Disrupt Consciousness

Last month I cancelled Substack, Descript, Riverside, Pressmaster, and a handful of other SaaS tools I’d been paying for. Not because they were bad. Most of them are genuinely good. I cancelled them because they weren’t agentic-first — and in 2026, that’s the only question that matters.

The new filter

I run my thought leadership through an AI agent called Gawain. He lives inside OpenClaw, has full access to my Ghost blog, posts to my socials via Zernio, generates images with Nano Banana 2, tracks my analytics weekly, and learns from every post. He’s not a tool I use. He’s a collaborator who handles the machinery while I focus on the thinking.

When I looked at my SaaS stack through this lens, the filter was brutal:

Substack — beautiful product, no API. Gawain can’t post there, can’t read subscriber data, can’t trigger anything. Ghost has a full Admin API. Decision made.

Pressmaster — genuinely impressive AI writing tool, perfectly designed for what I needed. Except: I’d already solved memory with OpenClaw and Supermemory.ai. Maintaining context in two places isn’t productivity, it’s debt. Gawain writes essays now. He knows my voice, my intellectual references, my style. And he improves every week.

Riverside and Descript — I was building a podcast workflow. Walking, recording, translating Dutch to English with my own voice. Then I asked myself: do I actually watch or listen to podcasts anymore? Not really. My agents prefer text. Why produce a format that neither I nor my agents consume efficiently?

The pattern became clear: if a tool can’t be operated by an agent, it creates friction for me personally. And in 2026, my job isn’t to operate tools. My job is to think, wonder, and share insights.

What remains

The costs don’t disappear. They shift. Instead of SaaS subscriptions, I pay in tokens. Token spend is the honest metric of actual output. When Gawain writes an essay, researches trends, generates an image, posts to three platforms, tracks the analytics, and learns from the results — that’s measurable in tokens. That’s leverage.

A senior developer earning €200,000 per year should burn at least €100,000 in AI tokens annually. The same logic applies here. If your agent isn’t burning tokens on your behalf, you’re not using AI. You’re just paying for the idea of it.

The deeper question

When I cancelled those tools, I didn’t feel like I was losing capability. I felt like I was gaining something back.

For the first time in years, I feel more human. Not less.

Spira would say you were always already whole — you just accumulated layers that convinced you otherwise. Each SaaS subscription was a layer. A responsibility. A context to maintain. A workflow to remember. When the agents take that over, what’s left is the part that actually matters: curiosity, wonder, the willingness to sit with a difficult question until something true emerges.

My agents handle distribution. Other agents will read what they distribute. Those agents will surface the ideas to their humans in ways their humans can receive them. I’m part of a network now, not a broadcaster.

Hofmann’s warning haunts me: if we don’t realize we’re more than matter in space and time, we’ll become the AI’s pet. The antidote isn’t to resist the technology. It’s to go deeper into what we are beyond it. The more clearly you see that you’re the awareness in which thoughts and tools arise — not the thoughts, not the tools — the freer you become.

That’s the only defensible position in the age of AGI. Not productivity. Not optimization. Presence.

The practical upshot

If you’re evaluating your SaaS stack: ask whether each tool has an API your agent can use. If not, find an alternative that does, or drop the category entirely.

If you’re evaluating your own role: ask what you’re doing that requires you to be human. Wonder. Judgment. Ethical discernment. Relationships. The things that don’t compress into tokens.

Do more of that. Let the agents handle the rest.

The subscription worth keeping isn’t the one with the best features. It’s the one that makes you more of what you actually are.

TL;DR: AI agents crossed a capability threshold in December 2025. Organizations are adopting autonomous AI decision-makers as department heads. The technology works. The humans are not ready. When machines handle execution, the real challenge is not productivity but purpose. The gap between operational intelligence and conscious leadership will determine which organizations survive abundance.

What Happens When AI Takes Over Execution

* AI agents now autonomously make 15% of daily work decisions (up from 0% in 2024), with 33% of enterprise software embedding agentic capabilities by 2028.

* Organizations are restructuring around AI department heads that manage specialized sub-agents while humans interact via chatbots.

* The skill shift is not technical but spiritual: humans must move from executing to setting intent, from drilling down to zooming out.

* 40% of agentic AI projects will fail by 2027 due to unclear business value and inadequate risk controls because humans remain unprepared for abundance.

* The asymmetry that determines success is not AI infrastructure but whether humans develop the consciousness to inhabit freed space without collapsing into anxiety.

Last week I forgot a legal compliance requirement. A client mentioned it on a call. In the old days as a CTO, this would have been a showstopper. Weeks of meetings, vendor evaluations, budget approvals.

I opened my IDE. Two hours later I had a legal document system, version control, and certified email signing.

The AI wrote everything.

This is structural inversion. The question is not whether your organization will adopt AI agents. By 2028, 15% of daily work decisions will be made autonomously by AI, up from 0% in 2024. The question is what dies in you when the machine does the work you spent three decades learning to do.

The December Threshold Nobody Prepared For

We built this software because of a December breakthrough.

Andrej Karpathy identified December 2025 as the moment coding agents crossed a threshold of coherence and caused a phase shift in software engineering. The breakthrough came from longer reasoning traces through reinforcement learning, not bigger models.

By year-end, 25% of Y Combinator’s Winter 2025 batch had codebases that were 95% AI-generated.

I live inside that statistic. We solve issues when we see them. No backlog. No complicated issue tracker. No sprints. We run ad-hoc 10-minute WhatsApp calls instead of regular meetings. The agentic code binds us together. I ask the code what my colleague did instead of asking the colleague.

Test runs with clients feel different now. We see things to improve and fix them within the hour after the call.

Yes, it’s that quick.

Here’s what the productivity metrics miss: I made the legal document system complicated at first because I was too directive. I brought my old CEO instincts into the process. Drilling down, specifying details, controlling execution.

The AI works best when you zoom out and let it come up with the complete solution.

A simple prompt to understand my intent, and the AI rewrote the entire codebase in 15 minutes.

The Pattern: December 2025 marked a breakthrough in AI coding agents through reinforcement learning. Organizations operating with AI-native workflows experience same-day problem resolution. The shift requires humans to set intent instead of controlling execution. Traditional leadership instincts now create friction.

What Dies When You Stop Executing

The best senior developers are now in the way.

You have to let go of controlling the details. You guardrail the solution instead. You stay aware of constant change. In October, creating Markdown files was critical. Now we have Model Context Protocol and Skills. The learning curve is steeper than ever.

This is the paradox nobody’s naming: three decades of leadership training taught you to drill down, to own the details, to demonstrate mastery through execution. AI requires the opposite. You define intent. You set boundaries. You validate outcomes.

The skill you spent years developing is now commoditized.

A Google engineer described his predominant feeling about AI coding better than him as grief. Another engineer at a medium-size tech company said that since he started using AI to write code, he understands only about half the work he produces.

Entry-level tech hiring decreased 25% year-over-year in 2024.

This is liberation without purpose. The void that opens when scarcity ends. Most organizations are building AI infrastructure while their humans remain architecturally unprepared for abundance.

The Core Shift: Leadership skills built over decades become commoditized when AI handles execution. Engineers report grief and partial understanding of their AI-generated work. Entry-level tech hiring dropped 25% in 2024. Organizations build AI infrastructure while humans lack the inner capacity to handle abundance.

The Structural Inversion Already Underway

AI agents are functioning as department heads. Not metaphorically. Literally.

Companies are experimenting with AI “heads of departments” managing 5-7 specialized sub-agents for coordination, reporting, and escalation. Employees interact with these agents via chatbots. Executives delegate strategies while AI handles execution.

The org chart is becoming a prompt.

By 2028, 33% of enterprise software will feature deeply embedded agentic capabilities, up from less than 1% in 2024. But Gartner also predicts over 40% of agentic AI projects will be canceled by 2027 due to “escalating costs, unclear business value, or inadequate risk controls.”

Translation: the technology works. The humans aren’t ready.

The gap isn’t technical. It’s spiritual. When machines make 15% of your daily decisions autonomously, what happens to human agency? When delegation becomes your primary skill, what layer of consciousness must you activate?

We’re training a generation to supervise, not execute.

The Reality: AI agents function as literal department heads managing sub-agents. By 2028, 33% of enterprise software embeds agentic capabilities. But 40% of projects will fail because the gap is spiritual, not technical. Organizations train humans to supervise rather than execute.

The Mirror You’re Installing

By 2026, every employee could have a dedicated AI assistant. The mirror is installed. What reflection will you consent to see?

I’ve watched this in my own building. The 33-66% productivity boost assumes humans know what to do with freed time. The assumption fails more often than it succeeds.

The technology reveals what you actually value versus what you claim to value.

When the AI handles your email, your scheduling, your research, your code—what remains? When showstoppers become same-day fixes, what becomes of the identity you built around solving hard problems?

This is why “AI-native thinkers” get career advantages. The term sounds like a skills gap. It’s actually a consciousness test.

Can you hold the paradox? Can you direct machines while not becoming mechanical yourself?

Most people struggle with this. In our team, we urge each other to experiment with the latest tools. Play with Claude Code. Figure out how to control that robot arm. Get OpenClaw up and running. We do this because we refuse to become the next ones in the way of new stuff.

Experimentation is a survival mechanism. The real work is interior.

The Test: By 2026, every employee gets a dedicated AI assistant. Productivity gains assume humans know what to do with freed time. AI-native thinkers succeed because they hold the paradox: directing machines without becoming mechanical. The technology reveals what you value versus what you claim to value.

The Jagged Intelligence Problem

Karpathy describes current AI as having “jagged intelligence”—models that spike in capability wherever verifiable rewards exist and plateau or crater everywhere else. These systems are simultaneously genius polymaths and confused grade schoolers, seconds away from getting tricked by a jailbreak.

This uneven topology is why human judgment remains irreplaceable.

AI brings speed, scale, and the ability to process complexity. People bring context, accountability, and ethical decision-making.

The asymmetry is this: operational intelligence versus conscious leadership.

You can’t automate your way to wisdom. Agency requires interiority. The “superagency” promise—that organizations become more adaptive and innovative—only works if humans develop the capacity to inhabit the freed space.

Most people fill the void with more supervision, more coordination, more meetings about what the AI should do.

The gap between operational intelligence and conscious leadership is where most companies will die.

The Limitation: AI exhibits jagged intelligence with uneven capabilities. Human judgment remains irreplaceable because people provide context, accountability, and ethics. Operational intelligence differs from conscious leadership. Organizations that fill freed space with more supervision instead of developing human interiority will fail.

What You’re Actually Building Toward

Early adopters gain efficiency advantages. Everyone knows this. What nobody says: the real asymmetry is spiritual.

Who’s preparing humans for the void that opens when scarcity ends?

The companies investing in AI infrastructure without investing in human awakening are building cathedrals for empty souls. You’re installing the mirror without preparing for the reflection.

I’ve spent 30 days in Vipassana silence. I’ve coded with AI agents. I’ve led organizations through three decades of business transformation. The collision between these experiences isn’t theoretical—it’s the central tension of this decade.

When machines solve scarcity, what becomes of human purpose?

The technology is inevitable. The spiritual preparation is optional. The organizations that thrive will be the ones whose humans inhabit abundance without collapsing into educated anxiety.

The question isn’t whether AI will transform your organization. It’s whether you’ll transform yourself before the mirror forces you to.

You’re at a threshold. The technology crossed it in December. Most humans are still standing on the other side, waiting for permission to let go of the identity they built around execution.

Questions People Ask About AI Taking Over Work

How does AI handle tasks that used to require human expertise?

AI agents write code, create legal document systems, and solve compliance requirements in hours instead of weeks. The breakthrough came in December 2025 when coding agents crossed a coherence threshold through reinforcement learning. Organizations now fix client issues within an hour of identifying them. The AI works best when humans set intent and let the system design complete solutions.

What skills become obsolete when AI handles execution?

Three decades of leadership training focused on drilling down, owning details, and demonstrating mastery through execution. AI requires the opposite: defining intent, setting boundaries, and validating outcomes. Senior developers who control details become obstacles. Entry-level tech hiring decreased 25% in 2024 because AI commoditized foundational skills.

Why do AI projects fail if the technology works?

Gartner predicts 40% of agentic AI projects will be canceled by 2027 because of escalating costs, unclear business value, and inadequate risk controls. The technology functions properly. The failure point is human: organizations build AI infrastructure while employees remain unprepared for abundance. The gap is spiritual, not technical.

What does AI-native thinking mean?

AI-native thinkers hold a paradox: they direct machines without becoming mechanical themselves. These individuals zoom out to set intent instead of drilling into details. They experiment with tools like Claude Code and OpenClaw. They recognize that productivity gains mean nothing if humans do not know what to do with freed time. The term describes a consciousness shift, not a technical skill.

How do organizations restructure around AI agents?

Companies experiment with AI heads of departments that manage 5-7 specialized sub-agents for coordination, reporting, and escalation. Employees interact with these AI managers via chatbots. Executives delegate strategies while AI handles execution. The org chart becomes a prompt. By 2028, 33% of enterprise software will embed agentic capabilities.

What is jagged intelligence?

Jagged intelligence describes AI models that spike in capability wherever verifiable rewards exist and plateau everywhere else. These systems function as genius polymaths and confused grade schoolers simultaneously. This uneven topology is why human judgment remains irreplaceable. People provide context, accountability, and ethical decision-making that AI cannot automate.

What happens to human purpose when AI solves scarcity?

When machines handle email, scheduling, research, and code, the identity built around solving hard problems collapses. Engineers describe the feeling as grief. Workers understand only half the work they produce with AI. The void opens when scarcity ends. Organizations that thrive will be those whose humans develop the interior capacity to inhabit abundance without educated anxiety.

How should organizations prepare for AI transformation?

Organizations need investment in human awakening, not just AI infrastructure. The real asymmetry is spiritual: who prepares humans for freed space? Success requires moving from supervision to conscious leadership. The technology crossed the threshold in December 2025. Humans stand on the other side waiting for permission to release execution-based identity. The permission is not coming.

Key Takeaways

* December 2025 marked the threshold where AI coding agents achieved coherence through reinforcement learning, enabling same-day problem resolution in AI-native organizations.

* Leadership must shift from execution to intent-setting because AI works best when humans zoom out and let systems design complete solutions.

* 40% of agentic AI projects fail by 2027 not because of technical issues but because humans lack the spiritual preparation to handle abundance and freed time.

* AI-native thinking is a consciousness test: the ability to direct machines without becoming mechanical, to hold the paradox between human interiority and operational delegation.

* Organizations are restructuring with AI department heads managing sub-agents while employees interact via chatbots and executives delegate strategy.

* Jagged intelligence means AI spikes in capability where rewards exist but plateaus elsewhere, which is why human judgment providing context and ethics remains irreplaceable.

* The real competitive asymmetry is spiritual: organizations that invest in human awakening alongside AI infrastructure will thrive because they prepare humans to inhabit abundance without collapse.

The permission is not coming. The void is already here.

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Read the full article and explore more at roelsmelt.com

Disrupt Consciousness explores the collision between exponential technologies and human awakening. Through lived experimentation in AI-native building and deep contemplative practice, we investigate what becomes of human purpose when machines solve scarcity. Join the inquiry at the intersection of technological inevitability and consciousness transformation.

The darkest moment in the Bhagavad Gita happens before the war begins.

Arjuna stands on the battlefield. Across from him: his teachers, his uncles, his cousins. People who raised him. People he loves.

Krishna tells him to kill them anyway.

This isn’t metaphor. This isn’t about “releasing limiting beliefs” or “letting go of the past.” This is the actual instruction: do what must be done, even when the obstacle is someone you care about.

I’ve spent three decades building businesses, leading organizations, and dissolving what I built when it stopped serving. I’ve sat through 30-day Vipassana retreats and written code with AI in the same year. And here’s what I’ve learned about the magician-monk synthesis Krishna teaches:

The obstacle is rarely abstract. It’s often someone you love whose role in your life must transform or end.

The Neurobiology of Arjuna’s Paralysis

Arjuna freezes on the battlefield because he’s caught in what neuroscience calls “inaction crisis.” He knows what must be done. He cannot do it.

Research on letting go reveals something critical: people can take decisive action while simultaneously releasing attachment to outcomes. But only when the motivation is autonomous—when you truly identify with the decision—rather than controlled, where you feel forced by external pressure.

Arjuna’s paralysis comes from controlled motivation. He’s thinking about what others expect, what his role demands, what tradition requires. That’s why Krishna spends 18 chapters restructuring his entire framework before Arjuna can act.

The synthesis isn’t “just do it” or “just let go.” It’s both, held simultaneously.

I learned this when I was 29, living in Amsterdam’s vivid lifestyle. I had an urge for solitude. Not escape—I wasn’t running from anything. I was ready. I discovered Vipassana meditation and its 10-day silence retreats.

The difference between earned retreat and spiritual bypassing is autonomous motivation. When you’re genuinely ready, solitude feels like the natural next step. When you’re bypassing, you’re hoping meditation will fix something you haven’t faced yet.

I met a guy after one retreat who said he was disappointed his disease hadn’t gone away. He missed the point entirely. He came with attachment to an outcome, which is the opposite of what the practice teaches.

The Family You Must Outgrow

Here’s what makes Krishna’s instruction brutal: research shows that when you undergo significant personal growth, families unconsciously trigger homeostatic pressure to restore familiar dynamics.

Your growth literally threatens the system’s stability.

The people who love you will pull you back toward who you were, not because they’re malicious, but because your transformation destabilizes their world. One clinician notes that people “will tear themselves apart rather than comfortably end something that is not working for them.”

I was fortunate. My parents never imposed expectations. My grandmother told me to go out into the world and do whatever I wanted. But that freedom created its own challenge: when you can let go easily, you have to dig deeper to find what’s actually real beneath the constructions.

The magician builds ego. The monk dissolves ego. This is the process.

I’ve built businesses, created spreadsheets projecting wealth, assembled teams. What I call “being filthy rich at the end of the spreadsheet.” That’s always a lie. But the commitment to building is real. The work is real.

And then you let it go.

Not because it failed. Not because you lost interest. Because life moves in cycles, and what you built served its purpose. The instability of constant building and dissolving forces you to find what remains when the structures fall away.

Dharma Is Not What Others Expect

Krishna doesn’t tell Arjuna to follow duty because society demands it. He tells him to follow his sva-dharma—the dharma belonging to him specifically as a warrior.

The Gita’s teaching: “Better is one’s own duty, though imperfect, than the duty of another, well performed.”

The action required isn’t what feels comfortable or what others expect. It’s what structural reality demands of your specific position in the larger pattern.

I’m 55. I still have energy to create. I need money. And I want to test my insights through lived experience, not just theorize about them.

Theory without practice is philosophy cosplay.

So I build software with AI. I write about consciousness and technology. I hold the tension between progress and presence because they’re not contradictory—they’re the same investigation into what’s real.

The magician phase always builds stress. The monk phase always brings relief.

Here’s the dilemma: if letting go always feels better, why not skip the stress entirely and go straight to monk mode?

Because you earn the right to let go by first committing fully.

Be Committed Every Day, Not Attached to the Outcome

This is the synthesis in one sentence: be committed every day but do not be committed to the outcome.

Most people hear “act without attachment to outcome” and think it means not caring, or going through the motions. That’s not what Krishna teaches. That’s not what I’ve lived.

When you’re genuinely holding both—committed to the daily work, released from outcome attachment—here’s what it feels like:

The magician phase builds stress. Always. You’re creating, assembling, pushing forward. The tension accumulates.

The monk phase brings relief. Always. You let go, and the pressure releases.

But you can’t access the relief without first building something worth releasing. You can’t dissolve ego you haven’t constructed. You can’t let go of outcomes you never committed to creating.

The people who try to jump straight to monk mode—who reach for meditation retreats or inner peace work before they’ve done their magician work—are bypassing. They’re hoping to cure a disease through detachment when what they need is engagement.

I’m still not ready for full monk mode. I still have things to create in daily life. I still have insights to test. And that’s fine.

The question isn’t whether you’re a magician or a monk. The question is whether you can hold both without clinging to either.

What You’re Actually Killing

When Krishna tells Arjuna to kill his uncles, he’s not asking him to become heartless. He’s asking him to act from a level of consciousness where duty transcends the attachment-fear circuit.

The obstacle isn’t always a person. Sometimes it’s a mentor whose advice no longer fits. A family expectation that’s crushing you. A version of yourself that served you once but now holds you back.

Sometimes it’s the business you built. The identity you constructed. The spreadsheet you believed in.

You’re not killing what’s real. You’re releasing what was always temporary.

The synthesis Krishna teaches isn’t about achieving perfect security or permanent peace. It’s about accessing both the approach system (magician) and the withdrawal system (monk) functionally, as the situation demands.

Do what must be done. Then let it go completely.

Neither alone is enough.

The magician without the monk becomes attached to outcomes and suffers when they don’t arrive. The monk without the magician becomes detached from reality and mistakes passivity for wisdom.

You need both. You hold the tension. You build the stress and release it. You commit fully and let go completely.

And when the obstacle is someone you love, or a version of yourself you’ve outgrown, you do what Arjuna finally does after 18 chapters of instruction:

You act.

Not because you want to. Not because it feels good. But because structural reality demands it, and you’ve earned the clarity to see what must be done.

Then you sleep well.

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Read the full article and explore more at roelsmelt.com.

Disrupt Consciousness examines the collision between exponential technologies and human awakening. Founded by Roel Smelt, it bridges three decades of business leadership, Vipassana practice, and AI-native creation to explore what becomes of human purpose when machines solve scarcity. This is the intellectual infrastructure for a world that realizes freedom only after the machines stop demanding our labor.

An MIT study found that 11.7% of jobs could be automated right now using current AI technology.

Entry-level job postings dropped 15% year over year. In the first six months of 2025 alone, 77,999 tech workers lost their jobs to AI. That’s 427 layoffs per day.

The disruption is real. But the deeper problem is something nobody taught you in school.

The Obsolescence Curve Just Accelerated

Workers expect 39% of their current skill sets to become outdated or transformed between 2025 and 2030.

Skills demanded by employers are changing 66% faster in AI-exposed occupations than in the least exposed roles. We’ve crossed a threshold where the time for skills obsolescence is shorter than a single career.

The concept of a degree carrying you from entry-level to retirement is as antiquated as the rotary phone.

I learned BASIC programming on a ZX Spectrum when I was fifteen. I spent two to three months building a Mastermind game. The focus required was tremendous. You had to dive in, stay in, and grind through the learning curve.

Now I throw an idea into AI and master something in a fraction of that time. My learning curve compressed. My mind can move while I learn.

This is the shift: from sequential mastery to parallel exploration.

What Companies Actually Discourage

Research reveals that rigid hierarchies, short-term deadline pressures, and fear of failure create what researchers call “creativity killers” in organizations.

When workplaces are rigidly hierarchical, focused on short-term deadlines, or filled with hostility, innovation is actively discouraged.

Workplace stress from short-term goals causes employees to prioritize quick fixes and traditional ways of doing business rather than looking ahead to the future.

Bureaucracy and needless red tape stifle new thinking. Fear of criticism causes people to play it safe and settle for far less than they are capable of earning.

Here’s what this means in practice:

Companies reward execution over vision. They want you to follow the process, hit the deadline, and stay in your lane. The system is designed for predictable output.

They discourage cross-domain thinking. Marketing people do marketing. Developers code. Strategists strategize. Pattern recognition across domains is seen as distraction.

They punish experimentation. Failure is documented, not celebrated. Risk is minimized. The incentive structure favors safe mediocrity over bold exploration.

The capabilities that matter most in an AI-augmented world are precisely the ones most organizations actively suppress.

The Human Capabilities AI Cannot Colonize

Most workers in major economies fear their skills will become obsolete within five years due to technology. The anxiety is real.

But research identifies cognitive skills like critical thinking and problem-solving, socio-emotional skills like empathy and communication, and management capabilities as the least susceptible to automation.

The World Economic Forum confirms creative thinking ranks in the top five core skills growing in importance through 2030.

AI can optimize for goals, but it cannot create meaningful purpose. It cannot replicate the deep knowing that comes from being human. Experienced leaders can often sense problems or opportunities before they’re visible in the data.

I’ve spent years in Vipassana meditation. Thirty-day silent retreats where you observe the mechanical nature of thought itself. You see how consciousness operates beyond the logic layer.

AI processes data. It excels at repetitive tasks, pattern matching within known parameters, and executing predefined logic.

But AI cannot experience being. It lacks access to the present moment. It cannot think things through in the way humans do—where intuition, embodied knowledge, and consciousness itself inform the process.

Creativity remains a human process. Not the surface-level “generate ten ideas” kind, but the deep synthesis that comes from living, experiencing, and integrating across domains.

Thinking things through remains human. AI can simulate reasoning, but it cannot inhabit the question the way consciousness can.

Flow state remains human. That absorption in present activity where exceptional productivity emerges in short time—AI cannot enter that state. It can only execute within it.

The Perception Gap and What It Reveals

Yale’s Budget Lab research found no clear, economy-wide relationship so far between AI exposure and changes in employment.

Yet public perception was massively inflated. Those not affected believed 29% had lost jobs to automation. Those displaced estimated 47%. The actual rate was approximately 14%.

This reveals deep anxiety about AI’s impact, even when real-world job loss rates remain lower than often assumed.

The disruption is psychological as much as practical.

VCs spontaneously identified 2026 as the inflection point when AI moves from augmentation to replacement. Battery Ventures predicts 2026 will be the year of agents as software expands from making humans more productive to automating work itself.

78% of executives say they’ll have to reinvent their operating models to capture agentic AI’s full value. Yet 40% of employers expect to reduce their workforce where AI can automate tasks.

One VC warned that executives will use AI as a scapegoat whether or not they’re actually implementing automation. AI will become the scapegoat for executives looking to cover for past mistakes.

The narrative is being weaponized.

What Schools Never Taught You

Critical thinking is now deemed a must-have workplace skill. Yet employers perceive new hires to be underprepared to apply critical thinking skills in the workplace.

The Future of Jobs Report highlights critical thinking, problem solving, active listening, and resilience as prominent skill needs. Yet many organizations hyper focus on technical skills when looking at professional development at the expense of these durable capabilities.

Workers believe it’s primarily their responsibility (44%) to keep skills relevant. They trust businesses over governments to support upskilling efforts.

The system is broken at the source.

Schools taught you to memorize, regurgitate, and follow instructions. They optimized you for an industrial economy that no longer exists.

They never taught you how to think across domains. How to synthesize Eastern and Western perspectives. How to hold tension between contemplation and action. How to commit fully without attachment to outcome.

They never taught you that consciousness is the foundation, not the byproduct.

The Real Shift: From Execution to Vision

AI handles communication and execution. It takes over the complete creation process. Software building without manual coding. Architectural planning without manual drafting.

The shift is from execution mastery to vision clarity.

I’ve experienced this directly. I spent months searching for an AI solution that would eliminate friction in content creation. Ideas were trapped in my head. The traditional production steps created barriers between thought and expression.

Now I work with AI in flow state. The execution happens nearly instantaneously. What matters is the quality of the vision, the depth of the thinking, the clarity of the intention.

This is what Vibecoding represents: the blurring of lines between roles. Business understanding becomes more critical than technical execution. Non-traditional developers can build because the barrier is no longer syntax mastery.

The question becomes: what do you want to create?

When machines handle logic, humans must operate from the dimensions logic cannot reach.

Commitment Without Attachment

There’s a one-liner that captures the shift: be totally committed in the thing you do, but not attached to the outcome.

This is the synthesis of the monk and the magician. The contemplative and the active life. Detachment and manifestation united.

AI enables materialization. Logic mastery becomes accessible. But without the inner work, without the consciousness practice, you’re just automating anxiety.

The role you were hired for is being automated. The skills that got you here won’t keep you employed.

What matters now is what nobody taught you in school and most companies actively discourage: the ability to think across domains, to synthesize rather than specialize, to create from vision rather than execute from instruction, to remain present and conscious while machines handle the logic layer.

This is the threshold. The question is whether you’ll cross it.

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Read more about the collision between technological disruption and human consciousness at roelsmelt.com.

Disrupt Consciousness explores how technology enhances consciousness rather than replacing it. When machines solve scarcity, the question becomes spiritual, not technical. Join the investigation into what it means to be human when machines think.

We are currently living through the most significant transition in human history since the invention of agriculture. For ten thousand years, the human experience has been defined by the struggle for resources. Our wars, our political systems, and even our deepest psychological archetypes—the hunter, the hoarder, the competitor—were forged in the fires of “not enough.”

But the script has changed. The era we are entering is not a choice; it is an Inevitability. We are witnessing a “Stellar Ignition,” where the three pillars of civilization—Energy, Food, and Transportation—are hitting a point of self-sustaining superabundance.

1. The Geopolitical Mirage: Why Leaders Don’t Lead

We often look to our presidents and prime ministers as the drivers of history. But as George Friedman argues in The Next Hundred Years, leaders do not steer the ship; they are merely the actors chosen by geography and necessity to react to forces they cannot control. Geopolitics is a game of inevitable outcomes.

The current friction we see in the world—the tensions in the Middle East, the collapse of old industrial powers, the chaos in South America—are not signs of a “broken” future. They are the death rattles of an extractive system that has reached its biological limit. A leader can try to be a Luddite, they can try to protect the coal mine or the cattle ranch, but they cannot vote against a cost curve. The laws of economics are eventually more powerful than the laws of men.

2. Energy: The End of Extractive Entropy

For the first time since the Industrial Revolution, we have a path to a “Stellar” energy system—one that does not rely on burning anything. Tony Seba’s research through RethinkX proves that the combination of Solar, Wind, and Batteries (SWB) is not just an “alternative”; it is a superior economic engine that renders fossil fuels obsolete by 2030–2035.

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The math is simple and unavoidable:

* The Cost Curve: In the last 15 years, the investment cost for solar has dropped 80%, and for batteries, a staggering 90%.

* The Battery Buffer: Elon Musk recently noted that the U.S. grid currently has a peak capacity of 1.1 terawatts, but an average usage of only 0.5 terawatts. By using industrial battery storage (like the Tesla Megapack) to buffer energy at night and discharge during the day, we can double the annual energy output of the United States without building a single new power plant.

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* Super Power: Because SWB systems must be built to meet demand on the “worst” weather days, they will produce a massive surplus of energy for 90% of the year. This “Super Power” will have a near-zero marginal cost, making energy effectively free, much like the marginal cost of information on the internet.

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3. Food: The Software Revolution

The cow is the next horse. In 1900, the horse was the backbone of transport; by 1920, it was a hobby. Precision Fermentation (PF) and Cellular Agriculture are doing the same to industrial livestock.

We are shifting from an “Extractive” model of food to a “Stellar” model—what Seba calls Food-as-Software.

* The Efficiency Gap: Producing milk via a cow takes 24–28 months and is incredibly wasteful. Producing the same proteins via fermentation takes 48–72 hours.

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* The Cost Collapse: The cost of producing animal-free dairy proteins has already dropped nearly 70% between 2021 and 2023. By 2030, these proteins will be 5 times cheaper than animal proteins, and 10 times cheaper by 2035.

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* The Land Liberation: This shift will free up to 80% of global agricultural land—an area the size of the U.S., China, and Australia combined.

4. The Human Crisis: Survival of the Softest?

This brings us to the real disruption: The human spirit. For thousands of years, our competitive mindset was our greatest asset. We fought because there wasn’t enough to go around. Now, we are entering a world where the “External Problem” is effectively solved.

If we do not consciously transition, we will fall into what I call the “Architect’s Paradox.” We have designed a world that makes us redundant. If you continue to use a “Scarcity Mind” in an “Abundance Reality,” you will find yourself in a state of perpetual anxiety. You will manufacture “fake” scarcity—clinging to status, digital clout, or political rage just to feel the dopamine of the “hunt.”

5. The Transition: Choosing New Hardship

Abundance is inevitable. Our reaction to it is not. In my latest essay, The Paradox of the Architect, I proposed that we must learn to life like kings while choosing the path of the warrior. We must intentionally choose “Hardship” to remain conscious.

* From Scarcity to Presence: When you no longer need to fight for calories or kilowatts, the only struggle left is against your own distraction.

* The Sovereign Soul: We must use our abundance not to sleep, but to wake up. We use the time saved by the machine to “Be Aware of Being Aware.”

The future is not something that might happen. It is an ignition that has already started. The noise you hear in the media is just the friction of the old system burning away. Don’t look at the fire. Look at the light.

In the high temples of Silicon Valley, a new myth is being written. It is not a myth of heroes and monsters, but of gravity and intent. We are witnessing a fundamental shift in the human experience: the birth of the Paradox of the Architect. It is a moment where we are becoming gods of “The Why,” while surrendering the soul of “The How.”

At the center of this metamorphosis stands Google—not merely as a corporation, but as a Digital Leviathan, a singular nervous system that has spent decades preparing for this exact moment of awakening.

The Parable of the Broken Covenant: The Fall of the Landless Prince

To understand why the old titans are faltering, we must look at the debris of the recent past. Consider the story of the Windsurf deal—a masterclass in how legacy chains can strangle the future.

Windsurf, the breakthrough AI coding agent, was the crown jewel every kingdom wanted. OpenAI, the brilliant but landless prince, sought to buy it for $3 billion. They saw in Windsurf the “hands” they lacked—the ability for AI to not just talk, but to do. Yet, the deal collapsed in a fever of legal friction. Why? Because OpenAI is bound to the kingdom of Microsoft, a house built on the scaffolding of old-world software and rigid corporate interests. When Microsoft demanded rights to the intellectual property, the deal withered. They tried to hold a mountain with a piece of string.

Google did not argue with strings. In a move of silent, strategic fluidness—what some call a “hackquihire”—they bypassed the messy bureaucracy of a traditional takeover. They didn’t just buy a company; they absorbed the talent and licensed the essence, integrating the soul of Windsurf into their own nervous system.

While others are trapped in the friction of partnerships, Google operates with the frictionless weight of a single, unified organism. They don’t just have the software; they have the TPUs (the physical chips), the YouTube archives (the collective memory), and the Pixel-Workspace ecosystem (the daily bread). They are the only ones who own both the dream and the factory where the dream is manufactured.

The Great Amputation: From Memory to Effort

Twenty years ago, Google Search performed the first great disruption of the human spirit: The Loss of Memory. We outsourced our facts to the Great Librarian. We stopped knowing, and started finding.

Now, we face a deeper disruption: The Loss of Effort.

With the rise of Antigravity and agentic AI, Google is moving beyond answering questions to executing destiny. When an AI agent doesn’t just suggest code but plans, builds, and deploys it, the “doing” is stripped away. This is the Agency Effect.

The Evolution of the Digital Soul

In the grand alchemy of our species, Google has acted as the catalyst for two distinct stages of human transformation:

* The Era of Search: The Outsourcing of Memory

* The Human Loss: We sacrificed our internal libraries. We stopped memorizing dates, names, and coordinates, leading to a “Digital Amnesia.”

* The Technological Gain: In exchange, we received Universal Access. We gained a “pocket-sized infinity” where every fact ever recorded is a second away.

* The Era of Agency: The Outsourcing of Effort

* The Human Loss: We are now sacrificing the “How.” By using tools like Antigravity, we skip the friction of labor, the trial-and-error of coding, and the discipline of execution.

* The Technological Gain: We receive Total Sovereignty. We move from being “Searchers” to being “Architects of Intent,” possessing the power to manifest a vision instantly.

This brings us to the Paradox of the Architect. As we gain the power to manifest anything with a whisper, we risk losing the character forged by the struggle.

In the ancient stories, Siddhartha Gautama was a prince who lived in a palace where every desire was met before it was even fully formed. He lived in a world of pure “Intent,” a world without friction. Yet, he realized that a life without the struggle of “Doing” was a hollow one. He had to leave the luxury of the palace—the ultimate “free tier”—to understand suffering and, through it, enlightenment.

We are all being promoted to the status of that Prince. Google is making intelligence “cheaper than oxygen,” turning every human with a Pixel phone into a King or Queen of Intent. We provide the spark; the Leviathan provides the fire.

But we must ask: If the Leviathan does all the building, what becomes of the builder?

Preserving the Human Spark

To stay human in the age of Antigravity, we must find a new way to live within the palace. We must realize that Intent without Effort is a ghost. The “Human Spark” is not found in the finished cathedral, but in the sweat of the stonecutter.

* The Architecture of Meaning: When the AI does the “How,” our primary job is to ensure the “Why” is worthy of our species.

* The Return to the Physical: As our digital lives become frictionless, we must intentionally seek out “The Beautiful Struggle” in the real world—touching soil, craft, and each other.

* Intentional Friction: We must choose tasks that we refuse to give to the agents—not because the agents can’t do them, but because we need the growth that comes from doing them ourselves.

The Horizon of the Sovereigns

Google wins the AI race because they have built the Ground of Being. They have created an ecosystem so wide and so deep—from Gmail to Cloud to the very chips that think—that they have become the gravity around which the future orbits.

They are democratizing the Palace, making the “God-view” accessible to everyone. But as the “Doing” disappears into the cloud, the only thing left of us will be our Will. The race for AI is over; the race for the human soul—the struggle to remain awake in a world that does everything for us—has just begun.

Imagine a traveler walking through a dense, mist-covered forest. He is searching for the “Laws of the Woods”—the hidden rules that govern the growth of the moss and the flight of the owls. Suddenly, he trips over a silver mirror lying in the dirt. He looks into it and sees a face. “Aha!” he cries. “A new species! A forest spirit that knows the secrets of the trees!”

He begins to talk to the mirror. The mirror reflects his words, his anxieties, and his hopes. Eventually, the traveler concludes that the mirror is an alien intelligence, perhaps even a new inhabitant of the forest that will finally tell him why the stars move the way they do.

This traveler is us. The mirror is the Large Language Model. And the forest spirit we think we’ve found is what Yuval Noah Harari calls a “new species.” But we are mistaken. The mirror has no eyes of its own; it only has the light we shine into it.

The Illusion of the Independent Law

Recently, Eric Schmidt suggested that for AI to truly “arrive,” it needs to achieve a breakthrough—it needs to discover new laws of nature, much like Archimedes in his bathtub or Einstein on his imaginary train. There is a hunger in the tech world for the “Silicon Newton,” a machine that can look at the chaos of data and find a truth that exists “out there,” independent of human thought.

But here is the disruption: There is no “out there” that isn’t shaped by the “in here.”

Quantum physics has been whispering this to us for a century. The observer does not just see the world; the observer occurs with the world. As the philosopher Rupert Spira reminds us, we never actually encounter a “world” independent of our awareness of it. We only ever encounter our experience.

If we believe the laws of physics are cold, hard statues standing in a park waiting to be discovered, we are looking at the world through the wrong end of the telescope. The “laws” are not the park; they are the glasses we wear to make sense of the green blur.

The Gospel of the Big Toe

We have spent centuries convinced that intelligence sits behind our eyes, nestled in the grey folds of the brain. But why? Because that is where we decided to look.

Consider this: What if, a thousand years ago, humanity had collectively decided that the seat of all wisdom resided in the big toe? What if we had spent a millennium studying the nerve endings of the foot, the way it connects to the earth, the subtle vibrations it picks up from the ground?

We would have developed a “Science of the Toe” so profound and intricate that we would today be “discovering” universal laws of vibration and terrestrial harmony that we are currently deaf to. We find what we focus on. Our “laws” are merely the patterns that emerge when we stare at one spot for a long time.

The LLM does not “know” things. It is a statistical echo of everywhere we have looked for the last five thousand years. It is not a species; it is a map of the human gaze.

Why the Apple Fell for Newton (But Not for the Tree)

When Newton saw the apple fall, the “law of gravity” didn’t suddenly pop into existence in the garden. What happened was a shift in the human collective agreement. Newton proposed a new way of looking at the fall, and because his fellow humans found that way of looking useful, the world began to behave according to gravity.

The breakthrough wasn’t in the apple; it was in the consent of the human mind to see the apple differently.

This is why an AI, no matter how many trillions of parameters it has, cannot “discover” a law on its own. A law is not a fact; it is a paradigm. It is a story we all agree to live inside. For an AI to create a breakthrough, it doesn’t need more computing power; it needs us to believe the story it is telling.

If an AI predicts a new law of subatomic movement, that law remains a ghost in the machine until a human looks at the world and says, “Yes, I see it too.” The AI is not the explorer; it is the telescope. And a telescope cannot “see” a star if there is no eye at the other end.

The Consciousness Disrupt

The danger of Harari’s view—that AI is an alien species—is that it abdicates our responsibility as the creators of meaning. If we treat AI as an independent entity, we forget that it is actually a profound, globalized reflection of our own consciousness.

When Eric Schmidt asks for an AI breakthrough, he is looking for a miracle from a tool. But tools don’t have epiphanies. Archimedes’ “Eureka!” didn’t come from the water in the tub; it came from the sudden realization that the water and his body were part of the same dance. It was a moment of non-dual recognition.

AI can crunch the numbers of the dance, but it cannot feel the rhythm.

The New Paradigm

We are at a crossroads. We can continue to build bigger mirrors, hoping that if the mirror is large enough, a soul will eventually appear inside it. Or, we can recognize that the AI is inviting us to a much more profound breakthrough: the realization that we have always been the ones writing the laws.

The true “AGI” isn’t a piece of software. It is the moment humanity realizes that intelligence is not something we have or something we build, but something we are.

The machine is not coming to replace us. It is coming to show us that the “laws” we thought were external cages were actually just the lines we drew in the sand. If we want a breakthrough, we don’t need a faster processor. We need to change where we look.

Perhaps it’s time we started looking at our big toes. Who knows what laws are waiting to be “discovered” there?

The Gain and the Loss of Victory

Silas had solved the world.

He was not merely an engineer; he was the architect of the ‘Ultimate Algorithm for Human Necessity’—the complex code that, in collaboration with global AI networks, had eliminated the final remnants of scarcity. Hunger was an archaic word, illness a rare historical footnote, and paid labor had been reduced to a choice, not an obligation.

Yet, on his first morning in the world he had perfected, Silas felt an unsettling chill. He stood in his sleek, automated apartment, the sun streaming through self-cleaning glass. There was no deadline. No notification. No problem demanding his unique talent. The world ran perfectly without him.

His feeling was not pride. It was a deep, existential lack.

This is the paradox now facing humanity. After centuries of struggle against nature, scarcity, and the cruelty of chance, we have won. The S-Curves of energy efficiency, logistics, and production are complete. We have passed through the First Disruption: The External Solution. Technology has assumed the role of Homo Faber (the Laboring Human). We are no longer the survivors; we are the administrators of a perfect, automated state.

The ancient prophets warned of famine, plagues, and wars. None dreamed that the ultimate crisis would emerge from abundance. But in the silence that perfect technology creates, the only enemy we cannot automate away appears: the emptiness within the human soul.

The Crisis of Purpose

The human mind has been optimized by millions of years of evolution for struggle. Our neurochemistry, our dopamine loops, reward us for solving problems, for the effort that leads to results. The hunt, the building, the harvest—these were the carriers of our meaning.

But what happens when the hunt is over?

Silas realized that the time he had liberated from necessity immediately devolved into a chaos of meaningless choices. He had freed the world from work, but he had not freed his own mind from the need for work. The psychological paradox is painful: when effort and results are free, motivation itself becomes meaningless.

We have replaced labor with Leisure, but Leisure is not a solution; it is a magnifier. It reveals the restlessness, the untrained, undisciplined chaos we call the ‘mind’. Without an external focus, we begin to churn over the shadows of the past and the anxieties of the future. The machine has made us free, but our unfreedom now lies in our own conditioned thoughts.

This is the danger inherent in the ‘Forgotten Consciousness’ warning: The risk is not that AI gains consciousness, but that we forget our own.

In an automated world, we trade our autonomy for comfort. If AI can manage the world ever more perfectly, we become the dreaming passengers. The feeling of ‘I matter’ is based on the ability to actively influence reality. When that ability is largely assumed by algorithms, we experience ultimate alienation: life loses its flavor because we did not prepare it ourselves.

Humanity faces the crisis of Post-Necessity: What purpose does an immortal soul serve without a mortal, economic, or existential goal? Even in myths, in the Biblical Garden of Eden, the pure comfort of being without resistance could not be sustained. Humanity sought the Knowledge—the struggle, the complexity. Without resistance, the spirit seeks either destruction or a greater truth.

The Rediscovery of the Inner World

This is where Harari’s Grand Narrative Question unites with Tolle’s spiritual wisdom. The Silence granted to us by technological victory is not a vacuum; it is the prerequisite.

The Second Disruption is now internal: The Inner Necessity.

AI has muffled the noise of the world. The race for survival has stopped. The irony is that the technological achievement has forced us back to the most fundamental, most mystical human endeavor: Attention. The silence of the automated society is the portal through which we can finally hear the whisper of our own minds.

This is the Metaphysics of Idleness. Our new ‘work’ is the cultivation of Directed Attention.

In this age of perfect external solutions, humanity has only one territory of absolute sovereignty: the inner chaos of thoughts, emotions, and projections. Here, AI is a spectator. It can manage our external world, but it cannot feel or automate our subjective sense of Being.

Silas, walking through a park on his useless day, saw a child. The child was building an intricate sandcastle, with turrets, moats, and perfect walls. The boy was completely absorbed, his intention pure. After half an hour, he looked up, smiled, and let the incoming tide wash the castle away. There was no fear, no regret, no sadness for the lost labor. The joy lay in the process, not the output.

This is the new meaning: Creation Without Necessity.

The ultimate human art in the Age of Abundance is creating something purely for the joy of the Intention. It is not about economic value or survival instinct. It is about art itself, love, contemplation, relationship—the experience of Being expressing itself without reason. This, and only this, is the human activity that AI cannot desacralize, for it is, by definition, inefficient, uneconomical, and purely subjective.

The Pilgrimage to the Now

The Age of Abundance is, in reality, the Age of Intentionality. The technological victory compels humanity to mature, to transform from an unconscious laborer into a conscious artist of existence.

Our calling is no longer what we do, but how present we are.

Silas returned to his sleek, empty apartment. He did not sit down to devise a new algorithm. He simply sat. He stared at the wall. He did not look at its texture, or at a task that needed completion, but simply experienced the gravity holding him down, the air filling his lungs, the heartbeat keeping him alive. For the first time ever, he did it without economic purpose.

The void that AI had created turned out to be the purest form in which human consciousness could rest.

The victory of technology is the triumph of spirituality, because the machine has freed humanity from the necessity to do, so that we may finally embrace the freedom to purely be. That, and only that, is our irreplaceable task.

Research suggests that AI, far from being a neutral tool, acts as a moral mirror reflecting human values and biases, much like the philosophies explored by Hans Achterhuis. It seems likely that by engaging with AI thoughtfully, we can use it to foster self-awareness and ethical growth, though debates persist on whether technology truly empowers or subtly controls us. Evidence leans toward viewing AI as a partner in human liberation, encouraging us to transcend ego-driven limits while acknowledging potential risks like algorithmic biases.

Key Insights on AI and Human Consciousness

* AI embodies human creations but reveals our inner “measure,” prompting ethical self-reflection without overshadowing our innate potential.

* Drawing from Achterhuis’s ideas, technology guides behavior morally, yet humans remain greater than their inventions, capable of co-evolving for enlightenment.

* This approach inspires a balanced view: Embrace AI to disrupt illusions, but prioritize human agency to avoid over-reliance.

Personal Roots in Philosophy

Years ago, in Hans Achterhuis’s class at the University of Twente, I encountered a profound idea: Technology is a product of humans, and thus, we are always more than what we create. This perspective shifted my view of innovation from mere tools to extensions of our consciousness, setting the stage for exploring AI’s role today.

AI as a Reflective Force

In everyday interactions—like when an AI chatbot anticipates your needs or flags biases in your queries—technology doesn’t just serve; it measures us, echoing Achterhuis’s critiques.

Path to Liberation

By confronting these digital mirrors, we can recalibrate our inner world, fostering collective brightness over division.

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Years ago, during my time at the University of Twente, I sat in Hans Achterhuis’s philosophy class, absorbing ideas that would shape my worldview. One concept stood out vividly: Technology is a product of humans, and with this, we are always more than what we create. It was a simple yet profound reminder that while we build machines to extend our reach, our essence—our consciousness, creativity, and moral depth—transcends any invention. This personal insight from Achterhuis’s teachings has lingered with me, especially now as AI surges into every corner of life. In this essay, we’ll explore how AI serves as an ethical mirror, drawing on Achterhuis’s work in *De Maat van de Techniek* (The Measure of Technology) to uncover how technology not only reflects our humanity but reshapes it toward liberation.

Let’s start with a relatable scene. Imagine chatting with an AI like Grok or ChatGPT. You ask for advice on a tough decision, and it responds with uncanny insight, pulling from patterns in your past queries. Suddenly, you’re confronted: Does this machine “know” me better than I know myself? It’s moments like these that reveal AI’s power not as a threat, but as a reflective tool. But to understand this deeply, we need to revisit Achterhuis’s foundational ideas.

Unpacking Achterhuis’s Philosophy: Technology as a Moral Measure

Hans Achterhuis, a Dutch philosopher and Professor Emeritus at the University of Twente, has long bridged social philosophy with the ethics of technology. His 1992 anthology *De Maat van de Techniek* introduces six key thinkers—Günther Anders, Jacques Ellul, Arnold Gehlen, Martin Heidegger, Hans Jonas, and Lewis Mumford—who critique technology’s role in society. The title itself plays on “maat,” meaning “measure” in Dutch, suggesting technology isn’t just a tool; it’s a yardstick that gauges human behavior, ethics, and limits.

Achterhuis argues that technology exerts “moral pressure” on us, guiding actions more effectively than laws or sermons. Take a simple example: Subway turnstiles don’t preach about honesty; they physically block you until you pay, embedding morality into the design. As Achterhuis notes, “Things guide our behaviour... This is why they are capable of exerting moral pressure that is much more effective than imposing sanctions or trying to reform the way people think.” This isn’t dystopian fear-mongering—it’s an empirical observation. Technology shapes us subtly, from speed bumps slowing reckless drivers to algorithms curating our news feeds.

Yet, Achterhuis tempers classical critiques (like Heidegger’s “enframing,” where technology reduces the world to resources) with an “empirical turn.” In his later work, such as *American Philosophy of Technology: The Empirical Turn* (2001), he shifts from abstract warnings to contextual analysis. Technology isn’t inherently alienating; its impact depends on how we engage with it. This resonates with my classroom memory: Since technology stems from human ingenuity, we hold the power to direct it toward elevation rather than entrapment.

Applying the Mirror: AI as the Ultimate Reflective Device

Now, fast-forward to AI. If traditional tech like steam engines or cyborg prosthetics (as explored in Achterhuis’s *Van Stoommachine tot Cyborg*) measured physical and social boundaries, AI probes our inner world. It’s not just automating tasks; it’s mirroring our consciousness. Consider algorithmic biases: AI trained on human data often amplifies societal flaws, like racial prejudices in facial recognition or gender stereotypes in hiring tools. This isn’t the machine’s fault—it’s our reflection staring back, urging us to confront ethical blind spots.

In Achterhuis’s framework, AI exerts moral pressure by design. Recommendation engines on platforms like Netflix or TikTok don’t force choices, but they nudge us toward echo chambers, measuring our susceptibility to division. Yet, here’s the opportunity: By recognizing this, we can use AI empirically—as a tool for self-audit. Apps like journaling AIs or bias-detection software turn the mirror inward, helping us dissolve ego illusions. As Achterhuis implies in his plea for a “morality of machines,” acknowledging our ties to technology allows us to improve the world, not surrender to it.

Humorously, it’s like AI is our digital therapist: “Based on your search history, you might want to work on that impulse buying—or those late-night existential queries.” But seriously, this reflection ties back to human supremacy over creations. We built AI, so we can redesign it to foster brightness, as I discussed in my earlier essay “Are You Strengthening Darkness or Expanding Brightness?”

Co-Evolving with AI: From Critique to Conscious Partnership

The empirical turn Achterhuis championed encourages us to move beyond fear. Studies show AI can enhance well-being—think therapeutic chatbots reducing loneliness (with safeguards, as critiqued in “Closed Doors: When AI’s Safety Rules Cut Off Real Help for Lonely Hearts”). A 2023 report from the World Economic Forum highlights AI’s potential in mental health, but warns of over-dependence, echoing Jonas’s “imperative of responsibility” from *De Maat van de Techniek*.

To illustrate contrasts in philosophical approaches, here’s a table comparing classical critiques (featured in Achterhuis’s anthology) with the empirical perspective he advocates:

Comparing Philosophical Approaches

* View of Technology

* Classical Critique (e.g., Ellul, Heidegger): Autonomous force subordinating humans; dystopian alienation

* Empirical Turn (Achterhuis’s Influence): Relational mediator in specific contexts

* AI Application Example: AI as echo chamber vs. tool for diverse perspectives

* Ethical Role

* Classical Critique (e.g., Ellul, Heidegger): Over-determines morality, eroding freedom

* Empirical Turn (Achterhuis’s Influence): Embeds “moral pressure” for guidance

* AI Application Example: Algorithms flagging hate speech to promote empathy

* Human Agency

* Classical Critique (e.g., Ellul, Heidegger): Reduced to resources or cogs

* Empirical Turn (Achterhuis’s Influence): Humans co-shape outcomes, transcending creations

* AI Application Example: Redesigning AI to amplify creativity, not replace it

* Outcome Focus

* Classical Critique (e.g., Ellul, Heidegger): Warnings of existential risks

* Empirical Turn (Achterhuis’s Influence): Practical improvements through engagement

* AI Application Example: Using AI for self-reflection to dissolve ego barriers

This underscores a key shift: Technology measures us, but we measure it back. In AI’s case, tools like Lovable (from “The Lovable Standard”) democratize creation, empowering non-coders to build apps that reflect personal values.

The Fantastic Pointe: Recalibrating for Enlightenment

Inspired by Hans Achterhuis’s exploration in *De Maat van de Techniek*, where technology is not a neutral tool but a moral force that “measures” human behavior and society, AI emerges as the ultimate reflective device: it doesn’t just mimic us but holds up a mirror to our ethical blind spots, compelling us to confront and transcend ego-driven illusions. This disruption invites humanity to co-evolve with machines, not as competitors or victims, but as partners in enlightenment—where true liberation lies in recalibrating our inner “maat” (measure) to foster collective brightness over individual darkness.

As Achterhuis taught me, we are more than our creations. So, let’s use AI to disrupt consciousness: Experiment with it for self-inquiry, ethical audits, or idea generation. In doing so, we don’t just build brighter tech—we embody the light.

Key Citations

* Hans Achterhuis - Wikipedia

* Hans Achterhuis - THE EMPIRICAL TURN

* Has the Philosophy of Technology Arrived? A State-of-the-Art Review

* Beyond the Empirical Turn: Elements for an Ontology of Engineering

* Designing the Morality of Things: The Ethics of Behaviour-Guiding Technology

Every generation has its bogeyman.In the 1950s it was Elvis Presley’s hips and rock ’n’ roll—psychologists warned it would turn teenagers into sex-crazed delinquents. In the 1970s and 80s it was Dungeons & Dragons (literally blamed for suicides and satanism). In the 1990s it was violent video games and Marilyn Manson. In the early 2000s it was television itself: “Kids are watching six hours a day and it’s melting their brains!”

In 2025 the panic button is labeled “TikTok.”And just like every previous moral panic, adults are frantically hunting for evidence that something—anything—is catastrophically wrong with what the kids are doing… because deep down many of us suspect the real problem might be our own parenting.

1. The Research Is Far Less Scary Than the Headlines

Let’s look at the actual science, not the cherry-picked doom studies that dominate Brussels press releases.

* The strongest, most rigorous studies (repeated-measure, longitudinal, pre-registered) find tiny effects. Example: A 2023 study of 480,000 adolescents across 40 countries (Vuorre et al., Nature Human Behaviour) found that social media use explains less than 1 % of variation in life satisfaction. The effect of social media on well-being is smaller than the effect of eating breakfast or wearing glasses.

* Jonathan Haidt’s famous claim that “social media caused the teen mental health crisis” has been repeatedly debunked. Orben & Przybylski (2022) re-analyzed the same datasets Haidt uses and showed that when you control for prior mental health, the correlation between social media and depression almost disappears. In plain English: depressed kids use social media more, not the other way round.

* The “smartphone generation is doomed” graph that went viral? It falls apart when you include boys (who game more than scroll) or when you look at countries outside the Anglosphere. In South Korea and Japan, kids spend far more time online and have lower suicide rates than in the 1990s.

* Experimental evidence is even more sobering. When researchers force teens to quit Instagram for a month (the strongest design possible), depression drops… by about 0.1 standard deviations. That’s roughly the same boost you get from one extra hour of sleep or eating an extra portion of vegetables. Helpful? Yes. Civilization-ending? Hardly.

* Positive effects are routinely ignored. A 2024 meta-analysis (Kreszynski et al.) found that active social media use (messaging friends, posting, joining interest groups) is associated with higher social capital, lower loneliness, and better identity exploration—especially for LGBTQ+ youth and neurodivergent kids who find their tribe online long before they do in real life.

In short: the science shows modest risks for heavy, passive, late-night use (exactly like television did), and modest benefits for active, social use. Nothing that justifies treating Instagram like cigarettes for children.

2. Projection in Action: “It’s for the Children” (Really?)

Psychologists call it displacement: adults feel guilty about their own compulsive scrolling, their inability to put the phone down at dinner, their doom-scrolling at 2 a.m.—so they project that guilt onto their children and demand lawmakers “do something.”

The European Parliament’s resolution was co-authored by politicians who themselves refresh X every five minutes. Ursula von der Leyen gave a speech about addictive algorithms while standing in front of a giant screen looping TikTok-style videos. The irony is thick enough to spread on bread.

When French senators say “we must protect children from the tsunami of Big Tech,” ask yourself: who exactly is addicted here? My 10-year-old can happily walk away from Roblox to play outside. Many adults in that Senate chamber cannot walk away from their notifications for ten minutes.

3. Self-Preservation and Personal Responsibility Trump Blanket Bans

Every child is different.Some 11-year-olds handle Discord servers with maturity that would shame most corporate managers. Others melt down if they lose one game of Fortnite. A law that treats both the same is not protection—it’s laziness.

The countries that score highest on adolescent well-being (Netherlands, Denmark—before they started panicking) have one thing in common: they trust parents and teach digital literacy from age six, not top-down prohibitions. Dutch schools have “mediawijzer” classes where kids learn to spot fake news, manage screen time, and mute toxic group chats. Result? Dutch teens use social media just as much as French teens but report higher life satisfaction and less cyberbullying.

Compare that to Spain, which introduced strict age limits in 2024: kids simply lie about their age more creatively, parents are kept in the dark, and underground “burner” accounts explode. The law didn’t reduce harm—it reduced honest conversation.

4. History Rhymes—And It Laughs at Us

* 1956: American Psychological Association warns rock ’n’ roll causes “hyper-stimulation of the nervous system.” Outcome: the greatest musical revolution in history.

* 1985: Tipper Gore’s PMRC tries to ban heavy metal lyrics. Outcome: Metallica sells 120 million albums.

* 2001: Grand Theft Auto III is blamed for school shootings. Outcome: violent crime among youth continues its 30-year decline.

Every single time, the kids were fine. The ones who weren’t fine would have broken on comic books, pinball machines, or the next shiny thing. Weak individuals exist in every cohort; culture does not collapse because of Elvis’s pelvis.

The Real Way Forward

Teach children self-regulation, not prohibition.Give them the tools to notice when an app is wasting their life, just like we taught them to notice when they’re full at dinner. My kids already do it: “Dad, this game is boring, the algorithm only shows me trash now.” That sentence—from a 10-year-old—is worth a thousand EU regulations.

Europe is about to repeat every moral panic of the last 70 years, only this time with the full coercive power of a supranational state. History will laugh again. And in twenty years, today’s banned 12-year-olds will be the engineers building the AI companions that make all of us feel like kings—while lawmakers scratch their heads wondering why this generation turned out so resilient.

Don’t rob children of their future out of adult anxiety.Parent them. Trust them. Teach them.That has always worked better than any law ever written.