Why the AI Intelligence Revolution Will Surpass the Industrial Era: Productivity, Costs, and Opportunities for Individuals in 2025.

Behavior, Economy, Ideas, Society, Technology, Uncategorised |

Introduction

In the swirling currents of technological change, few shifts have reshaped humanity as profoundly as the industrial revolution. Yet, as I contemplate the dawn of the AI era in mid-2025, I find myself convinced that the intelligence revolution unfolding before us will dwarf its predecessor in scope and societal consequence. This isn’t mere hype; it’s a recognition of how intelligence—once the exclusive domain of human minds—is becoming a ubiquitous force, much like mechanization transformed muscle power in the 19th century. Factories and steam engines multiplied physical output, promising an end to scarcity and ushering in abundance. Similarly, AI tools—from autonomous agents to predictive models—are amplifying cognitive capabilities, enabling efficiencies that could redefine productivity on a global scale. But here’s the sobering parallel: Just as the industrial shift delivered abundance at the expense of workers’ time, energy, and autonomy, AI’s promise comes with hidden costs for the individual. We’ll all become more efficient and productive, yet in the initial stages, this may mean outputting more just to maintain our current status, with wealth funnelling to a select few elites who control the “factories” of intelligence.

To grasp why this revolution eclipses the industrial one, consider the scale. The industrial era mechanized labour, shifting societies from agrarian roots to urban factories and sparking economic growth that lifted billions over centuries. But AI targets the mind itself—our decision-making, creativity, and problem-solving—potentially compressing centuries of progress into decades. In my essay “AI Revolution Unveiled: Humanity’s Future by 2050” (17th March 2025), I delved into how AI could collapse traditional power structures and rebirth civilizations, not through physical might but through augmented intelligence. This isn’t about replacing jobs; it’s about redefining what it means to work, think, and exist in a world where cognitive tools are as commonplace as electricity. Ubiquity is key: Just as industrial machines became accessible to factories worldwide, AI is embedding itself everywhere—from free chatbots on smartphones to APIs powering businesses. This democratizes intelligence, allowing a UK-based creator like me to analyse crypto trends or generate essay drafts in minutes, boosting output exponentially.

The allure of abundance is undeniable. As I outlined in “End of Debt: The Abundance Flywheel by 2040” (9th April 2025), AI’s efficiencies create a self-reinforcing cycle: Automation reduces costs, frees resources, and spurs innovation, potentially erasing global debt and flooding markets with affordable goods and services. Imagine healthcare diagnostics at near-zero marginal cost, or personalized education tailored to every learner. Productivity surges could add trillions to global GDP, echoing the industrial boom that made textiles and transport cheap. For individuals, this means opportunities to thrive in new ways—perhaps pivoting from routine tasks to creative generalism, as I explored in related pieces on AI’s role in fostering broader skills.

Yet, this abundance won’t come without a human toll, much like the industrial revolution’s dark underbelly. Workers flocked to factories for better wages, only to find their days stretched into gruelling shifts, with leisure sacrificed to the machine’s rhythm. Similarly, AI’s ubiquity demands we all become more skilled and productive to stay competitive. Current jobs—from finance to creative fields—will require outputting more, as AI sets a higher bar for efficiency. A marketer must now layer AI insights with deeper strategy to compete, while costs of goods fall, pressuring everyone to deliver faster and better. In the early phases, this scramble mirrors industrial adaptation: A small handful of actors—tech barons controlling data centres and models—capture the bulk of wealth, leaving most to hustle harder for scraps. Wealth concentration, as patterns from land to AI show, perpetuates inequality until reforms intervene.

Why does this matter for the individual? In an era where intelligence is commodified, our time and energy become the currency. We’ll adapt or fall behind, but opportunities exist for those who innovate with agency in mind—crafting tools that preserve human intent amid the flood. As we unpack these parallels, from historical lessons to modern costs and paths forward, the question looms: Will we let this revolution consume us, or steer it toward true freedom?

Historical Parallels: Lessons from the Industrial Revolution

To truly appreciate the magnitude of the AI intelligence revolution, we must first revisit the industrial revolution—not as a distant history lesson, but as a mirror reflecting our potential future. This era, spanning the late 18th to early 20th centuries, marked a pivotal transformation in human society, shifting us from agrarian economies reliant on manual labour and natural cycles to mechanized production powered by steam, coal, and innovation. In the UK, where I’ve spent my life, this change began in earnest with inventions like James Watt’s steam engine and the rise of textile mills in Lancashire. What started as a promise of progress—machines alleviating toil and multiplying output—unfolded into a complex saga of abundance intertwined with profound human costs. As I explored in “How Wealth Concentrates: From Land to AI” (28th March 2025), these shifts in resource control reveal enduring patterns: Technological leaps create wealth, but often at the expense of the many, concentrating power in the hands of a few while demanding more from individuals in terms of time, energy, and adaptation.

The industrial revolution’s allure lay in its productivity explosion. Before it, life was predominantly rural and seasonal. Farmers in pre-industrial England worked intensively during planting and harvest but enjoyed relative downtime in winter months, with labour dictated by daylight and weather. Communities thrived on local crafts, bartering, and social bonds. Then came the machines: Spinning jennies and power looms automated textile production, railways connected markets, and factories centralized work. Output soared—cotton production in Britain multiplied 50-fold between 1780 and 1860—leading to cheaper goods, urban growth, and eventual rises in living standards. Abundance materialized in forms like affordable clothing, preserved foods, and transportation, laying the groundwork for modern economies. This mirrors the AI-driven efficiencies we’re witnessing today, where cognitive tools amplify human capabilities at scale.

Yet, for the individual, this abundance was no immediate boon. The shift pulled people from farms into factories, imposing rigid schedules that devoured time. Workers, including women and children, endured 12- to 16-hour days, six days a week, in dimly lit, hazardous environments filled with noise, dust, and machinery accidents. Leisure evaporated; family life fractured as entire households laboured to survive. Energy was sapped not just physically but mentally—monotonous tasks eroded skills and autonomy, turning humans into extensions of the machine. Charles Dickens captured this in his novels, portraying the dehumanizing grind of urban industrialization. In my essay “Twentieth-Century Chaos: How Culture and Crisis Shaped Humanity’s Edge” (28th March 2025), I reflected on how such crises forged cultural resilience, but the initial toll was immense: Rising inequality, health epidemics like cholera in overcrowded cities, and social upheavals from Luddite rebellions to labour strikes.

Wealth concentration was a defining feature, much like the AI elites of today. A small cadre of industrialists—think Andrew Carnegie in steel or the Rothschilds in finance—amassed fortunes by owning the means of production: Factories, patents, and supply chains. They captured the bulk of gains from mechanization, while workers received subsistence wages. This wasn’t accidental; market forces, driven by competition and greed, perpetuated the imbalance. Governments initially lagged, with laissez-faire policies allowing exploitation until reforms like the UK’s Factory Acts of the 1830s-1840s introduced limits on child labour and work hours. Even then, it took decades for broader benefits—higher wages, shorter weeks, and social safety nets—to trickle down, often through union efforts and political pressure.

These parallels to the AI revolution are uncanny and cautionary. Just as industrial mechanization made physical labour ubiquitous and efficient, AI makes intelligence accessible, embedding it in everyday tools. But the individual cost echoes loudly: To stay competitive, we’ll all need to become more skilled and productive, outputting more in our current jobs simply to maintain status. A graphic designer, for instance, once relied on manual tools; now, with AI generators producing drafts in seconds, they must iterate faster, infuse deeper creativity, or specialize in human-AI hybrids to compete. This pressure spans sectors—teachers curating AI lessons, analysts layering insights over automated data crunching—driving down costs of goods and services while demanding relentless up-skilling. As factories forced farmers to adapt or perish, AI compels us to elevate our game, blurring work-life boundaries in an always-on digital world.

The energy drain is subtler but no less profound. Industrial workers faced physical exhaustion; AI users risk mental fatigue from constant adaptation and algorithmic nudges. Social bonds may weaken as gig economies fragment time, much like urban migration isolated families. And wealth? It flows upward to those controlling AI’s infrastructure—data moguls and model owners—perpetuating divides until societal interventions catch up.

History isn’t destiny, though. The industrial revolution eventually birthed the middle class, weekends, and public education, transforming drudgery into opportunity for many. AI could follow suit, but only if we heed these lessons early. By understanding this parallel, we can anticipate the costs and craft strategies to mitigate them, ensuring the intelligence revolution enhances humanity rather than extracts from it.

The AI Intelligence Revolution: Ubiquity and Productivity Gains

Fast-forward to 2025, and the intelligence revolution is no longer speculative—it’s here, reshaping our world with a velocity that makes the industrial era seem quaint by comparison. At its core, this revolution centres on the ubiquity of artificial intelligence: Tools that augment, mimic, or even surpass human cognition are becoming as commonplace as the smartphones in our pockets. Just as industrial mechanization made physical power accessible and scalable—turning manual crafts into mass production—AI democratizes intelligence, embedding it into everyday tasks, decisions, and creations. This isn’t about sentient robots overtaking humanity; it’s about a fundamental shift where cognitive enhancements are available to anyone with an internet connection, from a Devon-based writer brainstorming essays to a London trader forecasting markets. In my essay “Universal Intelligence: Beyond Human Limits in AI and Biology” (16th July 2025), I argued that intelligence isn’t confined to human brains or silicon chips—it’s a universal force, blending biology and technology to push beyond limits. Today, that vision is materializing, promising unprecedented productivity gains for individuals and societies alike.

Consider the mechanics of this ubiquity. AI assistants like Grok or ChatGPT are free or low-cost, handling queries, generating code, or analysing data in seconds. Autonomous agents—software that acts independently, like scheduling meetings or optimizing supply chains—are integrating into apps and workflows. Predictive models in healthcare diagnose issues faster than doctors alone, while generative tools create art, music, or reports from simple prompts. This mirrors the industrial spread of machines: Once exclusive to inventors, steam engines powered factories everywhere, boosting output exponentially. Now, AI’s zero-marginal-cost nature—replicating intelligence without additional expense—accelerates this further. By mid-2025, reports estimate AI contributing $15 trillion to global GDP, with tools accessible via platforms like x.com or mobile apps. For the individual, this means amplified efficiency: A photographer can upscale images instantly, a marketer personalize campaigns at scale, or an investor simulate scenarios with precision. As I detailed in “How AI Will Make You Rich: 5 Strategies for 2025” (13th March 2025), strategies like AI-driven investing or content creation can turn personal productivity into wealth, leveraging ubiquity to outpace traditional methods.

The productivity gains are tangible and transformative. In workplaces, AI automates routine tasks—data entry, basic analysis, or even creative drafting—freeing humans for higher-value work. A 2025 McKinsey report highlights efficiency boosts of 20-30% in sectors like finance and retail, where AI handles inventory predictions or fraud detection. For individuals, this translates to outputting more with less effort: An educator crafts customized lessons via AI tutors, a developer debugs code faster with automated suggestions. This parallels industrial gains, where assembly lines multiplied worker output from handmade items to thousands daily. But here’s where the parallel deepens and the demands emerge: Current jobs won’t remain static; they’ll require us to become more efficient, better skilled, and far more productive simply to maintain our standing. In competitive fields, AI sets a new baseline—analysts must now deliver insights layered over AI-generated reports, designers iterate concepts at AI speed, and even creatives like photographers (as I’ve experienced in my own work) upscale portfolios while infusing unique human flair to stand out. Humans will have to output more—deeper analyses, faster innovations—to stay relevant, as peers and employers adopt AI en masse.

This imperative stems from market dynamics: As AI drives down costs of goods and services, competition intensifies. A product once taking weeks to design might now take days, slashing prices and forcing providers to deliver higher volumes or quality to compete. In the UK, where small businesses and freelancers abound, this means gig workers hustling harder—outputting more proposals, analyses, or designs—to match AI-augmented rivals. The result? Falling costs benefit consumers (cheaper software, personalized services), but for workers, it’s a race to elevate skills continuously. Upskilling becomes non-negotiable: Learning prompt engineering, ethical AI use, or data literacy isn’t optional; it’s essential to harness ubiquity without being outpaced. As I noted in “AI Wealth Revolution: 3 Steps to Thrive in the New Era” (13th March 2025), thriving involves proactive steps like building AI-hybrid workflows, but this demands investment in time and mental energy upfront.

Neutral observers might celebrate this as progress—abundance flowing from efficiency, much like industrial goods flooded markets. Global supply chains optimized by AI could eradicate shortages, personalized medicine extend lives, and creative tools democratize art. In crypto and finance, as I’ve predicted, AI synergies could propel market caps to $12 trillion by 2026, creating wealth cascades. Yet, this productivity surge isn’t frictionless. It requires constant adaptation, echoing the industrial worker’s need to master machines or face redundancy. Early adopters gain edges, but laggards risk marginalization, widening divides. Moreover, ubiquity brings subtle pressures: Always-on tools blur boundaries, turning “downtime” into opportunities for more output.

In essence, the intelligence revolution’s ubiquity and gains propel us toward an abundant future, but they demand we redefine productivity on AI’s terms. As with industrialization, the benefits are real—amplified capabilities for all—but the path involves adaptation that could strain our resources. Understanding this sets the stage for confronting the costs head-on, ensuring we shape this revolution rather than letting it shape us unchecked.

The Hidden Costs: Time, Energy, and Wealth Concentration

As the intelligence revolution propels us toward ubiquity and soaring productivity, it’s tempting to envision a utopia of effortless abundance—machines handling the grunt work while humans pursue leisure, creativity, and fulfilment. But history whispers a caution: The industrial revolution promised similar liberation, yet delivered it unevenly, often at great personal expense. The AI era risks the same pitfalls, where gains mask hidden costs to our time, energy, and equitable distribution of wealth. In the initial stages, as AI embeds itself in every job and process, individuals will face relentless pressure to adapt, outputting more just to tread water. This isn’t alarmism; it’s a neutral assessment drawn from emerging patterns in 2025, where efficiency demands are already reshaping daily life. As I examined in “Social Media Addiction: How It’s Hijacking Your Brain and Mental Health in 2025” (15th July 2025), digital tools can subtly erode well-being, and AI amplifies this by turning cognitive enhancements into obligatory upgrades. The result? Abundance for economies, but a potential drain on the human spirit.

Let’s start with time—the most finite resource. In the industrial revolution, factories commodified hours, imposing clockwork schedules that stripped workers of natural rhythms. AI introduces a digital equivalent: Always-on ubiquity that blurs boundaries between work and rest. Tools like AI agents automate emails or reports, but they also create expectations of constant availability—respond faster, iterate more, monitor endlessly. A 2025 PwC report on AI in the workplace notes that while automation saves time on tasks, it often reallocates it to up-skilling or oversight, with no net reduction in hours for most. For individuals, this means current roles evolve into high-output demands: A teacher must now curate AI-generated lessons while delivering personalized feedback at scale, or a consultant analyse AI-summarized data with deeper strategic layers. To maintain status—salary, relevance, or employability—we’ll all have to produce more, as competitors leverage AI to undercut timelines and costs. Goods and services will fall in price—think cheaper AI-optimized logistics or content creation—but this deflationary pressure forces workers to compensate by ramping up volume or quality, echoing factory quotas that demanded more pieces per shift.

This time squeeze extends beyond offices into personal spheres, fostering a culture of perpetual busyness. Gig economy platforms, supercharged by AI matching and prediction, fragment schedules into unpredictable bursts—deliver more rides, complete more tasks—to stay viable. In the UK, where freelance work is rising, this could mean creators like photographers or writers (fields I’ve navigated) churning out AI-assisted content faster to compete with automated alternatives. Leisure? It risks becoming another optimization slot—AI-suggested hobbies or rest tracked for efficiency. The industrial parallel is stark: Rural downtime gave way to urban exhaustion, with workers collapsing after shifts. AI’s version might be subtler—mental overload from decision fatigue or notification pings—but no less taxing.

Energy costs compound this, striking at our mental and emotional reserves. Industrial labour broke bodies; AI targets minds. As algorithms nudge behaviours—personalizing feeds to maximize engagement or workflows to boost output—they exploit human instincts, creating a coercive flywheel where market forces extract more effort under the guise of empowerment. In “Why Fear and Greed Drive Markets: The Brain Behind Finance” (6th July 2025), I decoded how limbic drives fuel economic behaviours, and AI weaponizes this: Fear of falling behind prompts endless up-skilling, greed for gains keeps us plugged in. Health impacts are emerging—rising burnout, anxiety, and cognitive fatigue, as 2025 studies link AI tool overuse to sleep disruptions and decision paralysis. For mid-career professionals, adapting means constant learning curves, draining energy that could go to family, hobbies, or reflection. This echoes industrial epidemics: Factory pollution and overwork led to physical ailments; AI’s “mental pollution”—bias-laden outputs or ethical dilemmas—could foster psychological ones, as I’ve warned in pieces on behavioural nudging.

Wealth concentration exacerbates these burdens, mirroring the industrial barons who amassed empires while workers toiled. In AI, the “factories” are data centres, proprietary models, and vast datasets, controlled by a handful of entities—tech giants and visionaries shaping global narratives. As I analysed in “Trump, Musk, and the Tech Elite: Who Rules America in 2025?” (2nd March 2025), power coalesces around figures like Elon Musk, whose companies dictate AI’s direction. These elites capture the lion’s share of value: User data fuels models, generating trillions in revenue, while individuals contribute inputs (time, creativity) for marginal returns. In the initial stages, this skew is acute—AI startups boom, but consolidations favor incumbents, much like industrial monopolies in steel or oil. Workers adapt by outputting more, yet wages may stagnate as AI depresses labour costs, per projections in “The Long Climb: How Liquidity and Financial Conditions Could Push the Cycle to 2026” (8th March 2025). Falling prices for goods benefit consumers, but producers—us—must hustle harder to sustain incomes, widening inequality until reforms intervene.

This isn’t to deny abundance’s arrival; AI’s efficiencies will create wealth, potentially erasing debts and funding social goods, as in my abundance flywheel concept. But for individuals, the early costs could dominate: Time commodified by digital demands, energy sapped by adaptation, wealth skewed upward. History shows industrial reforms—unions, regulations—eventually balanced scales, raising standards for all. AI may follow, but only if we confront these costs proactively, designing systems that prioritize human agency over extraction. As we turn to opportunities, the path forward lies in innovations that reclaim what this revolution threatens to take.

Opportunities Amid the Shift: Agency and Innovation

Amid the daunting parallels between the intelligence revolution and its industrial predecessor—ubiquity breeding productivity at the cost of time, energy, and equitable wealth—it’s easy to slip into pessimism. Yet, history reminds us that revolutions, while disruptive, also seed opportunities for those who adapt proactively. The industrial era eventually birthed innovations like labour unions, public education, and consumer protections, redistributing some benefits and easing individual burdens. Similarly, AI’s landscape, though skewed toward elite control in its early stages, offers niches where individuals can leverage ubiquity to reclaim agency and thrive. This isn’t about denying the costs; it’s about recognizing paths to mitigate them through human-centric innovations. In my essay “How AI Superintelligence Nudges Human Behaviour: Preserving Agency in 2025” (20th July 2025), I emphasized the need to design AI systems that enhance choice rather than erode it. Here, that principle guides us: By focusing on agency-focused tools and strategies, individuals can turn AI’s demands into advantages, carving out value in a hyper-efficient world.

One key opportunity lies in navigational aids—tools and education that help people preserve autonomy amid AI’s subtle pulls. As jobs require more output to stay competitive, the risk of burnout and manipulation grows, but so does demand for resilience-building solutions. Imagine platforms auditing algorithmic influences on your decisions, or courses teaching critical AI literacy to spot biases in personalized feeds. This echoes industrial reforms like safety standards, but tailored to cognitive health. In “Proof of Personhood: Powering a $5T Human Engagement Economy” (1st April 2025), I envisioned an economy valuing verified human input over automated floods, potentially worth trillions. Individuals can participate by creating or consulting on such tools: A freelancer might develop apps verifying “human-made” content, countering AI-generated saturation, or offer workshops on ethical up-skilling. With edtech markets projected at $404 billion by 2025, this niche is ripe—low barriers like online platforms allow anyone to launch courses blending AI efficiency with human insight, monetizing expertise while addressing the energy drain we’ve discussed.

Decentralized technologies provide another avenue, blending AI with blockchain to diffuse control and create accessible wealth streams. Industrial monopolies dominated until cooperatives and regulations emerged; AI’s version could be crypto-AI hybrids empowering individuals. As I outlined in “AI and Crypto: The Decentralized Wealth Revolution Unveiled” (11th March 2025), fusing AI agents with blockchain enables peer-to-peer economies, where users own their data and outputs. For example, NFT-verified creations or Solana-based services allow creators to bypass gatekeepers, capturing value directly. In a world where goods costs fall due to AI, these models let individuals scale personal brands or side hustles—perhaps tokenizing essays or photography portfolios for recurring royalties. This counters wealth concentration: While elites own core infrastructure, decentralized apps democratize access, much like industrial cooperatives gave workers bargaining power. Opportunities here include investing in hybrid tokens or building custom bots, as suggested in my strategies for 2025, turning ubiquity into personal leverage without exhaustive corporate allegiance.

Human-AI collaboration niches also emerge, emphasizing irreplaceable traits like empathy, ethics, and generalism. As AI handles specifics, jobs evolve toward oversight and synthesis—roles where humans guide outputs to align with values. In “How AI Fuels the Rise of Generalism in 2025” (13th March 2025), I argued that AI frees us for broader expertise, blending fields like philosophy and tech. Individuals can thrive by consulting on AI ethics—advising firms on nudging risks—or curating hybrid content that marries AI efficiency with authentic storytelling. This preserves time by automating tedium while channelling energy into meaningful work. For instance, in creative industries, AI drafts visuals, but human curation adds the “edge” of chaos and culture I’ve explored elsewhere. Such innovations not only maintain status but elevate it, as falling service costs make specialized human input premium.

These opportunities aren’t handouts; they require effort—investing in skills to “earn” AI’s benefits, as ubiquity alone doesn’t suffice. Yet, they offer a counterbalance to the costs: By innovating for agency, individuals can reclaim time through smarter workflows and energy via purposeful engagement. Societal shifts, like policies for AI transparency or basic income trials, could amplify this, akin to industrial labour laws. The revolution’s scale demands vigilance, but with proactive steps, we can ensure abundance serves humanity, not just extracts from it.

Conclusion: Navigating Toward a Balanced Future

As we reflect on the intelligence revolution—its staggering scale surpassing the industrial era, the ubiquity fuelling productivity and abundance, the hidden tolls on time and energy, the stark wealth concentration, and the emerging opportunities for agency-driven innovation—one truth stands clear: This shift will redefine humanity, but its outcome hinges on our choices. The parallels to industrialization are not just historical curiosities; they serve as guideposts, warning of pitfalls while illuminating paths to progress. In the early stages, as AI demands we output more to stay competitive and drives down costs of goods and services, many will feel the squeeze—adapting relentlessly amid elite dominance. Yet, this isn’t a predetermined fate. By proactively embracing agency-focused strategies, individuals can steer toward a future where abundance enhances rather than extracts from our lives. As I pondered in “The Future of Identity: How to Thrive Authentically in a Tech-Curated World” (20th February 2025), authenticity in a tech-saturated age requires intentional navigation, preserving the self amid algorithmic currents.

The revolution’s promise lies in its potential for rebirth. Industrialization, for all its initial cruelties, ultimately expanded opportunities—spawning the middle class, global trade, and technological lineages leading to today. AI could catalyse even greater transformations: Economies free from scarcity, societies enriched by universal intelligence, and individuals empowered to pursue generalism over drudgery. But realizing this demands collective action—policies like AI ethics regulations, universal basic income to buffer adaptation costs, or decentralized frameworks ensuring broader wealth distribution. On a personal level, it’s about innovating with intent: Crafting tools that audit AI’s nudges, monetizing human-centric content via blockchain, or consulting on ethical integrations. These steps, as outlined in earlier sections, counter the coercive flywheel, reclaiming time for “the nice things” like reflection, relationships, and creativity that industrialization often deferred.

Neutral optimism is warranted here. While elite concentration may dominate initially, history shows diffusion follows—open-source AI models and community-driven platforms could democratize access, much like industrial patents eventually expired, sparking waves of invention. In “AI Revolution Unveiled: Power’s Collapse and Rebirth by 2050” (26th March 2025), I envisioned a cycle where concentrated power crumbles under its own weight, giving way to collaborative rebirths. We’re at the cusp: By 2040, abundance flywheels could eradicate debt and foster leisure, but only if we mitigate early costs through agency preservation. For individuals, this means viewing AI not as a master but a tool—investing effort to “earn” its benefits, as ubiquity alone won’t suffice.

In closing, the intelligence revolution challenges us to evolve: Adapt passively, and we risk echoing industrial exploitation; innovate for agency, and we unlock a balanced era. The choice is ours—harness this force to amplify humanity, or let it diminish us. For deeper dives into these themes, explore my site at https://aronhosie.com/blog/

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