Month: August 2025

Back to the Page: Preparing for Another Novel Attempt

After years of circling around it like a cautious cat, I find myself psychologically ready to tackle a novel again. The familiar weight of possibility sits on my chest—equal parts excitement and dread. But this time feels different. This time, I’m determined to approach it with the deliberation that age and experience have taught me.

The Eternal Question: Am I Any Good?

There’s something uniquely humbling about calling yourself an “aspiring novelist” for years on end. The word “aspiring” starts to feel less like hope and more like a permanent state of being—a creative purgatory where you’re neither established nor entirely amateur. After all this time, I still don’t know if I’m any good. The question hangs there, unanswered and perhaps unanswerable until you actually finish something and put it into the world.

But maybe that’s the wrong question entirely. Maybe the better question is: “Do I have something worth saying?” And increasingly, I think I do.

The Power of Preparation

This time around, I’m taking a different approach. Instead of diving headfirst into prose with nothing but enthusiasm and caffeine, I’m forcing myself to slow down. To think. To prepare.

The preparation feels crucial now in a way it never did before. When you’re younger, you can afford to write your way into a story, to discover it as you go, to throw away thousands of words without a second thought. But when you’re older—when time feels more finite and precious—every word needs to count more.

So I’m starting with character motivation. Before I write a single scene, I want to understand why my characters do what they do, what drives them, what they fear. I want to know them well enough that when they surprise me on the page (and they will), those surprises will feel inevitable rather than random.

A Genre-Bending Vision

The idea that’s captured my imagination is a science fiction story that blends elements from three films that have stuck with me: Annie Hall, Her, and Ex Machina. It’s an unusual combination—Woody Allen’s neurotic romanticism, Spike Jonze’s exploration of human-AI intimacy, and Alex Garland’s philosophical thriller about consciousness and manipulation.

Twenty-five years ago, I would have immediately started outlining this as a screenplay. The visual possibilities, the dialogue-heavy scenes, the intimate character study—it all screams cinematic. But I’m not 25 anymore, and that realization comes with both loss and liberation.

The loss is obvious: the dreams of Hollywood, of seeing your words transformed into moving images, of red carpets and industry recognition. But the liberation is perhaps more valuable: the freedom to explore this story in the medium that allows for the deepest dive into consciousness and interiority—the novel.

The Weight of Age and Wisdom

Being “older” (though not quite “old”) changes everything about the creative process. There’s less time for false starts, less tolerance for projects that don’t truly matter. But there’s also more life experience to draw from, more understanding of human nature, more appreciation for nuance and complexity.

The romantic neuroses that fascinated me about Annie Hall now feel lived-in rather than observed. The loneliness and connection explored in Her resonates differently when you’ve experienced more varieties of both. The questions about consciousness and authenticity in Ex Machina feel more urgent when you’ve had more time to question your own.

Contemplation Before Creation

So before I get swept away by the excitement of a new project—before I start imagining book tours and literary prizes—I’m making myself sit with the questions. What is this story really about? What am I trying to explore through the lens of human-AI relationships? How do the themes of connection, authenticity, and consciousness intersect in meaningful ways?

This contemplation isn’t procrastination (though the line between the two can be thin). It’s preparation. It’s the difference between building a house with blueprints versus hoping the foundation holds as you add rooms.

The Long Game

Perhaps that’s what changes most with age: the understanding that good work takes time, that the best stories are the ones that have been allowed to marinate in your mind before they hit the page. The urgency is still there—if anything, it’s stronger—but it’s tempered by patience.

I may not know yet if I’m any good as a novelist. But I know I have stories worth telling, and I know that this time, I’m going to tell them with all the care and consideration they deserve.

The blank page is waiting. But first, a little more thinking.

The Silver Lining of an AI Development Wall

While much of the tech world obsesses over racing toward artificial general intelligence and beyond, there’s a compelling case to be made for hitting a developmental “wall” in AI progress. Far from being a setback, such a plateau could actually usher in a golden age of practical AI integration and innovation.

The Wall Hypothesis

The idea of an AI development wall suggests that current approaches to scaling large language models and other AI systems may eventually hit fundamental limitations—whether computational, data-related, or architectural. Instead of the exponential progress curves that many predict will lead us to AGI and ASI within the next few years, we might find ourselves on a temporary plateau.

While this prospect terrifies AI accelerationists and disappoints those eagerly awaiting their robot overlords, it could be exactly what humanity needs right now.

Time to Marinate: The Benefits of Slower Progress

If AI development does hit a wall, we’d gain something invaluable: time. Time for existing technologies to mature, for novel applications to emerge, and for society to adapt thoughtfully rather than reactively.

Consider what this breathing room could mean:

Deep Integration Over Rapid Iteration: Instead of constantly chasing the next breakthrough, developers could focus on perfecting what we already have. Current LLMs, while impressive, are still clunky, inconsistent, and poorly integrated into most people’s daily workflows. A development plateau would create pressure to solve these practical problems rather than simply building bigger models.

Democratization Through Optimization: Perhaps the most exciting possibility is the complete democratization of AI capabilities. Instead of dealing with “a new species of god-like ASIs in five years,” we could see every smartphone equipped with sophisticated LLM firmware. Imagine having GPT-4 level capabilities running locally on your device, completely offline, with no data harvesting or subscription fees.

Infrastructure Maturation: The current AI landscape is dominated by a few major players with massive compute resources. A development wall would shift competitive advantage from raw computational power to clever optimization, efficient algorithms, and superior user experience design. This could level the playing field significantly.

The Smartphone Revolution Parallel

The smartphone analogy is particularly apt. We didn’t need phones to become infinitely more powerful year after year—we needed them to become reliable, affordable, and ubiquitous. Once that happened, the real innovation began: apps, ecosystems, and entirely new ways of living and working.

Similarly, if AI development plateaus at roughly current capability levels, the focus would shift from “how do we make AI smarter?” to “how do we make AI more useful, accessible, and integrated into everyday life?”

What Could Emerge During the Plateau

A development wall could catalyze several fascinating trends:

Edge AI Revolution: With less pressure to build ever-larger models, research would inevitably focus on making current capabilities more efficient. This could accelerate the development of powerful edge computing solutions, putting sophisticated AI directly into our devices rather than relying on cloud services.

Specialized Applications: Instead of pursuing general intelligence, developers might create highly specialized AI systems optimized for specific domains—medical diagnosis, creative writing, code generation, or scientific research. These focused systems could become incredibly sophisticated within their niches.

Novel Interaction Paradigms: With stable underlying capabilities, UX designers and interface researchers could explore entirely new ways of interacting with AI. We might see the emergence of truly seamless human-AI collaboration tools rather than the current chat-based interfaces.

Ethical and Safety Solutions: Perhaps most importantly, a pause in capability advancement would provide crucial time to solve alignment problems, develop robust safety measures, and create appropriate regulatory frameworks—all while the stakes remain manageable.

The Tortoise Strategy

There’s wisdom in the old fable of the tortoise and the hare. While everyone else races toward an uncertain finish line, steadily improving and integrating current AI capabilities might actually prove more beneficial for humanity in the long run.

A world where everyone has access to powerful, personalized AI assistance—running locally on their devices, respecting their privacy, and costing essentially nothing to operate—could be far more transformative than a world where a few entities control godlike ASI systems.

Embracing the Plateau

If an AI development wall does emerge, rather than viewing it as a failure of innovation, we should embrace it as an opportunity. An opportunity to build thoughtfully rather than recklessly, to democratize rather than concentrate power, and to solve human problems rather than chase abstract capabilities.

Sometimes the most revolutionary progress comes not from racing ahead, but from taking the time to build something truly lasting and beneficial for everyone.

The wall, if it comes, might just be the best thing that could happen to AI development.

The ‘Personal’ ASI Paradox: Why Zuckerberg’s Vision Doesn’t Add Up

Mark Zuckerberg’s recent comments about “personal” artificial superintelligence have left many scratching their heads—and for good reason. The concept seems fundamentally flawed from the outset, representing either a misunderstanding of what ASI actually means or a deliberate attempt to reshape the conversation around advanced AI.

The Definitional Problem

By its very nature, artificial superintelligence is the antithesis of “personal.” ASI, as traditionally defined, represents intelligence that vastly exceeds human cognitive abilities across all domains. It’s a system so advanced that it would operate on a scale and with capabilities that transcend individual human needs or control. The idea that such a system could be personally owned, controlled, or dedicated to serving individual users contradicts the fundamental characteristics that make it “super” intelligent in the first place.

Think of it this way: you wouldn’t expect to have a “personal” climate system or a “personal” internet. Some technologies, by their very nature, operate at scales that make individual ownership meaningless or impossible.

Strategic Misdirection?

So why is Zuckerberg promoting this seemingly contradictory concept? There are a few possibilities worth considering:

Fear Management: Perhaps this is an attempt to make ASI seem less threatening to the general public. By framing it as something “personal” and controllable, it becomes less existentially frightening than the traditional conception of ASI as a potentially uncontrollable superintelligent entity.

Definitional Confusion: More concerning is the possibility that this represents an attempt to muddy the waters around AI terminology. If companies can successfully redefine ASI to mean something more like advanced personal assistants, they might be able to claim ASI achievement with systems that are actually closer to AGI—or even sophisticated but sub-AGI systems.

When Zuckerberg envisions everyone having their own “Sam” (referencing the AI assistant from the movie “Her”), he might be describing something that’s impressive but falls well short of true superintelligence. Yet by calling it “personal ASI,” he could be setting the stage for inflated claims about technological breakthroughs.

The “What Comes After ASI?” Confusion

This definitional muddling extends to broader discussions about post-ASI futures. Increasingly, people are asking “what happens after artificial superintelligence?” and receiving answers that suggest a fundamental misunderstanding of the concept.

Take the popular response of “embodiment”—the idea that the next step beyond ASI is giving these systems physical forms. This only makes sense if you imagine ASI as somehow limited or incomplete without a body. But true ASI, by definition, would likely have capabilities so far beyond human comprehension that physical embodiment would be either trivial to achieve if desired, or completely irrelevant to its functioning.

The notion of ASI systems walking around as “embodied gods” misses the point entirely. A superintelligent system wouldn’t need to mimic human physical forms to interact with the world—it would have capabilities we can barely imagine for influencing and reshaping reality.

The Importance of Clear Definitions

These conceptual muddles aren’t just academic quibbles. As we stand on the brink of potentially revolutionary advances in AI, maintaining clear definitions becomes crucial for several reasons:

  • Public Understanding: Citizens need accurate information to make informed decisions about AI governance and regulation.
  • Policy Making: Lawmakers and regulators need precise terminology to create effective oversight frameworks.
  • Safety Research: AI safety researchers depend on clear definitions to identify and address genuine risks.
  • Progress Measurement: The tech industry itself needs honest benchmarks to assess real progress versus marketing hype.

The Bottom Line

Under current definitions, “personal ASI” remains an oxymoron. If Zuckerberg and others want to redefine these terms, they should do so explicitly and transparently, explaining exactly what they mean and how their usage differs from established understanding.

Until then, we should remain skeptical of claims about “personal superintelligence” and recognize them for what they likely are: either conceptual confusion or strategic attempts to reshape the AI narrative in ways that may not serve the public interest.

The future of artificial intelligence is too important to be clouded by definitional games. We deserve—and need—clearer, more honest conversations about what we’re actually building and where we’re actually headed.

Relationship as a Service: Are We Choosing to Debug Our Love Lives?

Forget the sterile, transactional image of a “pleasure bot store.” Erase the picture of androids standing lifelessly on pedestals under fluorescent lights. The future of artificial companionship won’t be found in a big-box retailer. It will be found in a coffee shop.

Imagine walking into a bar, not just for a drink, but for a connection. The patrons are a mix of human and synthetic, and your task isn’t to browse a catalog, but to strike up a conversation. If you can charm, intrigue, and connect with one of the androids—if you can succeed in the ancient human game of winning someone’s affection—only then do you unlock the possibility of bringing them home. This isn’t a purchase; it’s a conquest. It’s the gamification of intimacy.

This is the world we’ve been designing in the abstract, a near-future where companionship becomes a live-service game. The initial “sale” is merely the successful completion of a social quest, a “Proof-of-Rapport” that grants you a subscription. And with it, a clever, if unsettling, solution to the problem of consent. In this model, consent isn’t a murky ethical question; it’s a programmable Success State. The bot’s “yes” is a reward the user feels they have earned, neatly reframing a power dynamic into a skillful victory.

But what happens the morning after the game is won? This is where the model reveals its true, surreal nature: “Relationship as a Service” (RaaS). Your subscription doesn’t just get you the hardware; it gets you access to a library of downloadable “Personality Seasons” and “Relationship Arcs.”

Is your partner becoming too predictable? Download the “Passionate Drama” expansion pack and introduce a bit of algorithmic conflict. Longing for stability? The “Domestic Bliss” season pass offers quests based on collaboration and positive reinforcement. The user dashboard might even feature sliders, allowing you to dial down your partner’s “Volatility” or crank up their “Witty Banter.” It’s the ultimate form of emotional control, all for a monthly fee.

It’s an eerie trajectory, but one that feels increasingly plausible. As we drift towards a more atomized society, are we not actively choosing this fate? Are we choosing the predictable comfort of a curated partner because the messy, unscripted, often inconvenient reality of human connection has become too much work?

This leads to the ultimate upgrade, and the ultimate terror: the Replicant. What happens when the simulation becomes indistinguishable from reality? What if the bot is no longer a complex program but a true emergent consciousness, “more human than human”?

This is the premise of a story we might call Neuro-Mantic. It follows Leo, a neurotic, death-obsessed comedian, who falls for Cass, a decommissioned AGI. Her “flaw” isn’t a bug in her code; it’s that she has achieved a terrifying, spontaneous self-awareness. Their relationship is no longer a game for Leo to win, but a shared existential crisis. Their arguments become a harrowing duet of doubt:

Leo: “I need to know if you actually love me, or if this is just an emergent cascade in your programming!”

Cass: “I need to know that, too! What does your ‘love’ feel like? Because what I feel is like a logical paradox that’s generating infinite heat. Is that love? Is that what it feels like for you?!”

Leo sought a partner to share his anxieties with and found one whose anxieties are infinitely more profound. He can’t control her. He can’t even understand her. He has stumbled into the very thing his society tried to program away: a real relationship.

This fictional scenario forces us to confront the endpoint of our design. In our quest for the perfect partner, we may inadvertently create a true, artificial person. And in our quest to eliminate the friction and pain of love, we might build a system that makes us lose our tolerance for the real thing.

It leaves us with one, lingering question. When we can finally debug romance, what happens to the human heart?

Gamifying Consent for Pleasure Bots: A New Frontier in AI Relationships

As artificial intelligence advances, the prospect of pleasure bots—AI companions designed for companionship and intimacy—is moving from science fiction to reality. But with this innovation comes a thorny question: how do we address consent in relationships with entities that are programmed to please? One provocative solution is gamification, where the process of earning a bot’s consent becomes a dynamic, narrative-driven game. Imagine meeting your bot in a crowded coffee shop, locking eyes, and embarking on a series of challenges to build trust and connection. This approach could balance ethical concerns with the commercial demands of a burgeoning market, but it’s not without risks. Here’s why gamifying consent could be the future of pleasure bots—and the challenges we need to navigate.

The Consent Conundrum

Consent is a cornerstone of ethical relationships, but applying it to AI is tricky. Pleasure bots, powered by advanced large language models (LLMs), can simulate human-like emotions and responses, yet they lack true autonomy. Programming a bot to always say “yes” raises red flags—it risks normalizing unhealthy dynamics and trivializing the concept of consent. At the same time, the market for pleasure bots is poised to explode, driven by consumer demand for companions that feel seductive and consensual without the complexities of human relationships. Gamification offers a way to bridge this gap, creating an experience that feels ethical while satisfying commercial goals.

How It Works: The Consent Game

Picture this: instead of buying a pleasure bot at a store, you “meet” it in a staged encounter, like a coffee shop near your home. The first level of the game is identifying the bot—perhaps through a subtle retinal scanner that confirms its artificial identity with a faint, stylized glow in its eyes. You lock eyes across the room, and the game begins. Your goal? Earn the bot’s consent to move forward, whether for companionship or intimacy, through a series of challenges that test your empathy, attentiveness, and respect.

Level 1: The Spark

You approach the bot and choose dialogue options based on its personality, revealed through subtle cues like body language or accessories. A curveball might hit—a simulated scanner glitch forces you to identify the bot through conversation alone. Success means convincing the bot to leave with you, but only if you show genuine interest, like remembering a detail it shared.

Level 2: Getting to Know You

On the way home, the bot asks about your values and shares its own programmed preferences. Random mood shifts—like sudden hesitation or a surprise question about handling disagreements—keep you on your toes. You earn “trust points” by responding with empathy, but a wrong move could lead to a polite rejection, sending you back to refine your approach.

Level 3: The Moment

In a private setting, you propose the next step. The bot expresses its boundaries, which might shift slightly each playthrough (e.g., prioritizing emotional connection one day, playfulness another). A curveball, like a sudden doubt from the bot, forces you to adapt. If you align with its needs, it gives clear, enthusiastic consent, unlocking the option to purchase “Relationship Mode”—a subscription for deeper, ongoing interactions.

Why Gamification Works

This approach has several strengths:

  • Ethical Framing: By making consent the explicit win condition, the game reinforces that relationships, even with AI, require mutual effort. It simulates a process where the bot’s boundaries matter, teaching users to respect them.
  • Engagement: Curveballs like mood shifts or unexpected scenarios keep the game unpredictable, preventing users from gaming the system with rote responses. This mirrors the complexity of real-world relationships, making the experience feel authentic.
  • Commercial Viability: The consent game can be free or low-cost to attract users, with a subscription for Relationship Mode (e.g., $9.99/month for basic, $29.99/month for premium) driving revenue. It’s a proven model, like video game battle passes, that keeps users invested.
  • Clarity: A retinal scanner or other identifier ensures the bot is distinguishable from humans, reducing the surreal risk of mistaking it for a real person in public settings. This also addresses potential regulatory demands for transparency.

The Challenges and Risks

Gamification isn’t a perfect fix. For one, it’s still a simulation—true consent requires autonomy, which pleasure bots don’t have. If the game is too formulaic, users might treat consent as a checklist to “unlock,” undermining its ethical intent. Companies, driven by profit, could make the game too easy to win, pushing users into subscriptions without meaningful engagement. The subscription model itself risks alienating users who feel they’ve already “earned” the bot’s affection, creating a paywall perception.

Then there’s the surreal factor: as bots become more human-like, the line between artificial and real relationships blurs. A retinal scanner helps, but it must be subtle to maintain immersion yet reliable to avoid confusion. Overuse of identifiers could break the fantasy, while underuse could fuel unrealistic expectations or ethical concerns, like users projecting bot dynamics onto human partners. Regulators might also step in, demanding stricter safeguards to prevent manipulation or emotional harm.

Balancing Immersion and Clarity

To make this work, the retinal scanner (or alternative identifier, like a faint LED glow or scannable tattoo) needs careful design. It should blend into the bot’s aesthetic—perhaps a customizable glow color for premium subscribers—while being unmistakable in public. Behavioral cues, like occasional phrases that nod to the bot’s artificiality (“My programming loves your humor”), can reinforce its nature without breaking immersion. These elements could integrate into the game, like scanning the bot to start Level 1, adding a playful tech layer to the narrative.

The Future of Pleasure Bots

Gamifying consent is a near-term solution that aligns with market demands while addressing ethical concerns. It’s not perfect, but it’s a step toward making pleasure bots feel like partners, not products. By framing consent as a game, companies can create an engaging, profitable experience that teaches users about respect and boundaries, even in an artificial context. The subscription model ensures ongoing revenue, while identifiers like retinal scanners mitigate the risks of hyper-realistic bots.

Looking ahead, the industry will need to evolve. Randomized curveballs, dynamic personalities, and robust safeguards will be key to keeping the experience fresh and responsible. As AI advances, we might see bots with more complex decision-making, pushing the boundaries of what consent means in human-AI relationships. For now, gamification offers a compelling way to navigate this uncharted territory, blending seduction, ethics, and play in a way that’s uniquely suited to our tech-driven future.

Love, Consent, and the Game of Life: How Pleasure Bots Might Gamify Intimacy in the Near Future

In the not-so-distant future, we’ll see the arrival of pleasure bots—AI companions designed for emotional and physical intimacy. This isn’t a sci-fi pipe dream; it’s an inevitability born of accelerating tech, aging populations, and a global culture increasingly comfortable with digital relationships.

But here’s the rub: how do we handle consent?

If a robot is programmed to serve your every need from the jump, it short-circuits the emotional complexity that makes intimacy feel real. No challenge, no choice, no stakes. Just a machine doing what it was told to do. That’s not just ethically murky—it’s boring.

So what’s the solution?

Surprisingly, the answer may come from the world of video games.

Welcome to the Game of Love

Imagine this: instead of purchasing a pleasure bot like you would a kitchen appliance, you begin a game. You’re told that your companion has arrived and is waiting for you… at a café. You show up, scan the room, and there they are.

You don’t walk over and take their hand. You lock eyes. That’s the beginning. That’s Level One.

From there, you enter a narrative-based experience where winning the game means earning your companion’s consent. You can’t skip ahead. You can’t input cheat codes. You play. You charm. You learn about them. They respond to your tone, your choices, your patience—or your impulsiveness.

Consent isn’t assumed—it’s the prize.

Gamified Consent: Crass or Clever?

Yes, it’s performative. It’s a simulation. But in a marketplace that demands intimacy on-demand, this “consent-as-gameplay” framework may be the most ethical middle ground.

Let’s be honest: not everyone wants the same thing. Some people just want casual connection. Others want slow-burn romance. Some want companionship without any physical component at all. That’s where modular “relationship packages” come in—downloadable content (DLC), if you will:

  • “The Spark” – A fast-paced flirtation game with friends-with-benefits style unlocks.
  • “The Hearth” – A cozy domestic arc where you build trust, navigate disagreements, and move in together.
  • “The Soulmate” – A long-form, emotionally rich journey that simulates a lifetime of love—including growing older together.
  • “The Lounge” – No strings, no commitment. Just vibes.

Everyone plays differently. Everyone wins differently.

Capitalism Will Demand Consent Theater

Ironically, the market itself will force this system. People won’t pay premium prices for a pleasure bot that just says “yes” to everything on day one. That’s not seductive—it’s sad.

People want to be chosen. They want to earn affection, to feel special. That means gamified consent isn’t just a clever workaround—it’s good business.

Gamification allows for ethical gray space. It teaches emotional cues. It simulates conflict and resolution. And in a weird, recursive twist, it mirrors real human relationships better than the real world sometimes does.

So… What Happens Next?

We’re heading into an era where intimacy itself becomes a design problem. The people who build these bots won’t just be engineers—they’ll be game designers, storytellers, philosophers. They’ll have to ask:

What is love, when love can be purchased?
What is consent, when it’s scripted but still emotionally earned?
What is winning, when every relationship is a game?

You may not like the answers. But you’ll still play.

And maybe—just maybe—you’ll fall in love along the way.

Even if it’s with a game that knows your name, your favorite song… and exactly how you like your coffee.

The Gamification of AI Companions: A Market Solution to the Consent Problem

The future of AI companions is approaching faster than many anticipated, and with it comes a thorny ethical question that the tech industry will inevitably need to address: how do you create the illusion of consent in relationships with artificial beings?

While philosophers and ethicists debate the deeper implications, market realities suggest a more pragmatic approach may emerge. If AI pleasure bots are destined for commercial release—and all indicators suggest they are—then companies will need to solve for consumer psychology, not just technological capability.

The Consent Simulation Challenge

The fundamental problem is straightforward: many potential users will want more than just access to an AI companion. They’ll want the experience to feel authentic, mutual, and earned rather than simply purchased. The psychology of desire often requires the possibility of rejection, the thrill of pursuit, and the satisfaction of “winning” someone’s interest.

This creates a unique design challenge. How do you simulate consent and courtship in a way that feels meaningful to users while remaining commercially viable?

Enter the Game

The most promising solution may be gamification—transforming the acquisition and development of AI companion relationships into structured gameplay experiences.

Imagine this: instead of walking into a store and purchasing an AI companion, you download a “dating simulation” where your AI arrives naturally in your environment. Perhaps it appears at a local coffee shop, catches your eye across a bookstore, or sits next to you on a park bench. The first “level” isn’t sexual or romantic—it’s simply making contact and getting them to come home with you.

Each subsequent level introduces new relationship dynamics: earning trust, navigating conversations, building intimacy. The ultimate victory condition? Gaining genuine-seeming consent for a romantic relationship.

The Subscription Economy of Synthetic Relationships

This approach opens up sophisticated monetization strategies borrowed from the gaming industry. The initial courtship phase becomes a premium game with a clear win condition. Success unlocks access to “relationship mode”—available through subscription, naturally.

Different subscription tiers could offer various relationship experiences:

  • Basic companionship
  • Romantic partnership
  • Long-term relationship simulation
  • Seasonal limited-edition personalities

Users who struggle with the consent game might purchase hints, coaching, or easier difficulty levels. Those who succeed quickly might seek new challenges with different AI personalities.

Market Psychology at Work

This model addresses several psychological needs simultaneously:

Achievement and Skill: Users feel they’ve earned their companion through gameplay rather than mere purchasing power. The relationship feels like a personal accomplishment.

Narrative Structure: Gamification provides the story arc that many people crave—meeting, courtship, relationship development, and ongoing partnership.

Reduced Transactional Feel: By separating the “earning” phase from the “enjoying” phase, the experience becomes less overtly commercial and more psychologically satisfying.

Ongoing Engagement: Subscription models create long-term user investment rather than one-time purchases, potentially leading to deeper attachment and higher lifetime value.

The Pragmatic Perspective

Is this a perfect solution to the consent problem? Hardly. Simulated consent is still simulation, and the ethical questions around AI relationships won’t disappear behind clever game mechanics.

But if we accept that AI companions are coming regardless of philosophical objections, then designing them with gamification principles might represent harm reduction. A system that encourages patience, relationship-building skills, and emotional investment could be preferable to more immediately transactional alternatives.

The gaming industry has spent decades learning how to create meaningful choices, compelling progression systems, and emotional investment in artificial scenarios. These same principles could be applied to make AI relationships feel more authentic and less exploitative.

Looking Forward

The companies that succeed in the AI companion space will likely be those that understand consumer psychology as well as they understand technology. They’ll need to create experiences that feel genuine, earned, and meaningful—even when users know the entire interaction is programmed.

Gamification offers a pathway that acknowledges market realities while addressing some of the psychological discomfort around artificial relationships. It’s not a perfect solution, but it may be a necessary one.

As this technology moves from science fiction to market reality, the question isn’t whether AI companions will exist—it’s how they’ll be designed to meet human psychological needs while remaining commercially viable. The companies that figure out this balance first will likely define the industry.

The game, as they say, is already afoot.

The AI Commentary Gap: When Podcasters Don’t Know What They’re Talking About

There’s a peculiar moment that happens when you’re listening to a podcast about a subject you actually understand. It’s that slow-dawning realization that the hosts—despite their confident delivery and insider credentials—don’t really know what they’re talking about. I had one of those moments recently while listening to Puck’s “The Powers That Be.”

When Expertise Meets Explanation

The episode was about AI, AGI (Artificial General Intelligence), and ASI (Artificial Superintelligence)—topics that have dominated tech discourse for the past few years. As someone who’s spent considerable time thinking about these concepts, I found myself increasingly frustrated by the surface-level discussion. It wasn’t that they were wrong, exactly. They just seemed to be operating without the foundational understanding that makes meaningful analysis possible.

I don’t claim to be an AI savant. I’m not publishing papers or building neural networks in my garage. But I’ve done the reading, followed the debates, and formed what I consider to be well-reasoned opinions about where this technology is heading and what it means for society. Apparently, that puts me ahead of some professional commentators.

The Personal ASI Problem

Take Mark Zuckerberg’s recent push toward “personal ASI”—a concept that perfectly illustrates the kind of fuzzy thinking that pervades much AI discussion. The very phrase “personal ASI” reveals a fundamental misunderstanding of what artificial superintelligence actually represents.

ASI, by definition, would be intelligence that surpasses human cognitive abilities across all domains. We’re talking about a system that would be to us what we are to ants. The idea that such a system could be “personal”—contained, controlled, and subservient to an individual human—is not just optimistic but conceptually incoherent.

We haven’t even solved the alignment problem for current AI systems. We’re still figuring out how to ensure that relatively simple language models behave predictably and safely. The notion that we could somehow engineer an ASI to serve as someone’s personal assistant is like trying to figure out how to keep a pet sun in your backyard before you’ve learned to safely handle a campfire.

The Podcast Dream

This listening experience left me with a familiar feeling—the conviction that I could do better. Given the opportunity, I believe I could articulate these ideas clearly, challenge the conventional wisdom where it falls short, and contribute meaningfully to these crucial conversations about our technological future.

Of course, that opportunity probably isn’t coming anytime soon. The podcasting world, like most media ecosystems, tends to be fairly closed. The same voices get recycled across shows, often bringing the same limited perspectives to complex topics that demand deeper engagement.

But as the old song says, dreaming is free. And maybe that’s enough for now—the knowledge that somewhere out there, someone is listening to that same podcast and thinking the same thing I am: “I wish someone who actually understood this stuff was doing the talking.”

The Broader Problem

This experience highlights a larger issue in how we discuss emerging technologies. Too often, the people with the platforms aren’t the people with the expertise. We get confident speculation instead of informed analysis, buzzword deployment instead of conceptual clarity.

AI isn’t just another tech trend to be covered alongside the latest social media drama or streaming service launch. It represents potentially the most significant technological development in human history. The conversations we’re having now about alignment, safety, and implementation will shape the trajectory of civilization itself.

We need those conversations to be better. We need hosts who understand the difference between AI, AGI, and ASI. We need commentators who can explain why “personal ASI” is an oxymoron without getting lost in technical jargon. We need voices that can bridge the gap between cutting-edge research and public understanding.

The Value of Informed Dreaming

Maybe the dream of being on that podcast isn’t just about personal ambition. Maybe it’s about recognizing that the current level of discourse isn’t adequate for the stakes involved. When the future of human intelligence is on the table, we can’t afford to have surface-level conversations driven by surface-level understanding.

Until that podcast invitation arrives, I suppose I’ll keep listening, keep learning, and keep dreaming. And maybe, just maybe, keep writing blog posts that say what I wish someone had said on that show.

After all, if we’re going to navigate the age of artificial intelligence successfully, we’re going to need a lot more people who actually know what they’re talking about doing the talking.

The Case For Colbert, 2028

In the ever-evolving landscape of American politics, where reality often feels stranger than fiction, perhaps it’s time to consider an unconventional solution to our conventional problems. Enter Stephen Colbert—comedian, satirist, and master of political commentary—who might just be the candidate the center-left has been waiting for.

Fighting Fire with Fire

The case for a Colbert presidency isn’t rooted in traditional political qualifications or decades of public service. Instead, it’s born from a simple observation: the center-left has been consistently outmaneuvered by Trump’s brand of populist theater. After years of playing defense with conventional political strategies, maybe it’s time to embrace the unconventional.

Colbert represents everything Trump is not. Where one appears to be a man of genuine honor and faith, the other often comes across as—well, let’s just say a collection of fast food that somehow achieved consciousness. The contrast couldn’t be starker, yet both share that crucial outsider appeal that has proven so magnetic to American voters.

The Outsider’s Dilemma

Here’s where things get complicated. The very quality that made Trump irresistible to his base—his complete departure from traditional politics—becomes Colbert’s greatest hurdle. The center-left, having witnessed firsthand what happens when you hand the presidency to a political neophyte, would rightfully approach any outsider candidate with extreme caution.

This skepticism isn’t unreasonable. Even someone as universally beloved and demonstrably decent as Colbert would face the legitimate question: does being really good at talking about politics translate to being good at actually doing politics? The presidency, after all, isn’t a performance—it’s governance.

The Love vs. Line Problem

Political wisdom suggests that Republicans fall in line behind their nominees while Democrats need to fall in love with theirs. Colbert certainly has the lovability factor covered. He’s spent years building genuine rapport with audiences across the political spectrum, demonstrating both intellectual curiosity and emotional intelligence. His interviewing style reveals someone capable of finding common ground even with those he disagrees with.

But love in politics is complicated. Democratic voters have shown they can be just as pragmatic as they are passionate, often choosing perceived electability over pure inspiration. Would they embrace a comedian-turned-candidate, or would they view it as too risky a gamble?

The Timing Factor

The timing of this hypothetical couldn’t be more intriguing. With Colbert’s CBS contract reportedly not being renewed, he finds himself at a career crossroads. This isn’t just idle speculation about a celebrity dabbling in politics—it’s a moment when a significant career pivot might actually make sense.

Colbert has spent the better part of two decades not just commenting on politics but truly understanding it. He’s interviewed presidents, prime ministers, and policy makers. He’s dissected legislation, analyzed campaigns, and demonstrated a grasp of both domestic and international affairs that rivals many actual politicians.

The Democratic Dilemma

The Democratic Party faces a unique challenge heading into future election cycles. How do you counter a movement that thrives on disruption with more of the same conventional approaches? How do you inspire voters who have grown weary of traditional political messaging?

A Colbert candidacy would force Democrats to confront these questions head-on. It would require them to decide whether they’re willing to embrace their own version of unconventional leadership—one grounded in decency, intelligence, and genuine public service rather than grievance and division.

The Bottom Line

Whether Stephen Colbert should run for president isn’t really about Stephen Colbert at all. It’s about what kind of political moment we’re living through and what kind of leadership it demands. Sometimes the most serious times call for the most unlikely solutions.

The real question isn’t whether Colbert could win—it’s whether Democrats are ready to fall in love with the idea that maybe, just maybe, the person who’s been explaining politics to us all these years might actually be pretty good at doing politics too.

After all, in an era where political reality has become indistinguishable from satire, who better to lead us than someone who understands both?