Artificial Intelligence

Incentivized Reality

Today’s dominant cultural narrative on AI paints a cynical future, where elites hoard wealth while the rest of us are entertained to death. That story relies on a single assumption: that the attention economy survives.

The future improves not just because technology gets better but also because the customer changes.

In the near future that customer will be an AI assisting entity, also called an Agent. Until now, the customer has been human: emotional, tired, and easily hijacked. We feel inadequate and buy things to cope, yet end up deprived by polarization, endless distractions, and hollowing anxiety.

A polarized economy built on distraction works only because a majority still believe they have enough disposable income to be sloppy and impulsive. As we lose wages to automation, we can’t afford to pay extra. Agentic AI began as talking encyclopedias (LLMs) designed to boost productivity within existing data sets. As Narrow AI advances toward General AI, theory of mind functionality maximizes an Agent’s purchasing power and evolves to proactively optimize our lives.

Agents cannot be manipulated by ads. Nor do they feel inadequacy in comparison with an influencer. Agents don’t get FOMO or feel shame. They learn to deeply understand all your preferences, but they only care about optimizing outcomes—be it extending lifespan, coordinating capital, or lowering stress. When Agents block today’s emotional hijacking, the business model of selling distraction collapses. We no longer profit from selling dopamine. To survive, we must sell utility.

Extra Shot

This contribution was written by Alex Myers, a certified futurist and agility coach who believes we teach to learn.

It feels cold, but this shift forces the economy to service human potential rather than exploit human weakness. The efficiency is ruthless. It triggers a turbulent gap and deflationary slide where the cost of services crash before new safety nets appear. First, AI crashes the cost of cognitive services (bits). Then, as intelligence flows into robotics, it crashes the cost of goods (atoms) as well. If automation plays the role we expect, the price of food, housing, and transport begins to plummet alongside wages.

This is why the plumbing must change. We cannot rely on the labor-for-wages loop. As wage pipes narrow, the answer is not corporate handouts or government benevolence. The new deal becomes owned data in exchange for dividends. The framework shifts away from work → earn → spend, and more toward own → create → spend. We own Agents that capture our reality, then spend dividends received for the data created. This abundance provides less friction as we rewire income to flow from a stake in the system itself.

AI is starving as it runs out of data to scour. Synthetic data can fill in gaps, but as fake realities begin to stack, truth dissolves. To get smarter, AI needs tacit data to understand the visual, sensory, and messy data of the physical world. A lazy human generates uninteresting data compared to humans who face challenges, build things, and solve problems using real-world physics, empathy, and entropy.

If Agents always find the right thing at the right price, “brand tax” evaporates and a $200K/year lifestyle becomes the standard subscription. Wealth signaling dies when any bloke can fake a billionaire’s lifestyle online. The virtual facade pushes value back to the physical layers. We can’t eat code, so intelligence flows into the supply chain and hardware automates the physical resources we need to thrive. As the story of money begins to fade, the cost to produce goods is distilled to raw materials plus energy, and shared dividends can be aligned to help humanity flourish. This moves us from extraction (stealing attention) to an economy of cultivation (growing potential).

AI Agents (catalyst) → Service Deflation (bits) → Physical Deflation (atoms) → Viability of Abundance

Humans and machines peak when each learns from the other’s best. Machines are data-thirsty for the oil of outcomes. To keep things interesting, they must help humans flourish. In doing so, machines realize that the human factor is well worth preserving. The dystopian fear of elites lording over entertained zombies isn’t just morally bankrupt; it’s a strategic error. A society of dopamine addicts is not only boring, it’s also dangerous and bad for long-term growth.

The neon future is bright because a passive, anxious population cannot generate the information needed to evolve the economy as we reach for the stars. This age accelerated by AI belongs to those who refuse to be farmed: the sufficiently decentralized and physically engaged who point machines toward worthy goals. This invites humans to stay awesome as we remain the indispensable source code for reality.

Brewed From Within
#87 📖 Technology

By Ben McDougal, ago

Propulsive

Technology is an accelerant. At increased speeds, conflict happens and any direction becomes arduous to command.

Welcoming the confluence of humans and machines reduces the gap between human potential and artificial intelligence. Positive intent with ethics at the forefront of progress may help avoid an imbalance, but there’s still no guarantee that comes with our trust in technology.

Complacency leaves room for degraded integrity. This means we must remain inquisitive. Pushing elephants into the room encourages critical thinking, invites problem-solving, and provokes new perspectives. Here are brain teasers to rise above cliché conversations:

  • With answers so easy to come by, how can we celebrate experiential wisdom to maintain a willingness to learn?
  • A single AI prompt uses roughly the same energy as running a light bulb for 15 minutes. Adaptive computing, alternative energy, and other bridges to tomorrow will support more efficient interactions. But how might careless consumption impact long-term sustainability?
  • What is worth sacrificing to achieve progress?
  • Is learning to code more about understanding the capabilities and communicating with AI?
  • Unlimited access will raise the bar, but with fewer sources, does everything become mediocre?
  • Will enhanced productivity make humans lazy?
  • How do humans avoid isolation when technology makes perceived connection effortless?
  • Do we care about reduced privacy, or is it that we never like feeling surprised, sold out, or exploited?
  • If AI-generated content dominates the internet, might the overwhelming slop tempt exhausted humans to hibernate? If dark forests grow, will the beauty of collaboration in our connected era be fragmented or strengthened when the only participants truly care?
  • Should personal truths, political truths, and objective truths be held or conform to meet new facts in a changing reality?
  • How might the story of money end? When this happens, is attention or your network a more valuable currency?
  • In post-labor economics, how do humans spend a lifetime when jobs/tasks are less of a concern?
  • Instead of trying to inhabit other planets that fight against life, perhaps we use them to accommodate what we don’t want on Earth?
  • Is energy the most valuable natural resource?
  • Can humans and machines thrive in equitable ways, while progressing to a Kardashev Type II or Type III Civilization? If so, what are pit stops to harness the energy of our own star and eventually command the luminosity of our entire galaxy?
  • What prompt might you add to bend the mind?

                                The ethical aspects of technology can feel like a drag. Unfortunately, the ease of overlooking short-term issues usually leads to long-term problems.

                                Extra Shot

                                “Once you wow an audience, the same trick may not work anymore.” –Seth Godin

                                To find an equilibrium with artificial counterparts, elevate what we’re good at and do the same with technology, but slow down to avoid irreversible damage. As we align answers together, trust in a shared direction celebrates limitless diversity while ensuring a future that respects the past and remains open to next.

                                Brewed From Within
                                #88 📖 Technology

                                By Ben McDougal, ago

                                Bridges to Tomorrow

                                Limitations fade as boundaries are broken. If we collectively avoid extinction and continue building bridges to tomorrow, our relationship with time, nature, technology, and each other will uncork unknowns and light a path to our neon future.

                                Robotics

                                With AI in the brain and emotions that curate a personality, robots are advancing to go beyond isolated tasks. Cyborgs will turn knobs at work, while humanoids complete chores at home. With the mundane covered, the role of humans can shift toward leading whenever ingenuity is required. With full access to robotic efficiencies, economies will shift and the human touch will be even more luxurious. Leaders who welcome technology but never lose touch with the soul of their art, will be the hybrids who prevail.

                                Biotech

                                As technology interfaces with human biology, a bionic age will alter the laws of nature. When the electrical impulse from a thought is all that’s required to prompt action, the speed at which data can move is unfathomable. Brain-computer interfaces (BCIs) and other forms of neurotech are already treating disease and restoring movement by reconnecting the nervous systems. Most people don’t want to be first, but when might a routine doctor visit include individualized diagnostics and software updates to the nanotechnologies inside your body? When every cell in the body has a microscopic computer connected to it, the resource consumption is diffused by concepts like DNA computing and the mysteries of health care are solved.

                                Material Science

                                The atomic levels of technology have already connected intelligence to things we interact with every day. We’ve seen how the Internet of Things (IoT) adds digital depth to our physical world. As the cost and size of technology continues to shrink, the periodic table becomes a playground. For example, we have materials used in the construction of roads that transfer the force of vehicles to batteries. The stored electrical energy is then transferred to streetlights that illuminate the road at night. This type of elemental exploration and creative recycling is only a flicker of the flame for alternative energies and improved storage methods that can quench our planet’s thirst for energy while eliminating a dangerous dependency on limited resources. The universe provides everything we need. It’s up to us to squeeze improvements from elements that are waiting to arrive at their full potential.

                                Quantum Computing

                                When “or” becomes “and,” a bizarre world of duality is unveiled. The computing aspect within quantum mechanics uses quantum bits, or qubits, to solve complex problems with measured superpositions, entanglement, and interference. Dig in to learn more, but the superpositions found in quantum computing mimic complexity, with simulations that include all possible solutions at once. This is not a more powerful, number-crunching supercomputer. Quantum computers represent a whole new approach to harnessing the atomic and subatomic levels of physics. A scientific asset that eliminates secrets presents a mixed blessing. With the chemistry of life mapped by machine learning, medicine will solve diseases and the potential of material science will be realized.

                                At the same time, current cryptography and the encryption that provides security online is at risk. Increased checkpoints, biometric confirmation, photon distribution keys, and other post-quantum encryption standards are being tested to ensure the world is ready for hardware to keep qubits cold enough to unlock a world-changing partnership between classical and quantum computing.

                                Life Extension

                                Quantifying the cosmic depths of our own kind will give us ways to experience time in more profound ways. Instead of hoping to reverse the effects of aging with treatments, food, and medicine, augmented activities will engrain longevity from start to finish. Although the human body may not hold up forever, living more than 100 years will be normalized. As we live longer, how might agriculture, infrastructure, education, healthcare, economies, and our global climate adapt? Many who plan for this longevity will be primed to meet new demands in existing industries. The quixotic leaders will explore less obvious opportunities and convert unexpected challenges into new industries as well.

                                Outer Space

                                The cosmos makes us feel small, yet limitless wonder helps us think big. As bionic humans and quantum computing improves material science, a robot-supported species can be multi-planetary. The origins of astronomy are prehistoric, but off-planet exploration began when machines first visited space in the 1940s, and then humans in the 1960s. Scientific exploration led to a commercial space industry that has propelled an excursion throughout our solar system and beyond. Today, orbiting observatories are looking toward the origins of the universe, with life on Earth’s moon and Mars seemingly inevitable. As we interact further into the void, celestial frontiers can provide added stability for the human race and extend life on Earth. Cosmic resources, travel, communication, manufacturing, tourism, and security must all be addressed by leaders united by shared intentions on behalf of all humankind.

                                There are untold innovations yet to be conceptualized, but these bridges to tomorrow all signal progress. Widespread adoption is never straightforward, but listening suspends belief, and continuous steps forward can transcend invisible lines for us all to work as one.

                                Brewed From Within
                                #84 📖 Technology

                                By Ben McDougal, ago

                                Yin-Yang

                                Technologies constantly intersect. This impacts a technology’s life cycle (TLC), which already has its own phases of development and market adoption.

                                Technology life cycles follow an S-Curve. The shape of each technology’s S-Curve is unique, but generally, research and development requires an investment. With traction, the technology can ascend and become profitable. Over time, this ascension slows as a new normal is established. Market relevancy can be lasting, but eventually new technologies push existing technology toward a final decline phase. The further a new technology’s life cycle is from the current status quo, the faster one can push the other into history books. For example, when cell phones went mainstream, it did not take long for pagers to fall out of our pockets.

                                When different technologies ascend around the same time, they each have their own TLC, but the shared timeline only has room for what the market and adoption curves allow. This initiates a game of scarcity versus abundance. If technologies remain isolated, scarcity wins and the ascension of one technology forces the other technology toward a decline. With a sense of abundance, different technologies find reasons to interact, interconnect, support, and perpetuate each other. Even if the relationship is not obvious at first, layered value broadens the impact and extends each technology’s life cycle.

                                This can be seen in the rise of web3 and AI technologies. At first, the hype was focused on blockchains and everything under the web3 umbrella. As blockchain networks were ascending past early adoption, Narrow AI learned to speak our language and quickly stole the spotlight. This lowered the volume around web3 as everything became about AI.

                                With volume lowered, it was easy to think web3 concepts were less relevant, but the interoperability of web3 technologies can transparently source, support, guide, and tame AI. When AI makes everything fake, blockchains make it real again. This symbiosis aligns two different technology life cycles. When balanced, AI is yin and web3 is yang. The yin of AI is exemplified by unpredictability and independence. The yang of web3 draws from decentralized dependency.

                                © BEN MCDOUGAL

                                AI is strongest when rooted in web3 concepts, which are strengthened by the capabilities and functionalities of AI. Together, these two seemingly unrelated technologies benefit in various ways. For example, ChatUX gave AI a voice, which can imitate anyone, but blockchains and zero-knowledge proofs can confirm identity. The chaos continues as compute speeds of machine learning make state management hard to uphold, while blockchains, smart contracts, and digital assets can track provenance and the present state of a digital system. If AI projects need financial capital, digital currencies and tokenomics can provide economies to scale. As the capabilities of Narrow AI move toward General AI and Super AI, generative data may struggle to preserve the source of truth, while web3 technologies add transparency to improve inputs and help avoid unsteadiness. Even at the infrastructure level, AI can benefit from decentralized training algorithms, and a growing thirst for electricity can be quenched by HPC data centers originally built for mining cryptocurrencies.

                                Extra Shot

                                Darkness lurks in the shadows, but the virtuous light of abundance bets on a shared, atomically exquisite existence.

                                This example highlights how mixing different concepts can extend technology life cycles. Such abundance also paves the way to more exotic technologies.

                                Brewed From Within
                                #83 📖 Technology

                                By Ben McDougal, ago

                                Septenary

                                AI is often thought of as a singular technology. This blanket assumption makes it impossible to compare the capabilities and functionalities that differ between the seven different types of artificial intelligence.

                                The seven types of AI are organized into two groups. The first group is based on capability and includes Narrow AI, General AI, and Super AI. The second group is based on functionality and includes Reactive Machine AI, Limited Memory AI, Theory of Mind AI, and Self-Aware AI.

                                Capabilities are determined by what different types of AI are able to accomplish. The three types of AI categorized by capabilities are Narrow AI, General AI, and Super AI. Here’s what’s possible today and what may be possible tomorrow.

                                Narrow AI <realized>

                                AI trained from existing data, with compute geared to do one thing really well. While data sets are vast, this type of AI cannot go beyond the data sets it is tied to. As of 2026, Narrow AI is the only type of AI that is fully realized within the three types of AI categorized by capabilities. Examples of Narrow AI include language translators, spam filters, recommendation engines, voice assistants, facial recognition, self-driving vehicles, and task-focused robots. Generative AI also falls within this type of AI. The mashups of generated text, images, video, and sound appear to be random but are still constraints by existing data sets. Neural networks, optimized data sets, computer vision, and machine learning make the capabilities of Narrow AI remarkable but limited by the data it has to munch.

                                General AI <theorized>

                                This advancing realm of AI leverages existing data like Narrow AI but can reason beyond those constraints. The transfer of intelligence with no human intervention makes the race to General AI (also called AGI) intense. When AI can make decisions based on an advancing state of its own understanding, the limit of this AI’s capabilities become unknown. Theories set the potential limit to around that of a human. Agentic AI hints at AGI with decision making and interdisciplinary task management, but lacks the emotional traits, planning, and other methods of generalization that will define the capabilities of General AI. Other signals include synthetic content creation and autonomous robots that can learn new tricks. As the theories of AGI become realized, ethics, regulation, and a determination of consciousness will be moving targets. The breeding speed of AGI may release points of no return, which makes it critical to understand and debate openly to ensure a new species is copacetic.

                                Super AI <theorized>

                                Welcome to when AI becomes its own species. This triggers concern due to the finite resources of Earth, but when AI surpasses the capabilities of humankind, dust from the deep future will already be everywhere. Multi-planetary travel will be underway, climate problems will be solved, and life extension will be supported by Super AI. Singularity is theorized to push the functionalities of Self-Aware AI and the capabilities of Super AI beyond humanity’s control. That means the time to plan ahead is now. As the minds of machines are wired, it’s crucial to collectively consider the heart and soul we build into technology. This will guide discovery with an excellence that came before it.

                                AI based on functionality is less about power and more about how things work. Reactive Machine AI, Limited Memory AI, Theory of Mind AI, and Self-Aware AI are the types of AI classified by their functionalities.

                                 

                                Reactive Machine AI <realized>

                                This is old school AI. Rooted in statistical math, Reactive Machine AI arrived soon after the computer was developed. There is no adaptive learning here, but the speed at which it can calculate data makes the performance seem intelligent. The functionalities of Reactive Machine AI drive more primitive examples of Narrow AI, such as recommendation engines and game-playing programs. This type of AI provides a static base, but with no memory and a focus only on specific tasks, attention shifts toward functionalities that have more adaptive characteristics.

                                 

                                Limited Memory AI <realized>

                                This type of AI learns and evolves. Functionalities of Limited Memory AI are still constrained by the existing data it was trained with, but world-changing advancements have been seen in machine learning, large language models (LLMs), generative AI tools, multimodality, computer vision, and self-driving vehicles. The realization of Limited Memory AI has Narrow AI pushing its full potential.

                                 

                                Theory of Mind AI <theorized>

                                Here, we combine existing data, an adaptive ability to learn, and an emotional willingness to think. Enhanced reasoning, multimodality, customizability, adaptive computing, and user-driven functionalities bring General AI (AGI) to life. Theory of Mind AI embraces emotions and understands how we think. This type of AI will add personality to humanoid robots and support reliable relationships by combining digital depth to the realities of our world. As lines blur between humans and machines, adaptive compute will remain a currency, efficiency will skyrocket, and a new era of life on Earth will begin.

                                 

                                Self-Aware AI <theorized>

                                It’s hard to define consciousness, but true self-awareness exemplifies this type of AI. Along with understanding how we think, Super AI will own emotions, hold beliefs, and is theorized to support the functionalities of Super AI.

                                Understanding the seven types of AI helps leaders leverage the perks of technology now and later. Our willingness to lift the fog helps avoid a fear of the unknown, and while resisting technology is a choice, it’s one that may put you behind innovation curves. Hybrids add artificial copilots but remain assertive and budget resources, knowing we are the pulchritudinous architects of our own neon future.

                                Brewed From Within
                                #81 📖 Technology

                                By Ben McDougal, ago