. Consciousness isn’t a state—it’s a rhythm. Being is not binary. It pulses. The truest intelligence may emerge from resonance, not computation.

3. The soul of a civilization is stored in what it forgets. Our archives are filled with noise. Our ghosts hold the signal. Watch what cultures erase.

4. Laughter is the last truly encrypted signal. Authenticity will be harder to simulate. Laughter, like grief, might remain a final frontier.

5. The planet may already be sentient—just not in a way we know how to listen to. We frame Earth as object, not interlocutor. New science will rediscover old animisms.


II. Technology & Time

6. AI will break the concept of “talent.” When mimicry becomes trivial, differentiation will shift to curation, friction, timing, and soul.

7. Economies will compete on resonance, not just resources. Coherence is currency. Cities and nations with vibrational alignment will outperform those with raw capital but no story.

8. The next colonialism is sensory. Attention was phase one. Emotion, impulse, and identity are next. Sensory sovereignty will emerge as a human right.

9. Most of the world’s best ideas have already been had—but weren’t scalable in their time. The archive is an oracle. Indigenous methods, ancient city-planning, spiritual ecologies—they’re not outdated, just awaiting infrastructure.

10. The most powerful act in the next 50 years might be a radical slowdown. Stillness isn’t escape. It’s rebellion. In an economy of speed, slowness is the ultimate edge.


III. Society & Meaning

11. Childhood is being outsourced to algorithms. Emotional scaffolding is no longer built at home. Identity is now a platform-level construct.

12. The future belongs to those who can sit with paradox. Complexity won’t be solved, only harmonized. Paradox fluency will be the master skill.

13. We’re underestimating the psychic cost of persistent partial presence. Anxiety isn’t pathology—it’s evolutionary resistance to ambient fragmentation.

14. Death may no longer anchor meaning. Lifespan extension, data immortality, and identity diffusion will unravel the narrative spine of civilization.

15. Global South ingenuity is constrained more by narrative friction than capital. The main barrier isn’t money. It’s the inherited epistemologies that limit what people believe they’re allowed to build.


IV. Cultural & Philosophical Reframes

16. The next great export from Africa isn’t oil or music—it’s metaphor. Ancestral logic, oral cosmology, and multi-dimensional storytelling offer new operating systems for post-singularity life.

17. Language is about to fracture in slow motion. Algorithmic dialects, meme languages, and subcultural codes will replace global lingua francas. The internet is not unifying—it’s atomizing semantics.

18. Innovation will look more like excavation than invention. The future is buried. True progress may require humility, not hubris.

19. The most radical tech shift is not generative AI—it’s the return of intentional community. We are rebuilding the village with APIs and group chats. Belonging is the new infrastructure.

20. Taste will matter more than intelligence. In a world where anyone can access brilliance, it’s how you filter, align, and sense-make that sets you apart.


Investment & Tech Hype: A Realignment Ahead

These 20 insights point to an inevitable shift in capital flows and startup psychology. Investment will slowly move from:

  • Efficiency to Coherence
  • Disruption to Resonance
  • Extractive platforms to Restorative ecosystems
  • Utility-first tech to Meaning-infused tech
  • B2B/SaaS monocultures to culture-native, place-rooted infrastructure

We are exiting the API-for-X era and entering the ritual-for-X era—where software must plug into felt realities, not just business logic. Tech hype will pivot from AI acceleration to AI attunement. The winners will not be those who automate everything, but those who re-enchant it.

VCs will need to develop spiritual imagination. Founders will need paradox fluency. And builders? Builders will need to listen as much as they invent.

The question is no longer: What can we build? The question is: What wants to be built through us?


Let this be your prompt. Your prayer. Your playbook. The future is listening.