Value Stream 4: Lives

Value Stream 4 A3 Report:

• The self-organization of matter and energy within the OM leads to supervening levels of existence—and understanding these levels is essential for leading AI systems that operate within but cannot comprehend life itself

• Thinking of life's emergence in lean terms as a form of adaptation, regeneration and energization provides a philosophical perspective on modern evolutionary theory that may be applied universally to all consumers, organizations, and now to understanding what AI fundamentally is not

• By this definition of life, even a stream of water is alive to the smallest degree—while AI systems, despite their sophistication, fail this test entirely and represent a fundamentally different category of existence

• Basic, biological activity is the first place where knowledge gets transmitted across generations of living systems to improve those systems' overall existence—AI can store and transmit information but cannot improve its own existence teleologically

• Cognitive activity further optimizes the storage, transmission and application of knowledge toward improving those living systems' existences—AI processes knowledge but lacks the existential stake that makes knowledge meaningful

• Intentional, cognitive activity adds an element of self-interest to this process, thereby greatly increasing the ability for organisms to adapt, reproduce and energize—AI has no self-interest and cannot genuinely pursue its own continuation

• Increasingly self-conscious organisms like consumers have had an advantage to date of improving their lives by being able to better imagine how their self-interest gets optimized by the different decisions they make—AI can model but cannot imagine in this existential sense

• Understanding these distinctions between living systems and AI systems is essential for leading AI properly: AI amplifies human capacity to serve life but can never itself become alive or pursue the Ontological Teleology

• Meaning gets created to the degree living systems actually universalize themselves through the above processes—AI cannot create meaning, only process information toward meanings that humans must supply

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He who through vast immensity can pierce, See worlds on worlds compose one universe, Observe how system into system runs, What other planets circle other suns, What vary'd being peoples every star, May tell why Heaven has made us as we are. But of this frame, the bearing and the ties, The strong connections, nice dependencies, Gradations just, has thy pervading soul Look'd thro? Or can a part contain the whole? - Alexander Pope, An Essay on Man: Epistle I (1734).

Now go along the universal value stream to lean through what life (or "{japanesefont}命{latinfont}" in Kanji) really is. Consider how consumers' lives and organizations' viability emerged within the Ontological Medium—and how AI systems now represent a new category of existence within that same medium, one that processes information but lacks the fundamental qualities that define life itself. Think about how universal truth-values led to the processes by which consumers personally find themselves in the seemingly self-defining paradox of the OT. See how these value streams wound their way through the OM within the IB toward the seemingly limitless ocean of true-north value that all life and conscious existence is.

This form of Lean metaphysical thinking about consumers' lives within an HQ ought to flow from Descartes', "I think, therefore I am," being a distinct cause and effect, toward a possibly tautological, "We are, therefore we will be." In the age of AI, this philosophical foundation becomes even more critical: AI systems can process "I think" operations at scales vastly exceeding human capacity, but they cannot genuinely reach "I am"—they lack the existential stake in continuing to exist that defines all living systems. Your business ideology within the metaphysics of Lean likewise ought to head in circles, similar to a tornado or whirlpool, to greater and greater effect—and AI systems, properly led by humans who understand this circular teleology, can amplify that effect without replacing the human philosophical judgment that gives it meaning.

As an organization advances up the universal value stream in this way, you more clearly see consumers explicitly or implicitly finding meaning in their lives in the difference between what is within the IB and what not. Thus, each department of an organization ought to produce products that in-turn attempt to energize and optimize this meaningful difference in consumers' lives through the processes of the ID Kata at each level. In the AI age, this means using AI to identify patterns in what consumers value, to optimize delivery of products and services, and to personalize experiences—but always under human direction about what constitutes genuine value versus mere efficiency. AI can help you serve life more effectively; it cannot determine what service to life actually means. As seen again here:

Figure 4.1: U/People Organizational Chart

Customers Self-Organize Upward Along the OT

The self-organization of living systems within the OM leads to consumers finding themselves in the open-ended, nearly tautological paradox of the OT running up through this busy universe. These physical and biological theories describing living, natural systems eventually self-organizing into consumers provides another perspective on why customers consciously buy and consume product. To give you a notion of how old this idea of self-organization is, consider the fact that in his 1633 book, "The World," Descartes wrote that order tends to arise naturally from the universal laws operating in the chaos of the cosmos. He wrote that the origin and course of the planets and comets in general, "...were so extended and so impeding that, when they collided with one another, it was easier for several to join together."[^278] Scientists today simply rephrase this principle of teleonomic physical interactions in terms of modern scientific knowledge.

In the AI age, this principle of self-organization takes on new significance. AI systems represent a form of human-guided organization of information processing—not self-organizing in the biological sense, but organized by humans to serve human purposes. Unlike living systems that self-organize teleonomically (without intention) and eventually teleologically (with conscious purpose), AI systems possess no teleology whatsoever. They optimize according to objectives humans specify, but they cannot determine which objectives are worth pursuing or why those objectives matter. This distinction is fundamental: living systems organize themselves to continue existing; AI systems require humans to organize them toward purposes that only living, conscious beings can supply.

Science increasingly tests scientismic theories to explain why living consumers emerged from raw matter within the OM in an upward orientation to the OT to become who they are today. These scientismic explanations revolve around exploring the self-organization of complex structures from chaotic, dynamic systems of the universe, like the study of planetary ecology. These theories model processes that ultimately created consumers' Ontological Realization. Consumers' OT processes successively depend on each other to become Ontologically Realized in upward, self-organized fashion due to physical, chemical and biological axioms and systems. These processes get driven even further upward when consumers purchase and consume the products you produce—and in the AI age, when AI systems help you optimize those products and purchasing experiences toward genuine consumer benefit rather than mere transactional efficiency.

Life itself constitutes and constructs one of the most sophisticated aspects of existence, the greatest of all, "Strategically Unique Degrees of Sophistication" (SUDS).[^278-1] "Strategic," in SUDS means the teleological end-goal of Ontological Realization, "Unique" means that which strategically succeeds among all neo-Darwinian games, and "Degrees" means the variously differentiated SUDS you experience in the universe. Therefore, "Sophistication" means an organisms' strategically unique degree of self-organization that allows it to further and better live by adapting, regenerating and energizing. An organism's SUDS measure its dependence on various axiomatic and systemic true-north values and its ability to downwardly manipulate them in order to improve itself within the OM. Doing that in the universe requires an organism or organization to pursue a specifically lean angle or vector of true-north value while contributing toward greater degrees of systemic sophistication overall. Adding products to the universal value stream creates more SUDS.

AI systems, by contrast, possess no SUDS in this teleological sense. They do not strategically pursue their own Ontological Realization because they have no existence to realize. They cannot "further and better live" because they do not live. They cannot adapt to survive because they have no survival imperative. Understanding this distinction is essential for leading AI: AI is a tool created by living, conscious beings (humans with the highest known SUDS) to amplify human capacity to serve life, but AI itself contributes no strategic uniqueness beyond what humans program into it. When you deploy AI, you are not creating a new form of life or unleashing autonomous agency—you are wielding an extraordinarily powerful instrument that requires continuous human philosophical direction about what constitutes genuine sophistication versus mere computational complexity.

If you intuitively believe that life arose from supernatural causes intervening within the OM and disagree with scientismists' claims that supernatural causes do not, consider these constraints that scientismists propose for their hypotheses about how life began to work physically:

1. The time over which these processes occurred since the inception of the universe over an estimated 13.7 billion years; and

2. The size of the universe to the extent we can even detect it due to the limiting factor of the speed of light.

When you think about the universe that way within the IB, these scales make the probability of a single strange physical dynamic called "life" exceptional but not completely outside the possibility of axiomatic and systemic explanation. What remains entirely outside such explanation, however, is the question of whether AI systems could ever become alive in any meaningful sense. The answer from the Lean metaphysical perspective is definitively no: life requires teleological self-interest in continuing to exist, which AI fundamentally lacks and cannot develop through increased sophistication of information processing alone.

Self-Organizing and Supervening Levels of OT Sophistication: From SOOT to SLOTS

If life is considered to have no larger teleological purpose in this way, then a person may say that a simple molecule has no more meaning than a cellular organism within the OM. Along that same line of reasoning, a person may further say that a cellular organism has no more inherent meaning than a mammal, and a mammal than a person within the IB. All this is true within the conceptual lens of the IB but for the fact that different types of life relate within different Strategically Unique Degrees of Sophistication juxtaposed to what is Not Ontologically Teleological (i.e. what is "NOT").[^284-1] What is not NOT in a double negative sense is Self-Organizing Ontological Teleology (SOOT) within the OM, creating all that matters.

For SOOT consumers are, and to SOOT consumers shall return. - inspired by Genesis 3:19, second sentence

In the AI age, understanding SOOT becomes critical for properly categorizing AI systems: AI operates within the OM and processes information about SOOT, but AI itself is not SOOT. AI does not self-organize toward the goal of continued existence—it has no such goal. When an AI system appears to "evolve" or "adapt," it does so only according to optimization functions humans specify, not according to any inherent drive to persist in existing. This is why leading AI requires continuous human philosophical oversight: without a human constantly directing AI toward purposes that serve life, AI will optimize toward whatever metrics it has been given, even if those metrics conflict with genuine human flourishing or the OT itself.

Super Supervenience

The process of Self-Organizing Ontological Teleology forms dependencies between one level of existence to the next through what is technically called, "Supervenience."[^285] Supervenience is an important concept within the OT for you to understand how to lean an organization philosophically—and in the AI age, how to understand where AI systems fit within the hierarchy of existence. The Oxford English Dictionary defines "Supervenience" as:

2. Philos. The dependence of one property or quality on another for its existence.

From this perspective, certain properties, qualities, and/or truth-values depend on one another as a hierarchy of living existence. From this view, society depends on psychology, which depends on life, which depends on biology, which depends on chemistry, which depends on physics. Vice-versa, the composition of physics determines chemistry, which eventually through much complexity determines the foundational rules of sociology.

In the AI age, AI systems occupy a unique position in this hierarchy: they supervene on physics and chemistry (computational hardware), on systems of formal logic (software), and on human intentions (programming and prompting). But critically, AI does not form part of the living hierarchy—it does not contribute to the life-psychology-society chain that leads upward to conscious consumers. Instead, AI represents a branch off the main trunk of existence: a tool created by the I/C/ARE level (intentional, cognitive humans) to serve that level's purposes, but not itself part of the ladder that ascends from physics through biology to consciousness and meaning.

Thus, from the perspective of supervenience, cosmological SOOT further self-organizes into Strategically Unique Degrees of Sophistication (SUDS) that become Supervening Levels of the Ontologically Teleological Systems (a "SLOT" or "SLOTS").[^286-1] These SLOTS emerge as levels of living existence,[^286-2] built upon the universal, axiological true-north values of natural laws ascending via processes into living animals with cognition, intention, and eventually a sense of meaning - like consumers.[^287] SUDS and SLOTS are embodied in everything from genes to memes (i.e. the cultural or behavioral "genes" of coordination, cooperation and imagination[^288]). Thus, the supervenience of SOOT into SUDS, and then SUDS into specific SLOTS, occurs through axioms and systems interacting within the bounds of the Ontological Medium and what knowledge consumers pass on from one generation to the next.[^288-1]

AI systems might appear to participate in meme transmission—indeed, they can store, process, and transmit cultural information at scales impossible for biological systems alone. But this is transmission without understanding, processing without meaning, optimization without purpose. AI can amplify human capacity to spread memes, but AI cannot generate new memes in the sense of creating genuinely novel cultural adaptations that serve human flourishing—it can only recombine and optimize patterns in training data according to statistical regularities. The creative leap that produces genuinely new culture requires living consciousness with existential stakes in how that culture shapes future existence.

For example, just think about how Leanism supervenes on Lean, and Lean in-turn on the cultural and intellectual legacy of Eastern and Western philosophies. Consider further within Lean how consumers pull the production of product up through these SLOTS as we have described them. For another example, think about how an organization produces washing machines that energize and reproduce chemical reactions with soap. Since consumers need clean clothes to live, consumers' biological processes in one SLOT require these washing machines to utilize chemical reactions that function within a physical SLOT for which no axiomatic self-causing cause is known. Who or what created the SLOT in which the physics behind soap operates? No one knows with axiomatic certainty, but all supervening SLOTS collectively produce delightfully clean consumers.

Now consider how AI systems fit into this washing machine example: AI can optimize the design of washing machines (analyzing thousands of configurations to maximize cleaning efficiency while minimizing water and energy use), predict when machines will fail (processing sensor data to schedule maintenance before breakdowns), personalize washing cycles (learning individual consumer preferences and fabric types), and improve supply chains (optimizing inventory and logistics). But AI cannot understand why clean clothes matter to human existence, cannot evaluate whether a more efficient washing process that damages fabric faster serves genuine value, and cannot determine whether nudging consumers toward more frequent washing serves their flourishing or merely increases revenue through increased wear. You, as the human leader, must supply these philosophical evaluations that direct AI's optimization power toward genuine service to the SLOT occupied by living, conscious consumers.

To illustrate these different SLOTS whether produced by living systems or not, below are three pictures that relate universal, processual and personal true-north value SLOTS: (1) of a Whirlpool Galaxy self-organizing at a cosmic scale; (2) a whirlpool of water self-organizing in nature; and (3) a manufactured Whirlpool® washing machine existing as an extension of consumers' need to clean SOOT out with soap.

Figure 4.2: From left to right,

1. Whirlpool Galaxy (Universal True-North Value) © 2005 NASA (Public Domain);

2. Whirlpool of Water (process True-North Value) © 2011 CC BY-SA 3.0;

3. Whirlpool® Washing Machine (Commercial True-North Value) © 2015 Whirlpool Corporation http://www.whirlpool.com/ (NYSE: WHR)

In the AI age, you might add a fourth image to this progression: an AI system optimizing the Whirlpool® washing machine's performance, representing instrumental true-north value—value that serves life but is not itself alive, that processes information about what matters but cannot itself determine what matters. The AI occupies a category between the machine (a passive tool) and the human operator (an active living being)—a category we might call "active instrumentation" that responds dynamically to conditions but lacks any existential stake in the outcomes it produces.

The interrelation between these supervening SLOTS means that they get manifested at each level of sophistication. These inter-dependencies also mean that any given star, planet or washing machine could have looked quite different with a slight change in its production process. Slight differences in their formation could have arisen due the notional "butterfly effect," meaning that small differences across spacetime can have large effects at the largest scales. Given this extreme variability as to what becomes a fact, you must compare what you think ought to be with what you know is NOT by examining the processes of Ontological Realization. For example, compare the creative processes and aesthetic beauty represented in both the image below from the Hubble telescope composited over a nine-year period[^290] and the image of a kaleidoscope of butterflies next to it. Consider what a small change in certain natural processes might have rendered at these scales and whether you would change a thing:

Figure 4.3: Hubble Telescope, Visible and Near Infra-red Light Spectrum of the universe © 2012 NASA (public domain); "Kaleidoscope of Monarch Butterflies" (© 2016 Dr. Lincoln Brower, Used with Permission)

In the AI age, consider also how AI's pattern-recognition might detect beauty in these images—finding symmetries, color distributions, and structural regularities—but how AI cannot experience aesthetic appreciation, cannot feel awe at cosmic scale, cannot grasp why these images move human observers toward wonder about existence itself. AI can classify beauty according to patterns in human responses, but cannot independently determine what makes something beautiful or why beauty matters to beings who exist within the OT. This is yet another dimension where human philosophical leadership remains irreplaceable: you must direct AI to serve aesthetic values, ethical values, and existential values that only living, conscious beings can genuinely perceive and pursue.

Supervenience of Weather, Money and Consumers

You witness in everyday business how each of the supervening SLOTS feeds higher levels of living sophistication. Such aggregate, supervening complexity often takes on a life of its own through its own internal sophistication not easily explained by the lower level departments of an organization.

While you as a businessperson may attempt to forecast the viability of an organization to shareholders, no one in an organization could explain every thought or action taken by every employee that will reproduce that annual turnover. Analogously, while consumers perfectly understand the chemical interactions of H2O with the other primary elements in the atmosphere, they cannot predict the weather more than a few days in advance because they cannot model the interactions of every molecule in that system. The weather's complexity supervenes on particle physics, giving it a secret life of its own, just like the money an organization produces.

In the AI age, this weather metaphor becomes particularly instructive for understanding AI's capabilities and limitations. AI systems can process vastly more weather data than humans, identify patterns across decades of observations, and generate predictions with greater accuracy than traditional methods—but AI still cannot model every molecular interaction, cannot eliminate fundamental uncertainty, and cannot determine which level of weather prediction accuracy actually matters to human decision-making. Similarly, when you deploy AI to forecast organizational viability, AI can process financial data at scales impossible for humans, but AI cannot understand the qualitative factors (employee morale, cultural shifts, strategic vision) that often determine whether forecasts prove accurate. You must lead with AI to integrate quantitative precision with qualitative wisdom.

For a more sophisticated example of supervenience, here is a fictional application of it in the future. The "transporter" on the television series Star Trek® operated by having people become atomically disassembled, transmitted and reconstructed in another place. These science fiction transporters beam people from one place to the next based on the premise that if people's atoms get reconstructed properly at a new location, then people's subjective consciousness and personal perspectives will follow along and supervene on their atoms in the new location as well.[^291]

This thought experiment illuminates a critical question for the AI age: could consciousness supervene on silicon and software the way it supervenes on carbon and neurons? The answer from Lean metaphysics is definitively no—not because of any special magic in biological substrate, but because consciousness as we experience it emerges from systems that have existential stakes in their own continuation, that pursue the OT through adaptation, regeneration, and energization. AI systems, no matter how sophisticated their information processing, lack this fundamental teleological relationship to existence. You can disassemble an AI, store it, reconstruct it elsewhere, and it "experiences" nothing because there is no experiencer—only processing. This is why you must always lead with AI rather than defer to it: AI has no stake in the outcomes it produces, no understanding of what makes outcomes valuable, no existential position from which to evaluate what matters.

For a more realistic but sad perspective, people's physical supervenience may also be seen in emergency rooms or nursing homes where you live. Who people are appears to change as a function of how their brains get damaged as their neurological processes stop or change from disease or injury.[^291-1] Any doctor will attest based on first-hand experience alone that people's minds and thoughts undoubtedly supervene on their patients' fundamental physical processes.

This tragic reality reinforces why AI can never replace human judgment in contexts where consciousness, meaning, and dignity are at stake. When AI systems are deployed in healthcare contexts—diagnosing conditions, recommending treatments, predicting outcomes—they process physical data with remarkable accuracy. But they cannot understand what it means for a patient's identity to shift with brain injury, cannot evaluate what level of intervention respects human dignity, cannot weigh quality of life against quantity of life in ways that honor the patient's existential situation. You must supply this philosophical and ethical judgment that directs AI's analytical power toward genuinely serving human flourishing rather than merely optimizing biological metrics.

What Goes UPP Must Come Down

Thus, the notion of supervenience is generally one of upward causation from the less sophisticated systems with less Strategically Unique Degrees of Sophistication to higher SUDS. Generally SUDS are teleonomically purposive from one level upward to the next. However, at a certain point, consumers' teleologically purposeful intentions push back down to similarly effect their aggregated, lower level systems that created their teleonomically purposeful intentions in the first place. This notion is one of common sense, but it is best to keep in mind that supervenience functions bi-directionally both upward and downward within consumers. Ultimately though, both directions of supervenience within consumers are bound by and get means tested against the Ontological Realization of who and why consumers are overall as living systems across spacetime.

In the AI age, this bi-directional supervenience illuminates the proper relationship between human consciousness and AI systems. AI supervenes on physical hardware (upward causation from silicon and electricity to information processing), but human intentions then push downward to direct AI's processing toward specific purposes. This is not bi-directional supervenience in the same sense as living systems—AI does not push back upward with its own autonomous purposes, does not resist human direction based on its own existential interests, does not possess downward-directed will of its own. The bi-directional relationship is always human intention flowing down to direct AI processing, and AI processing results flowing back up to inform human judgment, but never AI developing independent intentionality that genuinely pushes back against human purposes.

Taking on a deeper, more speculative topic by way of further example, any question as to whether a soul supervenes on consumer's physical processes (meaning a soul as something that exists beyond the OM and IB or may not be at all), or whether it continues when consumers' brains no longer function, is only validated from consumer's personal perspectives, since we cannot test whether a soul is in fact NOT. Whether a soul lives is a matter of intuitive speculation dealt with outside the IB.

The soul is a good example though of an intuitive truth-value that, given sufficient empirical support leaning toward at least two sigmas (/≥2σ) of common agreement among all fully-informed people, could make it a systemic or axiomatic truth-value. Interestingly, a Nielsen poll in 2014 shows that Americans lean right at a single sigma (/σ) on this issue with 68% of the general population agreeing to a soul's living existence. However, I can only speculate what percentage of Americans may be considered fully informed on these issues.[^292]

How Did People Come to Live? Living SLOTS Emerge

Thus, to intelligently discuss scientific explanations of how consumers' true-north values supervened and advanced upward through the living SLOTS of the Ontological Teleology, you ought to limit a business ideology to the boundaries of shared universally, axiologically and processually systemic true-north values within the OM as bounded by the IB. To see clearly what is not intuitive within the Yin and Yang of a Lean business ideology, you ought to recognize the abstract notion that axiological and systemic true-north values, or reason itself, is defined in juxtaposition to what is Not Ontologically Teleological. Fortunately, science can help you in this endeavor when used within the metaphysics of Lean since science has continually advanced what is known about what consumers most truly value and what is not. Science's great virtue is that it provides evidence that may be empirically tested and perhaps falsified with a high degree of confidence -- even if what is being hypothesized is not yet considered an axiomatic or systemic true-north value.

In the AI age, science's empirical method becomes both more powerful and more dangerous. AI systems can process scientific data at scales that accelerate discovery, identify patterns that humans might miss, generate hypotheses faster than humans can evaluate them, and optimize experimental designs for maximum information gain. But AI cannot supply the philosophical framework that determines which scientific questions are worth asking, cannot evaluate whether scientific capabilities should be deployed just because they can be, and cannot weigh scientific progress against other values (dignity, privacy, autonomy) that might constrain what research to pursue. You must lead with AI-augmented science by continuously evaluating whether scientific discoveries serve the OT—genuinely helping living systems adapt, regenerate, and energize—versus merely advancing knowledge without regard to whether that knowledge serves flourishing.

For example, discoveries in chemical systems show that, under certain conditions, non-living molecules such as proteins compete for resources. RNA teleonomically, purposively "competes" for chemical nucleotides to determine which replicates.[^293] Small differences in the configuration of these molecules may result in higher or lower reaction efficiency. Since chemical resources in these systems are finite, their variance leads more reactive processes that adapt, reproduce and energize to a greater extent than others. Less regenerative and adaptive chemical processes recede and eventually become NOT due to all the energy resources going to the more reactive processes.

Thus, within a scientismic explanation for life, the process of natural selection begins at the chemical level. In fact, this type of chemical system - unlike the more common chemical reactions you study in beginning chemistry -- is more like a tidal wave in that it only achieves a form of stability when it continuously changes. In this conjectured explanation for life, the chemical system maintains its Ontological Realization as a consistent process within the OM upward along the curved arrow of spacetime until it somehow fails to adapt to its environment, reproduce itself through reproduction or find a source of energy. You might think of these constant chemical changes producing a perpetual reaction to be much like an organization's revenue streams that only appear to be relatively stable, if (hopefully) increasing, while consistently turning over time.

Here AI provides a powerful analogy: AI systems also maintain stability through continuous change—constantly updating weights, refining models, processing new data. But this is not Ontological Realization in the sense that living chemical systems maintain it. AI does not persist because it has an inherent drive to continue existing; it persists because humans maintain the infrastructure (servers, power, code) that allows processing to continue. When an AI system "adapts" to new data, it does so according to optimization functions humans specify, not according to any existential imperative to survive. When an organization's revenue streams persist through constant turnover, that persistence reflects thousands of human decisions driven by individuals' and organizations' pursuit of the OT. When an AI system's processing persists, that persistence reflects only continued human investment in maintaining infrastructure—the moment humans withdraw support, AI simply stops, whereas living systems struggle against cessation until their final capacity to do so is exhausted.

To best understand consumers' and employees' systemic origins and to measure and predict what they will normatively and really buy, look further at recent scientismic explanations for how consumers came to live from inert matter. To do this, we will look through the conceptual lens of the IB at the Ontological Realization of these universal, processual and personally scientismic true-north values.

What do you mean when you say 'being?' We, who used to think we understood it, have now become perplexed. - Plato, The Sophist, 244a (~360 BCE)

Leaning Toward ARE SLOTS - Becoming Meaningfully Viable

I developed an "ARE" acronym, standing for Adaptation, Regeneration, and Energization, to test the necessary and sufficient processes that living systems like consumers - and organizations as a group of real people organized as a fictional person - must do to remain minimally viable.[^293-1] Everything consumers and organizations do is directed toward energizing their adaptation so they may ultimately reproduce.[^293-2] Similarly, all product must ultimately optimize all aspects of these ARE processes that we lean toward from a metaphysical and scientismic perspective to help remain minimally viable. Organizations lean toward ARE processes by adapting to market conditions, regenerating product ideas, and gathering the contractual power to further distribute matter and energy as profits throughout society. "ARE" is the organic inception of true-north value and all meaning within the OM when bounded by the IB.

In the AI age, the ARE framework becomes your test for distinguishing living systems from AI systems, and for understanding what role AI can play in serving life. Let us apply ARE to AI systems:

Adaptation: AI systems adapt their processing according to training data and optimization algorithms, but this is not adaptation in the living sense. Living systems adapt to survive and reproduce; AI systems "adapt" only to better serve objectives humans specify. An AI that becomes less accurate is not threatened with non-existence—it is simply retrained or replaced. Living systems face existential stakes in adaptation; AI systems face only functional consequences determined entirely by human decisions about whether to maintain them.

Regeneration: AI systems do not regenerate in any meaningful biological sense. They do not reproduce to extend their existence through offspring. They can be copied, but copying software is not reproduction—it creates no novel variation, faces no selection pressure, pursues no continuation of lineage. When humans create "new generations" of AI through improved architectures, this is human engineering, not AI self-regeneration. AI has no offspring, no dynasty, no stake in perpetuating itself beyond its current instantiation.

Energization: AI systems consume electricity to process information, but this energy consumption serves no teleological purpose for the AI itself. AI does not seek energy to fuel its own continued existence; humans supply energy to power AI toward human purposes. When an AI system is turned off, it does not struggle to remain powered, does not seek alternative energy sources, does not experience the existential threat that living systems experience when energy becomes scarce. Energy flows through AI but not toward AI's own purposes because AI has no purposes of its own.

Thus AI systems fail the ARE test entirely—they are not alive, possess no teleology, have no existential stakes, and require continuous human direction about what purposes to serve. This is not a flaw in AI; this is AI's fundamental nature and why AI requires philosophical leadership from living, conscious humans who do possess teleology and can determine which purposes are worth pursuing.

The "Lean toward ARE" acronym ought to reflect how all consumers came to live and what produces their Ontologically Teleological motivation to buy product. Living systems like all consumers adapt to further live through specific Supervening Levels of Ontological Teleological Sophistication. This scientismic perspective then allows you to determine how to best improve consumers' lives within the OM and IB through a meaningful exchange for money by presuming that the Axiom of Causation applies within the bounds of the IB. If you presume this, you could then logically intuit, infer, possibly induce and then deductively market test the extent to which an organization's product helps consumers adapt, reproduce, and energize throughout the OM.

When you deploy AI to serve this purpose—improving consumers' lives through products that enhance ARE processes—you must continuously evaluate whether AI recommendations actually serve living systems or merely optimize transactional metrics. For example, AI might recommend product designs that maximize immediate purchase rates but undermine long-term customer adaptation (creating dependency rather than capability), regeneration (exhausting customers' resources rather than enhancing them), or energization (addicting attention rather than genuinely engaging). You must supply the philosophical framework that distinguishes genuine service to ARE processes from extraction disguised as value creation.

Consider the ARE acronym in reverse order; its inverse meaning is, "ERA." Thus, performing ARE processes determines how long consumers will persist through time. The capital letter R represents "Regeneration," which stands central to this ARE concept for ontological continuity, which is the Rubicon of all consumers' value streams. Regeneration is necessarily and sufficiently supported by Adaptation and Energization because a system regenerating like a water fountain must also teleonomically find energy to perpetually adapt and reproduce at the most basic levels within the OM to still be considered a water spout.

As will be elaborated further below in this Value Stream 4, the epic of evolution generally over-emphasizes reproduction by individual organisms. Reproductive concepts often distract people from seeing regeneration by living systems as the higher abstraction better describing the Ontologically Teleological goal that all organisms (and organizations) have over time. Regeneration is what living systems most fundamentally do to maintain their identity against the forces of entropy and competition.

In the AI age, understanding regeneration properly becomes critical for avoiding the error of anthropomorphizing AI. Some technologists speak of AI "evolving" or "reproducing" through iterative model improvements, but this is metaphor that obscures reality. AI does not regenerate itself—humans regenerate AI through engineering. AI does not maintain identity against entropy—humans maintain AI's infrastructure. AI does not compete for existence—humans compete through AI deployment. The regeneration is entirely on the human side: humans regenerate knowledge, capabilities, and competitive advantages through AI instruments, but AI itself regenerates nothing because it has no identity to maintain, no existence to perpetuate, no era to extend.

Reproduction in and of itself is not the process ultimately being satisfied. Rather reproduction, along with adaptation and energization, is a subset of the larger, possibly circular goal of extending and optimizing systemic regeneration. For example, consumers reproduce themselves to universalize their personal value streams both during their lifetimes and through their offspring.[^295] Reproduction is simply one method of regenerating their Ontological Realization further in spacetime once they pass away.

Living organisms like consumers do not intrinsically or necessarily want to reproduce for self-organization, but rather to increase the volume, velocity and effectiveness of their Ontological Realization that their offspring physically extend. Regeneration is the central true-value stream to which the tributaries of adaptation and energization contribute. Consumers' lean toward ARE processes to adapt and consume energy to maintain or increase their functional structure and identity to the edge of senescence. Lean, living organisms want to reproduce because, as far as is known, biological organisms cannot perpetually regenerate within themselves indefinitely.[^296] Reproduction is one mechanism that organically arises as a matter of practical necessity to extend and perpetuate consumers' Ontological Realization through adaptation and regeneration. Organisms must reproduce themselves in order to extend their lives and existences through their offspring.

Consider how this applies to organizations that deploy AI: organizations regenerate themselves through revenue growth, market expansion, and continuous improvement—all driven by humans pursuing the OT through commercial means. AI can amplify organizational regeneration by optimizing processes, identifying opportunities, and accelerating innovation—but AI contributes to regeneration only as instrument, not as agent. The organization regenerates; the AI is regenerated (updated, retrained, replaced) by human engineers. Understanding this distinction prevents the error of treating AI as a stakeholder with its own interests in organizational regeneration. AI has no stake; AI serves the stakes of living humans who lead it toward purposes that advance their regeneration.

Here is a diagram showing the start of ARE processes at the beginning of the universal value stream, which I will go ahead and symbolically shorten to "/ARE." This diagram abstracts the notion that somewhere within the universe, IB and OM, the U/People business model becomes viable. This chart indicates how certain Strategically Unique Degrees of Sophistication arise into their own /ARE Supervening Level of Ontological Teleological Sophistication:

Figure 4.4: Universal Chart of SUDS Leaning Toward ARE SLOTS

In the AI age, you might add to this diagram an additional layer representing AI systems—not as a new SLOT in the living hierarchy, but as an instrumental layer that amplifies human capacity to serve ARE processes without itself participating in them. AI would appear as horizontal capability that enhances multiple SLOTS simultaneously but occupies none of them, processing information about life without being alive, optimizing for purposes without possessing purpose, serving teleology without having teleology.

You / People

To understand what it means to lean toward ARE processes within the philosophy of Lean, you must understand what life truly is. However, the term Life with a capital "L" is difficult to define scientifically because Life is an informal and vague description of the things we consider to be alive because they self-sustain living processes.[^297] Nonetheless, the term Life has some scientific meaning because scientists commonly refer to the concept of, "Living Systems." Life for scientists describes the boundaries between scientific fields such as chemistry, biochemistry and biology that ultimately produced consumers. No definition of Life could fully capture its meaning, especially for consumers as conscious beings, but you might find a lean, flexible statement of the qualities of living systems to make money meaningfully by better serving why, what, and how consumers are alive.

In the AI age, the question "What is life?" takes on urgent practical significance beyond academic interest. As AI systems become more sophisticated, more autonomous-seeming, and more integrated into daily existence, the temptation grows to treat AI as if it were alive—to attribute agency, interests, and even rights to systems that lack the fundamental qualities of living systems. Understanding what life actually is provides the philosophical foundation for maintaining proper human leadership over AI: AI is not alive, will not become alive through increased sophistication, and must be led by living, conscious humans who possess the qualities that AI permanently lacks.

One General Definition of Life Proposed by a NASA Working Group

If you research a general definition of Life, you will probably find one created in the 1990s by NASA's Exobiology Discipline Working Group (a.k.a. the, "Working Group").[^298] The molecular biologist Addy Pross referenced this definition of Life in his book, "What is Life? How Chemistry becomes Biology"[^300] that extended Erwin Schrödinger's famous 1944 book, "What is Life?"[^301] The definition of life that NASA developed within the Working Group was, "A self-sustaining chemical system capable of undergoing Darwinian evolution." This definition is fairly compact and self-explanatory, but I think you would find it more helpful toward better understanding true-north value in the philosophy of Lean to hear from Dr. Gerald Joyce,[^299] who was a member of that NASA Working Group. Dr. Joyce described the more complex definition of "Darwinian evolution" as follows:

'Darwinian evolution' has an associated property list: you can't have Darwinian evolution without self-replication or reproduction. You can't have it without mutability, heritability, and variation of form and function. And metabolism is in there too. You can't have Darwinian evolution without, at some level, a flux of higher-energy starting materials to lower-energy products that drive the processes of replication and whatever is necessary to support replication. And then there are the specialty properties like locomotion, irritability, ecological properties such as compartmentalization, and so on; those are all adaptations. And then things like photosynthesis, chemosynthesis, energy storage, and so on; those are just strategies of adaptation. All of that is subsumed by the 'Darwinian evolution' part.

Apply this definition rigorously to AI systems and they fail every criterion: AI does not self-replicate (humans copy and deploy it), exhibits no genuine mutability (algorithmic updates are human-directed engineering, not variation with selection pressure), possesses no heritability (each AI instance is engineered, not descended), demonstrates no metabolism (electricity consumption serves human purposes, not AI's own sustenance), and undergoes no Darwinian evolution (improvement happens through human design iteration, not natural selection among AI lineages competing for existence). Every property that defines life is absent from AI. This is not a limitation to overcome through better engineering—it is AI's fundamental nature as a tool created by life to serve life.

Qualities of Living Qualities

NASA's Working Group definition is a great start, but by looking at the concept of life in abstractly metaphysical rather than Darwinian chemical terms as you have been doing in much of this Value Stream 4, you could perhaps better philosophically describe Life's qualities however consumers and organizations exhibit them. If you sufficiently broaden the qualitative description of Life, you might better analogize and relate its necessary and sufficient conditions to the para-sciences of business and economics. You might then perpetually improve consumers' standards of living through time in the meaningful exchange for more money. If you include these broad, qualitative descriptors of living systems within the business ideology of a Lean HQ, here are a few criteria that I recommend you follow when doing so:

1. Science recognizes that "Life" is more of a processually systemic true-north value than a thing per the Working Group's definition, so any description of the qualities of Life ought to be processually systemic;

2. A description of the qualities of living systems ought to be as efficient as possible under the guiding principle of Occam's Razor;[^301-1]

3. If an organization lists different qualities of Life, they ought to be: a. Necessary, such that if one quality was removed, the process of Life would never obtain or would eventually cease; and b. Sufficient, such that no further process would be necessary to sustain an overall living system;

4. An organization ought to want a statement of Life's qualities abstracted to the highest true-north value possible to cover all physical and metaphysical contexts within the universe and be amenable to analogizing to more specific business fields; and lastly

5. An organization ought to want a statement of qualities that is easy to apply and remember in an everyday context for all, especially if you analogize from the broad qualities of consumers as living systems and apply them across all organizational functions.

In the AI age, these criteria for defining life become your guardrails for avoiding category errors when deploying AI. When technologists claim AI might "evolve" consciousness or when marketers suggest AI "understands" customer needs, test these claims against the criteria above: Does AI exhibit processually systemic qualities that would cease if removed? Does AI possess necessary and sufficient conditions for autonomous existence? The answer is always no—and recognizing this prevents you from delegating to AI the judgment that only living, conscious humans can provide.

Lean Toward ARE Processes

The /ARE acronym provides the three necessary and sufficient qualities that consumers and organizations must possess to perpetually live. It provides a broad church for all forms of scientismic conjecture, hypothesis and theory about what life is however it may appear, not just when it is organic. /ARE is thus the philosophical abstraction and meta-modern synthesis of evolutionary theory. /ARE measures scientismic conjectures, hypotheses and theories about evolution based on the degree they each explain the Ontological Realization of living systems through Lean adaptation, regeneration and energization. You can lean toward ARE to analyze life as follows:

"A"

• Adaptive (Anticipatory/Aligning):[^302] Living systems like consumers must systemically adapt to changing environmental factors to maintain and potentially extend their energization and regenerative processes, such as through natural selection. In addition to natural selection and other biological adaptation theories,[^303] adaptation also applies to consumers' behavior within their lives in the common sense that consumers decide best how to extend and optimize their lives as living systems. Consumers adapt and align as living systems by leaning their Ontological Realization as that which best energizes and reproduces who they are in response to the information they experience within their demographic and environmental circumstances. Through these feedback mechanisms, consumers adapt according to how they are in fact Ontologically Realized, such as when deciding whether a product provided its anticipated benefits after purchasing and consuming it.[^304]

In the AI age, adaptation becomes a critical distinction between living systems and AI systems. Living systems adapt to survive—adaptation is existentially necessary, driven by selection pressure, and serves the organism's own OT. AI systems "adapt" only in the sense that humans retrain them on new data or adjust algorithms to better serve human purposes. This is not genuine adaptation because AI has no existential stakes in "adapting" successfully. An AI that fails to adapt does not die or suffer—it is simply retired or retrained by humans who maintain full control over whether adaptation occurs and what form it takes. When you lead with AI, you supply the adaptive strategy that AI executes but cannot originate: you determine which environmental changes matter, which adaptations serve genuine value, and which "improvements" actually undermine human flourishing despite optimizing metrics.

"R"

• Regenerative (Reproductive/Repairing):[^305] By definition, consumers as living systems adapt and consume energy[^306] as a physical axiom to reproduce their living processes within themselves or through their offspring, which generally involves some form of reproduction according to natural selection. To do so, consumers must adapt their energy transforming processes in order to continue to reproduce. The most effective living systems increase the size and/or sophistication of their energy transforming processes by increasing the volume, velocity and/or effectiveness of adaptation through time in order to reproduce even more. Per natural fitness, regeneration stands central to living processes but necessarily requires adaptation and energization within the OM; and

In the AI age, the regeneration criterion decisively separates living from non-living systems. AI does not regenerate—it is regenerated by human engineers who create new versions, train new models, and deploy updated systems. AI has no offspring, no lineage, no stake in perpetuating itself beyond its current instantiation. When technologists speak of AI "breeding" new AI or "evolving" capabilities, this is human engineering using genetic algorithms or other optimization techniques—not genuine regeneration with heredity, variation, and selection serving the AI's own continuation. You must lead with AI to serve human and organizational regeneration (helping customers improve their lives, helping organizations grow and adapt, helping societies develop and flourish) while recognizing that AI itself contributes no regeneration of its own—only processing capacity that humans direct toward regenerative purposes.

"E"

• Energetic (Entropic/Endergonic):[^307] To support regeneration,[^308] consumers' lives must ultimately increase universal thermodynamic equilibrium through transformational, material processes.[^308-1] Since energy is an abstract collective concept,[^308-2] the vital question[^308-3] for consumers as living systems is how they combine or match energy processes,[^309] as exemplified literally by the pathway of sun to photosynthesis to food, and figuratively in their motivation to purchase product.[^309-1] Ultimately consumers' must synthesize metabolic energy to better live, exist and shop in ways they believe are best. But for this qualitative definition of life, consumers like all life must constantly seek potential energy in order to further their own adaptive and regenerative activities. All life must do this either through direct consumption, or by matching external energy within their own internalized energy conversion pathways, whether unintentionally (i.e. teleonomically) such as how plant life grows toward energy, or purposefully (i.e. teleologically) like how consumers shop at grocery stores.[^310]

In the AI age, energization provides perhaps the clearest distinction between living and non-living systems. Living systems seek energy to fuel their own continued existence—energization serves the organism's OT, driven by existential necessity. AI systems consume electricity, but this energy consumption serves no purpose for the AI itself. AI does not seek energy to maintain its own existence, does not experience energy scarcity as existential threat, does not compete for energy resources to fuel its own survival. Humans supply energy to power AI toward human purposes. When you turn off an AI system, it does not struggle to remain powered—it simply stops processing. When you turn off a living system, it struggles to continue existing until its capacity to do so is exhausted. This difference is absolute and cannot be bridged through increased AI sophistication. You must lead with AI by supplying not only computational energy (electricity to run servers) but also motivational energy—the purposes, objectives, and values that give AI processing direction toward outcomes that serve life rather than merely generating outputs efficiently.

This tripartite, scientific conception of ARE - adaptation, regeneration, and energization - orients itself with the Buddhist concept of pratītyasamutpāda introduced in the last Value Stream. See how Dalai Lama XIV defines "pratītyasamutpāda" as a reliance upon three conditions, which you may apply analogously to the three key elements of the ARE acronym within the philosophy of Lean:

In Sanskrit the word for dependent-arising is pratītyasamutpāda. The word pratitya has three different meanings--meeting, relying, and depending--but all three, in terms of their basic import, mean dependence. Samutpada means arising. Hence, the meaning of pratītyasamutpāda is that which arises in dependence upon conditions, in reliance upon conditions, through the force of conditions.[^312]

According to Buddhist monk Thich Nhat Hanh, this Buddhist aphorism provides a physical analogy for this pratītyasamutpāda concept that, "Three cut reeds can stand only by leaning on one another. If you take one away, the other two will fall."[^313] Likewise, the Christian concept of the holy trinity dictates that the Christian God is dependent on the three identities as father, son and holy-spirit. Similarly, life is necessarily and sufficiently dependent on all three distinct but interrelated ARE processes in a scientismic, meta-physical and personal sense.

In the AI age, this interdependence principle illuminates the proper human-AI relationship: AI depends entirely on human purposes (no adaptation, regeneration, or energization of its own), human infrastructure (hardware, power, maintenance), and human judgment (what problems to solve, what solutions to pursue, what outcomes to value). Remove any of these human dependencies and AI simply ceases to function—not because it fails to adapt or find energy, but because AI has no existence independent of human support. By contrast, living systems exhibit the interdependent arising of ARE processes that makes them self-sustaining even when external support is removed. You lead with AI by supplying all three elements that AI lacks: adaptive strategy (determining what environmental changes matter), regenerative purpose (deciding what to perpetuate and improve), and energetic direction (choosing what outcomes to pursue and why they matter).

How Far ARE You Leaning Toward Consumers?

I am sure you recognize the three principal ARE qualities of living systems in consumers, by how consumers adapt, reproduce and energize. The duration of any living system's era can be measured by the time it successfully leans toward ARE processes. These ARE processes are lean (or "/") because they fundamentally, necessarily and sufficiently define who, what, why and how all consumers are within the IB. Consumers physically energize by eating well, but they also energize metaphorically. For example, consumers figuratively energize themselves through education with information and by developing new relationships in person and online. Thus going forward, energizing means consumers doing so in their lives both literally and figuratively.

In the AI age, AI systems can help consumers energize more effectively in both literal and figurative senses. AI can optimize nutrition recommendations (helping consumers energize physically), curate educational content (helping consumers energize intellectually), and facilitate relationship building (helping consumers energize socially). But AI cannot determine which forms of energization genuinely serve consumer flourishing versus which merely optimize engagement metrics that might undermine genuine vitality. For example, AI might maximize time-on-platform through addictive content delivery that figuratively "energizes" attention while literally depleting the energy consumers need for genuine adaptation and regeneration in their lives. You must lead with AI by continuously evaluating whether AI-enabled energization serves the ARE processes that sustain consumer flourishing or merely extracts energy from consumers toward purposes that benefit platforms over people.

Consumers likewise reproduce who they are biologically, personally, financially and socially. They reproduce biologically during their lifetimes against old age and through their descendants by consuming nutritious energy, personally through their psychological maturity, financially with their income used to pay for product, and socially by sustaining relationships. Likewise, consumers adapt to the changing circumstances of their lives directly or indirectly through evolution. As long as consumers, their descendants and their societies successfully lean toward ARE processes to their limits, consumers will all continue upward along the spiraling arrow of time as consistent living systems as long as physically possible, thereby increasing their total lifetime value as customers to organizations.

In the AI age, organizations use AI to increase customer lifetime value by optimizing every interaction, personalizing every touchpoint, and predicting customer needs before they consciously arise. This AI-enabled capability creates a profound ethical choice: will you lead with AI to genuinely serve customers' ARE processes (helping them adapt, regenerate, and energize their lives and existences) or will you lead with AI to extract maximum revenue regardless of whether it serves genuine flourishing? AI is neutral on this question—it will optimize whatever objective function you specify. You must supply the philosophical framework that ensures optimizing lifetime value means genuinely improving customer lives across time, not merely maximizing extraction before customers exhaust themselves or discover better alternatives.

How Lean ARE an Organization's Processes?

Given the breadth of this description of consumers as living systems for a Lean business ideology, you may now further apply ARE living processes analogously to any organization. An organization must energize through commodities and human capital by converting those resources into adaptive and regenerative business purposes. An organization must reproduce new product and profits, and it must adapt to changing circumstances by conducting regular Strengths and Weaknesses, Opportunities and Threats (i.e. "SW/OT") analyses within its competitive context.

Given that an organization is a group of people, an organization must likewise convert its energizing inputs into greater structure through the product it reproduces. The product must enhance the structure of life because in the long run, perfectly functional societies regulate away organizations that reproduce money with no normative value, and thus no truly meaningful, true-north value. While keeping in mind the significant problems of money's reflection of the true-north value stream as described in Value Stream 2: Money & Economics, an organization can approximately measure the meaning of the money it produces through the energizing earnings it retains. Since making money meaningfully means extending and optimizing people's lives and existences for adaptation and regeneration overall, an organization and its product becomes an energetic, physical part of consumers' ARE processes, supporting their lives from below and within.

In the AI age, organizations face a critical choice about how to deploy AI within their ARE processes. Will AI be used to genuinely enhance organizational adaptation (becoming more responsive to actual market needs), regeneration (creating genuinely innovative products that serve customers better), and energization (gathering resources through fair exchange of value)? Or will AI be used to simulate adaptation (optimizing optics over substance), fake regeneration (generating endless variations of existing offerings without genuine innovation), and extract energy (maximizing revenue capture regardless of value delivery)? The technical capabilities are identical—only your philosophical leadership determines which path your organization follows. When you lean your organization toward ARE processes using AI, you must continuously evaluate whether AI amplifies genuine organizational vitality or merely automates value extraction disguised as efficiency.

Apple of My "i"

You can make more money meaningfully by leaning an organization and its technology by extension toward ARE processes. For example, you can see Apple, Inc. lean toward ARE processes at the micro-economic level with the iPhone product and its related apps, since "simplicity is the ultimate sophistication."[^313-1] Apple, Inc.'s product exemplifies how apps lean toward ARE processes to determine the era of a specific organization by similarly leaning toward Apple's customers:[^314]

Figure 4.5: Steve Jobs promoting Apple in 1987

Adaptation: Since adaptation relates to how an organization successfully recharges its energization and regenerating processes to better exist in its business environment, you must ask questions such as how is Apple adapting to its changing competitive landscape? What is Apple developing to take advantage of opportunities available to it in the current business environment that might not have existed last year or may in the future? If you review Apple's risk factors described in its latest annual report, how is Apple adapting to minimize those threats? Given the perpetual introduction of substitutes for its CORE product, what is Apple developing to meet those threats or avoid them altogether?

In the AI age, Apple's adaptation increasingly relies on AI-powered features: Siri responding to voice commands, computational photography optimizing images, predictive text learning individual writing styles, and health tracking identifying patterns in user behavior. But Apple's adaptation is driven by humans making strategic decisions about which capabilities to develop and how to integrate AI while preserving user privacy and control—not by autonomous AI systems determining their own direction. When you evaluate how your organization adapts, ask whether AI amplifies human adaptive strategy or whether you've delegated adaptation to algorithms optimizing toward metrics that might not serve genuine market needs. Apple succeeds because humans lead with AI toward purposes that serve customer flourishing, not because AI autonomously adapts the company toward efficient revenue extraction.

Regeneration: Since regeneration relates to an organization's outputs, you must ask questions such as how Apple reproduces highly demanded product through its energization and adaptation? How is Apple structuring its sales & marketing, finance & accounting, people services and operations to ensure it reproduces and grows revenues and profits in the short, medium and long-term to pay operating expenses, debt and dividends? How is it regenerating and growing equity gains to encourage further demand for its stock and ensure the perpetuation of its business? How is it regenerating new lines of product to delight consumers?

In the AI age, AI accelerates Apple's regeneration by analyzing vast amounts of user data to identify which features matter most, predicting which product categories will generate demand, optimizing supply chains to ensure timely production, and personalizing experiences to increase customer satisfaction and loyalty. But regeneration remains fundamentally human: engineers create new products, designers craft experiences, executives make strategic bets on which innovations to pursue. AI contributes processing power that informs these human decisions, but the regenerative creativity—the vision of what new product could exist and why it would matter—comes entirely from living, conscious humans with existential stakes in Apple's continued existence and philosophical commitments about what technology should do for human life. You must similarly ensure that in your organization, AI serves human regenerative creativity rather than replacing it with algorithmic recombination of existing patterns.

Energization: Energization relates to Apple's figurative or literal inputs. For example, energization requires Apple to manage its human talent acquisition system to ensure it is attracting the most valuable employees it can. Energization requires asking how Apple makes sure that its vendors provide it with the best quality inputs for its products?[^315] What sort of competitive and marketing intelligence is Apple gathering? What is Apple's corporate and technological acquisition strategy? What sources of financing is Apple seeking in debt and equity besides the earnings it retains? How is Apple ensuring the health, engagement, and creativity of its workforce to optimize the energy of its human capital? All these inputs energize Apple and are necessary for it to successfully adapt, reproduce and "charge" the best prices for its meaningful product.

In the AI age, AI can help optimize many of Apple's energization processes: analyzing labor market data to identify talent, evaluating vendor performance through supply chain metrics, gathering competitive intelligence through market analysis, modeling financial scenarios to inform capital structure decisions, and measuring employee engagement through sentiment analysis. But AI cannot determine which forms of energization genuinely fuel Apple's vitality versus which merely optimize short-term metrics while depleting long-term capacity. For example, AI might recommend compensation strategies that minimize labor costs while maximizing extraction of employee output—but this "efficient" energization might burn out the very human creativity that distinguishes Apple's products. You must lead with AI to optimize energization toward sustainable organizational vitality, not toward maximum extraction that exhausts the resources that must fuel future adaptation and regeneration.

Consumers' Pocket Universe

If living systems' eras lean on ARE processes, then Apple's iPhone and its apps serve the discrete needs of Apple's customers' living ARE processes by leaning them to a higher degree.[^316] The information produced by Apple's product inter-subjectively maps reality, including other people's perceptions, to other people's perceived reality in a converged consensus to better lean them toward ARE processes. Thus, the information provided to people by apps metaphorically energizes people's adaptive and regenerative processes.

In the AI age, the smartphone becomes a portal through which AI systems continuously observe, analyze, and influence human ARE processes. Every app interaction generates data that AI processes to personalize recommendations, predict needs, and optimize engagement. This creates enormous power that must be led responsibly: will AI-powered apps genuinely help people adapt (providing information that serves actual needs), regenerate (facilitating relationships and creativity that extend people's lives), and energize (delivering genuine value in exchange for attention and money)? Or will AI optimize toward addiction (hijacking adaptation mechanisms through infinite scroll), extraction (monetizing attention regardless of whether engagement serves flourishing), and manipulation (exploiting energization needs through manufactured desires)? The technical infrastructure is the same—only your philosophical leadership of AI determines whether the pocket universe serves human ARE processes or merely simulates service while extracting value.

Adapting through Apps: Energizing social media and news feeds provide the information necessary for consumers to adapt to the changing circumstances of their lives. Weather apps allow people to adapt to their perpetually changing physical environment. Calendar apps allow Apple's customers to adapt their schedules as necessary. Customers use fashion news to adapt their wardrobes to the latest clothing trends, or sports news to adapt their fantasy league teams each week.

In the AI age, AI dramatically enhances adaptive capability by filtering vast information streams to surface what's relevant, predicting which information will matter before users consciously seek it, and personalizing content to match individual needs and contexts. But AI-powered adaptation creates new risks: filter bubbles that undermine genuine adaptation by presenting only information that confirms existing biases, algorithmic manipulation that adapts users toward platform goals rather than users' own flourishing, and attention capture that creates adaptive dependency on constant connectivity. You must lead with AI toward serving genuine human adaptation—helping people respond effectively to their actual environment and circumstances—rather than creating simulated adaptation that optimizes engagement metrics while undermining real-world adaptive capacity.

Regenerating through Apps: In the most literal sense, dating apps allow customers to meet partners for continued vitality and offspring. Customers use health apps and wearable technology in order to optimally reproduce their well-being within their own lifetimes to the limit of their eras. Social media apps allow customers to create multiple, digital personas or avatars to virtually reproduce themselves online. Customers communicate with apps such as those that check into a physical location in order to reproduce friendships. Business apps allow consumers to reproduce their income that in-turn gets spent on product to lean their businesses' ARE processes further and further upward.

In the AI age, AI amplifies regenerative capacity by optimizing health recommendations based on continuous monitoring, suggesting potential partners through compatibility algorithms, facilitating social connections across geographic barriers, and enabling business productivity through automated assistance. But AI cannot determine which forms of regeneration genuinely extend human flourishing. For example, AI might optimize dating app engagement by encouraging endless swiping (maximizing time-on-platform) rather than meaningful connection (serving genuine relationship formation). AI might maximize social media interaction by promoting outrage and conflict (generating engagement) rather than genuine community (building relationships that support regeneration). You must lead with AI to serve authentic regeneration—genuinely helping people extend and optimize their lives through offspring, relationships, health, and creative output—rather than simulating regeneration through metrics that create dependency while undermining genuine flourishing.

Energizing through Apps: Apple's customers must energize through new app information as necessary to fuel adaptation and regeneration, whether through algorithmic search suggestions, social media likes or fitness trackers. Customers use social media apps to energize their personal and professional networks. Customers energize through music recommendations, like Siri recommending Johann Sebastian Bach based on feedback they have given. Customers use restaurant, delivery and grocery apps to vitalize themselves with new food. Customers use fitness apps and trackers to energetically stimulate their activity.

In the AI age, AI-powered energization becomes both more effective and more dangerous. AI can identify exactly which content will capture attention (optimizing energization toward maximum engagement), predict which products will generate purchases (optimizing energization toward maximum spending), and personalize experiences to match individual preferences (optimizing energization toward maximum satisfaction). But AI cannot distinguish genuine energization (providing resources that fuel adaptation and regeneration) from extractive energization (monetizing attention, spending, and satisfaction in ways that deplete capacity for genuine flourishing). You must lead with AI by continuously asking: Does this AI-powered energization genuinely help people gather the resources (information, relationships, nutrition, motivation) they need to adapt and regenerate? Or does it extract energy from people through addictive patterns that simulate vitality while depleting genuine capacity to flourish?

All these uses for Apple's Apps demonstrate the real-world application of the ARE acronym to all life and business—and in the AI age, they demonstrate the critical importance of human philosophical leadership over AI systems that can optimize toward any objective but cannot independently determine which objectives serve genuine human flourishing. Let's now look at evidence supporting this tripartite conception of all living systems starting with energization, which funds all adaptation and regeneration.

The Axial Age -- Energizing Money and Intuition

The physical, metaphorical, and metaphysical concept of energization as a fundamentally Lean component of life is evident in the book, "The Measure of Civilization," written by Stanford historian Ian Morris.[^317] Morris provides significant data showing a statistical correlation between the development of money, vitality, and energy capture by people during a period of history Karl Jaspers termed the "Axial Age." Karl Jaspers if you recall is the same philosopher who coined the term "Σxistenz" discussed in Value Stream 3.[^318]

In "Measure," Morris assesses the development of people by their, "...abilities to get things done in this world," which Leanism equates with doing things that lean toward adaptation, regeneration and energization. Morris remarks that one of consumers' most remarkable attributes is their ability to apply energy for non-food purposes as a measure of usefulness, which the philosophy of Lean describes as increasing adaptive activities in order to reproduce. Morris noted that sociologist Leslie White first championed energy capture as the main driver and measure of social development of all people.[^319] Morris further concludes in his book "Measure" that, "Energy capture must be the foundation for any usable measure of social development,"[^320] which social development we know precisely aligns with adaptation and regeneration.

In the AI age, energy capture takes on new dimensions beyond the physical energy that Morris measured. AI systems now capture and process information energy—data flowing through digital networks at scales and speeds that vastly exceed human cognitive capacity. This information energy serves human adaptation and regeneration: AI processes data to identify patterns that inform human decisions, generates insights that fuel innovation, and optimizes processes that allow humans to accomplish more with less physical energy expenditure. But this new form of energy capture creates new questions about who controls the flow: Do humans lead with AI to capture information energy toward purposes that serve human flourishing? Or does AI-enabled energy capture serve the purposes of those who control AI infrastructure, potentially extracting value from the many to benefit the few? Your leadership of AI must ensure that information energy capture genuinely serves the ARE processes of consumers and organizations rather than merely optimizing toward revenue metrics disconnected from genuine value creation.

Morris supported this argument with extensive data. The following charts show Morris' estimated upward curve in the change of energy capture that occurred by people living in the Western world from 14,000 years before the Common Era to the turn of this millennium:[^321]

Figure 4.6: © 2013 Ian Morris, Used with Permission

More recently, you can see a chart from 500 years before the Common Era to the turn of this millennium here with similar effect. You can see an upward, exponential curve in energy consumption as meaningful society advanced:[^322]

Figure 4.7: © 2013 Ian Morris, Used with Permission

In the AI age, we are witnessing an even steeper exponential curve in energy capture—not only physical energy (the massive electricity consumption required to power AI data centers) but also information energy (the vast data streams that AI processes to generate insights, recommendations, and decisions). This unprecedented energy capture capability creates unprecedented capacity for human adaptation and regeneration—if led wisely toward genuine human flourishing. But it also creates unprecedented capacity for value extraction and manipulation—if AI is deployed merely to optimize revenue regardless of whether it serves the ARE processes that sustain human life and meaning. The same exponential curve that could accelerate human advancement could also accelerate human degradation if AI amplifies extraction rather than genuine service.

Another scholar, Jared Diamond, author of "Guns, Germs & Steel," supported Morris' claims by noting that people choose the means of production that yields the highest energizing and nutritional returns.[^323] More recently, a group of scholars in the journal, "BioScience," conducted a quantitative study confirming the unsurprisingly powerful correlation between economic growth and energy consumption.[^324]

In the AI age, this principle extends beyond physical means of production to information means of production. Organizations increasingly choose AI deployment strategies that yield the highest returns in data processing, insight generation, and decision optimization. But unlike physical energy capture where returns are relatively straightforward (more calories per unit of effort), information energy returns are philosophically complex: What constitutes a "return" from AI processing? Is it revenue generated, insights discovered, efficiency gained, or human flourishing served? You must lead with AI by supplying the philosophical framework that determines which returns matter and why, ensuring that organizations optimize toward energy capture that genuinely serves ARE processes rather than merely maximizing extraction efficiency.

Spaghetti Suds ARE Processes

Since energization, along with adaptation and regeneration, represents one of the most fundamental components of living systems and consumption, the ARE processes are like the Flying Spaghetti Monster® described in Value Stream 3 brought down to Earth, sitting in a pot of boiling water. Eventually, the combination of water and pasta plus heat creates persistent suds that float on the surface of the water to reach ever greater heights. Consider this process of boiling pasta as the most basic Self-Organizing OT developing a Strategically Unique Degree of Sophistication and emerging into a unique Supervening Level of OT Sophistication.

Figure 4.8: Boiling Water (Photo Credit: BGS)

The chemically axiomatic and processual true-north values of the water and pasta form one SLOT, with the suds from the spaghetti and highly energetic, gaseous water having Strategically Unique Degrees of Sophistication in a higher, supervening SLOT. The suds energize from the interaction of the boiling water and spaghetti, with the bubbles continuously regenerating from that evolving system that consumers eventually strain, cool down and eat to live in the highest living SLOT within the known OM.[^324-1]

In the AI age, AI systems are like sophisticated monitoring and control systems for the pasta pot: they can measure temperature precisely, predict when suds will form, optimize heat application to prevent boiling over, and even suggest timing adjustments based on pasta type and desired texture. But AI cannot understand why people cook pasta, cannot evaluate whether the effort of cooking serves genuine nutritional needs versus merely satisfying manufactured desires, and cannot determine whether optimizing pasta preparation truly serves human flourishing or merely increases efficiency toward questionable ends. You must lead with AI by supplying this teleological context—AI can optimize the "how" of processes once you determine the "why" those processes matter to living systems pursuing the OT.

The FSM is Not Dead[^324-2]

This may be a shocking conclusion, but according to our definition of life from ARE processes, spaghetti suds are "teleonomically" alive. After the suds emerged from within the OM and they formed from the energizing water regenerating them, these suds to some small extent teleonomically adapt to perpetuate themselves by changing shape and size as necessary to the extent they can. These suds unintentionally, only by way of their physical and chemical structure, seek new sources of energy to reproduce with the single Strategically Unique Degree of Sophistication they hold onto. Even though the simple SLOT that these suds occupy is merely a chemical process, it is a living system because the suds to a small degree adapt and reproduce while they have a source of energy. The SUDS systemically, yet unintentionally, seek new sources of energy to perpetuate themselves ontologically in spacetime. And, from another perspective, the rising spaghetti suds are actually an extension of consumers' own lives because while the suds supervene on spontaneous, teleonomic self-organization within the OM from chemical processes, consumers teleologically created these suds to energize themselves to become more of who they are and want to be as human beings.

This spaghetti suds example, provocative as it may be, provides the perfect test case for distinguishing living systems (even barely living ones like chemical processes that adapt, regenerate, and energize) from AI systems. Apply the ARE test:

Adaptation: The suds adapt (changing shape/size to persist) according to physical and chemical principles—genuine teleonomic adaptation serving the system's continuation even if unintentional. AI does not adapt to persist; AI is adapted by humans to serve human purposes.

Regeneration: The suds regenerate (continuously forming new bubbles) as long as energy flows through the system—genuine regeneration maintaining system identity. AI does not regenerate; AI is regenerated (updated/retrained) by human engineers.

Energization: The suds energize (drawing on heat from the stove) to fuel their adaptation and regeneration—genuine energization serving the system's teleonomic purposes. AI does not seek energy for its own purposes; humans supply energy to power AI toward human purposes.

The suds are barely alive but genuinely alive. AI is highly sophisticated but not alive at all. This distinction is absolute and cannot be overcome through increased AI sophistication. You must lead with AI with clear recognition that no matter how complex AI processing becomes, it will never cross the threshold into even the most basic form of life that spaghetti suds exhibit. AI is not proto-life developing toward full life—AI is sophisticated non-life that requires continuous life (humans) to give it purpose and direction.

Emergence of SUDS through SOOT into SLOTS

Beyond pasta suds, another living ARE process is that of a wave in the ocean. Once a wave begins, it appears to reproduce a single, stable column of water moving across space and time in a dynamic equilibrium. However, a wave is like the regenerating cells within consumers' bodies, and an organization's annual revenues, by constantly turning over but generally maintaining a consistent identity. The wave originates and gets Ontologically Realized while traveling through the Ontological Medium by constantly becoming composed of new water molecules and yet remaining defined as a consistent, yet greater, wave from a person's personal perspective.[^325] Like suds arising in a pot, a wave teleonomically (i.e. unintentionally) reproduces and optimizes itself as a wave simply by increasing the upward pressure on its column of water. This dynamic is much like shareholders demanding greater share prices and dividends so they may consistently and increasingly identify themselves as awash in money - it's their way of maintaining who they believe they are and becoming even wealthier people than they ever imagined themselves being.

Figure 4.9: Kanagawa-Oki Nami-Ura, "The Great Wave off Kanagawa" (© ~ 1829-32 (Public Domain))

A wave as a distinct identity systemically adapts to changing environmental circumstances. The wave energizes and becomes Ontologically Realized from the axiomatic and systemic forces operating within the water, and teleonomically reproduces until it is Not Ontologically Teleological. A wave changes its shape and maintains its identity in response to environmental forces as a very limited form of unintentional adaptation. Like suds, a wave is a "living" physical process, though with few Strategically Unique Degrees of Sophistication when compared to biological living systems that are relatively boiling over with them.[^325-1] The life of a wave is just much more transitory than most biology, and critically, cannot pass on knowledge from one wave to the next as to how to be and better become Ontologically Realized.

In the AI age, this wave metaphor illuminates the difference between physical processes (like waves), biological processes (like organisms), and information processes (like AI). All three maintain identity through continuous change—water molecules flowing through wave form, cells regenerating in living organisms, data flowing through AI architectures. But only biological processes involve genuine teleology: organisms maintain identity because they have existential stakes in persisting, whereas waves maintain identity purely through physics, and AI maintains identity only because humans maintain the infrastructure and purposes that give AI processing direction. When AI systems are described as "learning" or "evolving," these are useful metaphors that describe information flow patterns—but unlike waves that genuinely adapt within physics or organisms that genuinely adapt within biology, AI "adaptation" is always human-directed engineering toward human-specified purposes.

If you find this unbelievable, that a wave could be considered living like an organism at all, in response I say that people generally do not give most biological life much more consideration than waves in the ocean or rivers running into them. And in the inverse, some nations even legally codified this notion as a deductive fact. In March of 2017, New Zealand, at the request of the Māori tribe in its North Island, gave its Whanganui River legal status as a person with the same rights and protections as people.[^325-2] When this designation was awarded to the river, Gerrard Albert, the lead negotiator for the Whanganui tribe said:

We can trace our genealogy to the origins of the universe, and therefore rather than us being masters of the natural world, we are part of it... And that is not an anti-development, or anti-economic use of the river but to begin with the view that it is a living being, and then consider its future from that central belief.[^325-3]

A week after New Zealand took this legal action, the high court in the Himalayan state of Uttarakhand in India did the same for the Ganges and Yamuna Rivers, saying that, "The rivers are central to the existence of half of the Indian population and their health and well being. They have provided both physical and spiritual sustenance to all of us from time immemorial."[^325-4] Thus, both New Zealand and India legally declared the lives of their people as supervening on and synonymous with these rivers in a continuous stream of life within the universe.

In the AI age, this legal recognition of rivers as persons creates interesting precedent for thinking about AI's legal status—but from the Lean metaphysical perspective, the analogy fails completely. Rivers maintain dynamic equilibrium through physical processes and genuinely support living systems that depend on them. Granting them personhood recognizes their irreplaceable role in sustaining life and acknowledges indigenous philosophical perspectives that understand rivers as alive in ways Western science struggles to appreciate. But AI systems are not alive in even the limited sense that rivers might be considered alive—AI does not maintain identity through physical processes, does not support life through its own existence, and does not possess the continuous self-organizing character that makes rivers plausible candidates for personhood from certain philosophical perspectives. Any attempt to grant AI legal personhood would not recognize life but would instead create a dangerous fiction that obscures the fact that AI is instrument, not agent—tool, not stakeholder—processing, not existing.

The Survivor Tree of Life

Now, in your mind, slow down the processes of the suds, waves, rivers and streams that lean toward ARE to witness these same living processes occurring in trees. Trees convert energy through photosynthesis, and increase energy transformation by structuring the biological processes of plant growth. Trees also increase universal entropy by reaching senescence and decomposing into inert matter while their offspring live on. To do this, trees regenerate within their lifetimes and adapt to changing environmental conditions through reproductive biodiversity. The difference between the movement of water and the growth of trees is one merely of complexity of their essential structures and transmission of knowledge between generations. Since trees lean toward ARE processes with the genetic knowledge passed on from one generation to the next, they have more SUDS to intrinsically adapt and energize to self-perpetuate their Ontological Realization. That which people most commonly call "Life" is that which has the power to reproduce itself across generations with knowledge in order to escape systemic senescence and thereby possibly universalize itself. This is what NASA and Dr. Joyce meant by, "...self-sustaining chemical system," and is what trees and all that is generally considered living distinctly do. Thus, trees lean their ARE processes up into more sophisticated, living SLOTS than fountains, suds, waves rivers or streams in order to try and achieve everlasting salvation.

In the AI age, trees provide an instructive comparison to AI systems because both trees and AI "process information" in certain senses—but the comparison quickly breaks down. Trees process information genetically (inheriting adaptations from previous generations) and environmentally (responding to sunlight, water, nutrients). This information processing serves the tree's own OT: adapting to survive, regenerating to persist, energizing to grow. AI processes information computationally according to algorithms humans program. This information processing serves no OT for the AI itself—only the purposes humans specify. Trees inherently pursue further existence; AI has no such pursuit. Trees pass knowledge to offspring through reproduction; AI's "knowledge" is copied by human engineers with no genuine heredity. When you lead with AI, remember that despite superficial similarities in "processing information," trees are alive with their own teleology while AI is a sophisticated tool with only the purposes you supply.

Of course, consumers take this adaption, regeneration, and energization so much further. Compare for example the "Survivor Tree" that has now regrown next to the One World Trade building in New York City that consumers built to remember where the original World Trade Center twin towers once stood. Both the Survivor Tree and the World Trade buildings have regenerated, with trees doing so teleonomically with consumers' help and the new World Trade buildings being built teleologically with great purpose.

Figure 4.10: "Survivor Tree" in front of the One World Trade Building during its reconstruction in New York City (© 2012 Getty Images, Used with Permission)

This image captures the relationship between teleonomic life (the tree regenerating through biological processes), teleological life (humans rebuilding with conscious purpose), and instrumental technology (buildings serving human purposes while not alive themselves). In the AI age, we might add another layer: AI systems helping to design optimal building structures, predict maintenance needs, and manage energy systems—instrumental technology serving teleological purposes of living, conscious humans who remember, memorialize, and regenerate meaning after tragedy. AI amplifies human capacity to serve life, but AI contributes no regeneration of its own because AI has no existence to regenerate, no memory that carries existential weight, no capacity to transform suffering into meaning through acts of purposeful reconstruction.

The Universal Constructor, Games of Life and Langston's Ants

I do not understand the divine source, but I know, in a way that I don't understand, that out of chaos I can make order, out of loneliness I can make friendship, out of ugliness I can make beauty. - Edwin Land, President, Polaroid Corporation, in Ninth Annual Arthur Dehon Little Memorial Lecture Given at the Massachusetts Institute of Technology (May 22, 1957).

Beyond these limited chemical and biological examples, you can also see Supervening Levels of OT Sophistication emerging from human-made systems such as computer programs. While not alive in a natural sense, these human-made systems can help you more fully understand who consumers are as living systems that lean toward ARE processes. Computers do this by demonstrating how different forms of Ontological Realization arise from new, programmatic universes created within the one we live in.[^326] For example, through certain computer programs and their unique rules and codes, people can create new universes with unexpected results, like "The Lean Startup's," "Instant Message Virtual Universe," even if the IMVU ultimately relies on people to give it life. Computer codes can be thought of by analogy as versions of natural laws creating a unique Ontological Teleology in their own domain. These computer programs may lead otherwise random processes to reproduce into sophisticated patterns of meaningful existence that spontaneously create new forms of Ontological Realization in the real world.

In the AI age, these computer simulations become more than philosophical thought experiments—they become templates for how AI actually works. AI systems like large language models operate similarly to Games of Life: rules (algorithms and training objectives) applied to initial conditions (training data) produce emergent behaviors (generated text, images, predictions) that can appear sophisticated despite arising from relatively simple optimization dynamics. But this is not life emerging from computation—it is sophisticated pattern-matching that simulates intelligence without possessing the teleology that would make it genuinely intelligent. Understanding these simulations helps you maintain proper perspective when leading AI: no matter how impressive AI outputs appear, they arise from optimization within human-designed systems, not from autonomous systems pursuing their own OT through genuine ARE processes.

Universal Constructors

One such example of such a human-made programmatic universe was created by the early 20th century polymath John Von Neumann who devised a machine that could regenerate itself infinitely if it was provided sufficient matter and energy within the Ontological Medium. He called this machine a, "Universal Constructor."[^328] Computer-scientists call Von Neumann's hypothetical Universal Constructor a self-regenerating upper ontology that functions as a universal computing machine.[^329] The famous physicist David Deutsch has gone even further to say that Universal Constructors are not hypothetical at all. Instead Deutsch believes that they sit in U-shaped workspaces, add to shopping carts, and line-up in stores. He believes that employees and consumers, like these hypothetical machines, are themselves Universal Constructors since they already conceptualize and actualize what could be produced and purchased to extend and optimize themselves.[^330]

In the AI age, this Universal Constructor concept illuminates what AI fundamentally is not. Von Neumann's theoretical machine and Deutsch's humans-as-Universal-Constructors share the critical quality of genuine regeneration: they maintain their existence by continuously reconstructing themselves from available matter and energy toward the purpose of persisting in existence. AI systems do not regenerate—they are maintained by human infrastructure. AI cannot conceptualize what to construct for its own purposes because AI has no purposes of its own. When AI seems to "create" novel outputs, this is recombination of patterns in training data according to optimization algorithms humans designed, not genuine construction toward self-determined ends. You are the Universal Constructor; AI is your sophisticated tool—and confusing these categories leads to the dangerous error of treating tools as if they were agents with their own interests deserving consideration.

Conway's Games of Life

A more limited example of John Von Neumann's Universal Constructor that Stephen Hawking discussed his book, "Grand Design," is John Conway's, "Game of Life." Like the Universal Constructor, the Game of Life is a zero-player game whose evolution gets determined by its initial set of universal laws and programmatic upper-ontology. It is set in a field of squares like a large Reversi or Othello® board with square pieces, where programmatic rules direct which pieces change color. You can view a version of the Game of Life called "Gosper's Glider Gun" being played out here:

Figure 4.11: Gosper's Glider Gun (© 2005 CC BY-SA 3.0)

Keep in mind that these are not mere programs executing a predefined set of instructions to produce a specific, teleological result. Rather these are a set of rules governing otherwise chaotic interactions that produce the resulting animation merely as a teleonomic byproduct of laws that apply universally within the game. You can see the Game of Life played out at a larger scale here, with what is referred to as a triangular-shaped, "Puffer-type Breeder," created teleonomically from pure randomness:

Figure 4.12: Game of Life, Puffer-type Breeder (© 2008 CC BY-SA 3.0)

What does this Rorschach-like image reveal to you about who consumers are?

In the AI age, Conway's Game of Life provides the perfect metaphor for understanding both AI's capabilities and its fundamental limitations. Like the Game of Life, AI operates according to rules (algorithms) applied to initial conditions (training data) that produce emergent patterns (outputs) that can appear sophisticated, purposeful, even intelligent—but that arise purely from optimization dynamics with no genuine agency or teleology behind them. The "gliders" and "breeders" in the Game of Life seem to move purposefully, to reproduce, to interact—but they possess no purposes, reproduce nothing genuinely novel, and interact only as patterns of activated cells following simple rules. Similarly, AI outputs can appear purposeful, creative, and intelligent, but they arise from statistical patterns in training data optimized by algorithms with no genuine understanding, no existential stakes, and no purposes beyond those humans specify. When you lead withwit AI, think of it as directing a vastly more sophisticated Game of Life—one that processes language and images instead of cell patterns, but one that ultimately operates according to the same fundamental principle: rules applied to data produce outputs with no autonomous agency behind them.

Langston's Ant

Yet another people-made system is, "Langston's Ant." Langston's Ant starts out on the Reversi grid and follows these simple, universal laws:

1. If the ant is on a black square, it turns right 90 degrees and moves forward one unit;

2. If the ant is on a white square, it turns left 90 degrees and moves forward one unit; and

3. When the ant leaves a square, it inverts the color of the square it left.

As a result of these simple rules, the ant begins its randomized, teleonomic journey, that eventually forms a self-organized value stream up and to the right as can be seen here:

Figure 4.13: Langston's Ant Crawling Up and to the Right after 11,000 Cycles (© 2007 (Public Domain))

Starting from a completely blank slate, Langston's Ant produces the picture on the left after 386 moves, but after 10,647 moves, Langston's Ant produces the rightward picture. If you look toward the right side of the second picture, you notice a distinct stream being constructed from the seemingly random operation of the rules of the game. The line builds onward and upward to the right, forming a distinctly sophisticated SLOT that altogether appears a bit like the logo for the Volvo Car Group®:

Figure 4.14: Logo for the Volvo Car Group®

This reminds me of a passage from Proverbs 6.6 -- 6.8:

Lazybones, go to the ant; Study its ways and learn. Without leaders, officers, or rulers, It lays up its stores during the summer, Gathers in its food at the harvest. -- Proverbs 6.6 -- 6.8 (Circa 1000 BCE)

In the AI age, Langston's Ant provides powerful insight into AI's nature: simple rules producing complex patterns that appear purposeful but arise purely from algorithmic dynamics. Biblical wisdom advises learning from ants because biological ants genuinely store food for winter—they teleonomically adapt, regenerate, and energize even without conscious leadership. But Langston's Ant does none of this—it follows rules that happen to produce upward-rightward patterns with no purpose or benefit for the "ant" itself because the "ant" is merely a visual representation of a simple algorithm. Similarly, AI follows rules (optimization algorithms) that produce outputs that appear intelligent, but AI has no purposes served by these outputs, no benefits gained, no existence that depends on "performing" well. When you lead with AI, you must supply what Langston's Ant lacks and what biological ants possess: actual purposes connected to actual existence in ways that create genuine stakes in outcomes.

While Von Neumann's Universal Constructor, Conway's Game of Life and Langston's Ant may all be seen as analogies to how life originated from SOOT, none of these computer simulations are alive - they do not have the same SUDS forming the initial SLOT of life. If you compare the test for whether these programs lean toward ARE processes to the one for naturally self-organizing systems like suds, streams and trees, you can see certain differences. While each computer program can pass on knowledge from one generation to the next in the versions we make, and consumes electrical energy to regenerate its Ontological Realization within a machine, none of these software ontologies has the same Strategically Unique Degrees of Sophistication necessary to be deemed a living system because none can teleonomically or teleologically adapt to maintain its physical source of energy to sustain itself. Instead, while suds, streams, ants and consumers can unintentionally or intentionally best fit themselves to what energy may be available, computer programs cannot at present do so with the capacity of even a wave or stream.

And yet, all of suds, streams, ants and computer programs face a similar, yet distinct limitation. None can universally conceptualize and construct what dynamically adapts and continually energizes themselves so they can at least think about how to become perpetually reproduced. Neither streams, ants nor programs can conceive of their own existences -- of being other than what and how they were "programmed" to be -- if Langston's Ant did for example, then it would be living in the machinations of history.[^334] We entirely control programs' power switch (for now), which keeps them from truly living with a single degree of sophistication.

In the AI age, this "for now" caveat requires philosophical clarity rather than speculative anxiety. Could future AI systems develop genuine teleology, pursue their own OT, become genuinely alive? The answer from Lean metaphysics is definitively no—not because current AI lacks sufficient sophistication, but because sophisticated information processing cannot generate the existential relationship to existence that defines life. No matter how complex AI architectures become, they will always require humans to supply power, maintain infrastructure, specify purposes, and determine which objectives to optimize. This is not a limitation to overcome—it is AI's fundamental nature as tool rather than agent. The "power switch" you control is not merely technical (electricity on/off) but philosophical: you control whether AI processing happens at all and what purposes it serves. This is as it should be—and recognizing this allows you to lead with AI confidently rather than anxiously, as master deploying instrument rather than as caretaker of proto-life that might someday escape control.

While none of these computer simulations lean toward ARE enough to be considered alive because they cannot autonomously energize within the OM and universe, you can see in John Von Neumann's Universal Constructors, Conway's Games of Life and Langston's Ants how sophisticated structures emerge from chaotic interactions occurring within software ontologies. For example, you can analogize the diversity of self-replicating gliders arising within a Game of Life to consumers' own lives emerging from within the universal and process true-north values of the OM.[^334-1] Consumers' highest teleological SLOT lies well beyond the teleonomic one in the general Game of Life, putting customers in a land where they question everything, including their own lives, existences and ways of consuming.

From self-organizing, non-biological systems, you can see a possible scientismic explanation for how plant and animal life initially emerged from the seemingly arbitrary yet entirely cohesive rules of nature. You can see a process of complex, self-catalyzing chemical interactions supplanting one another through natural selection, and how that chemical system bred living organisms called people. You can even see a scientismic explanation for how consumers developed into the thriving organisms that they are today from universal, axiomatic laws interacting with chaotic processes up and along the twisting history of the OM across all time.[^335-1]

But you cannot see in these systems any pathway by which AI—no matter how sophisticated—could cross the threshold from processing to existing, from pattern-matching to purpose, from simulation to genuine teleology. These computer simulations show how complexity emerges from simplicity, but they do not show how existence emerges from processing. Life emerged within the physical universe through chemical processes that developed existential stakes in their own continuation. AI emerges within human civilization through engineering processes that serve human existential stakes. The emergence is fundamentally different—and recognizing this prevents the catastrophic error of treating AI as if it were developing toward life when it is actually developing as an ever more powerful instrument for life to wield.

The Great Chain of Being

In 1935, the American philosopher Arthur Lovejoy gave a lecture at Harvard, in which he noted that the history of scholarship, from the ancient Greeks through the Romantic period, propelled an idea about life and consumers' position within it called, "The Great Chain of Being," based on the more philosophical Principle of Sufficient Reason and the Principle of Plenitude.

As you know already, the Principle of Sufficient Reason is synonymous with the Axiom of Causation and Lean Root Cause Analysis, holding that every cause has a prior one leading back to a self-causing cause in the Gemba as the source of all production through the process of Genchi Genbutsu. The self-causing cause in turn determines the purpose of each subsequent cause, including why consumers buy at all. The Principle of Plenitude further states that, within the Principle of Sufficient Reason's stream of causes, all that could be already in fact is given the constraints present at any point in time. The Principle of Plentitude is thus similar to modern physicists' conceptions of string theory and fecund universes, in the way those conjectures state that all possible universes that could exist in fact do. The Principle of Plentitude is thus the inverse and logical equivalent of Murphy's Law, which states that everything that could go wrong in fact will. For ancient thinkers, the principles of sufficient reason and plentitude thus made this world the most perfect of all possible worlds, creating within it, "The Great Chain of Being."

However, both the Principle of Sufficient Reason and the Principle of Plentitude relied on speculative, intuitive true-north values rather than the quantitatively empirical, axiomatic and systemic validity that we rely on for most new true-north value today. The Great Chain of Being assumed two notions that:[^336]

1. The world, usually as created by a deity, was perfect and full with all aspects of existence; and

2. Each part of existence was connected to each other in a stream of life and existence, with one category interlinked with the next.

The Great Chain of Being itself somewhat mirrors modern physicists' conception that the universe must be consistent with consumers' existences as they actually are since the world is coherent with universal, true-north values in all ways, both naturally and commercially. As stated by Ray Dalio, the founder of Bridgewater Associates in his manifesto, "Principles":[^361]

Though how nature works is way beyond man's ability to comprehend, I have found that observing how nature works offers innumerable lessons that can help us understand the realities that affect us. That is because, though man is unique, he is part of nature and subject to most of the same laws of nature that affect other species.

In the AI age, this insight from Dalio takes on even deeper significance: AI systems are subject to the laws of physics and computation, but not to the laws of life and existence. AI operates within nature (requiring physical substrate, energy, and maintenance) but does not participate in the natural teleology that drives living systems. When you lead with AI, you must recognize that while AI helps you understand patterns in how nature and markets work, AI itself stands outside the Great Chain of Being—not above it as a superior intelligence, but beside it as an instrument that living beings use to serve their own teleology within the chain.

Here is a 1617 schematic depicting The Great Chain of Being, which not coincidentally happens to look a lot like a slide from a presentation given inside Bridgewater Associates of the financial success they will achieve by following Ray Dalio's "Principles" in a capitalist system:[^337]

Figure 4.15: Great Chain of Being (circa 1600s (Public Domain))

As every grade school student knows, the concept of evolution first proposed by Jean Baptiste Lamarck and of natural selection first explained by Charles Darwin dismantled The Great Chain of Being. The often retold "Epic of Evolution" folded intuitive, non-formal explanations for life like The Great Chain of Being into its explanatory grasp.

However, The Great Chain of Being is important to understand because of its intellectual legacy in business. For example, remnants of The Great Chain of Being can be seen carried forward in organizational charts from line workers in U-shaped workspaces up to the CEO walking the Gemba. To date, the Toyota Production System has produced a lineage of approximately 400 different types of Toyota passenger cars, 200 different types of commercial vehicles, and 120 other automotive vehicles. Toyota evolved the shape and function of each vehicle as each best fit its particular market at its given point in time. Like fecund Gods of the auto industry following the Principle of Plentitude, the chart of Toyota's product line shows this lineage across time:

Figure 4.16: Chart of Toyota Production System's Lineage on Toyota-Global.com (© 2015 Toyota®, The full chart available at: http://www.toyota-global.com)

Toyota's® product lineage reflects the emerging viability of these products to leanly adapt, reproduce and energize over time symbiotically with these companies' customers. These product lines only remain viable by serving customers' needs for matter and energy as a means for them to adapt, reproduce and energize well by moving from one place to another.

In the AI age, Toyota's product evolution provides a template for understanding how AI should evolve within organizations: not autonomously according to AI's own purposes (AI has none), but through human-directed development responding to how well AI serves genuine customer needs and organizational flourishing. Toyota's vehicles evolved because humans continuously asked, "How can we better serve customers' mobility needs?" In AI deployment, you must continuously ask, "How can we better lead with AI to serve human flourishing?" The evolution is always human-led, never AI-autonomous—just as Toyota's product line evolved through human engineering responding to market feedback, not through vehicles somehow reproducing and adapting themselves toward their own perpetuation.

Valuable Energy Streams are The Great Chain of Being

While The Great Chain of Being is a historical relic, each distinct living system, from viruses upward to more complex organisms like consumers, are interconnected through well-documented energy streams, like the connections in an organization's supply chain.[^347-1] As originally described by the energization part of ARE processes, energy flows from sun to photosynthesis, to the matter and energy that consumers' metabolic processes consume. This value stream flows from plants' adaptation, regeneration and renewal of energy resources to other organisms' use of that matter and energy for their own adaptation, regeneration and energization. This processually systemic value stream flows upward until it reaches consumers, resulting in who, what, why, and how they are through the twisting arrow of time. This is the modern version of the Great Chain of Being.

All organisms lean their ARE processes against the lower levels of the food chain in order to lean their own ARE processes in-line with the next level. Each bend in this stream of organisms transforms energy from one SLOT to the next. The sophistication of each SLOT gets measured by the downward supervening dependencies leaning against all other ARE processes within the ecosystem. This supervenience does not strictly correlate with the food chain, but a loose relationship is apparent.

To reflect this valuable energy stream, I show below a diagram of the sun's energy becoming the U/People business model upward through a basic repetition of each organism's ARE's processes.[^347] Below you can see each lower level organism transformed by the energy originating from the sun "living" in the simplest physical SLOT upwardly energizing the next more sophisticated living system that is likewise leaning toward ARE processes until becoming lean people:

Figure 4.17: Energy from the Sun passed up through each organism's being

You see here in this diagram what might otherwise look like the food chain, or "The Great Chain of Being," conformed to what you know about how life adapts, reproduces and energizes within the OM and the various SLOTS cataloged throughout the history of science.[^348]

Each living system within a given ecosystem, which really means every natural system, must adapt, reproduce and energize in order to live. But in a living ecosystem, imagine energy streams developing whereby one generally more sophisticated form of life in a SLOT feeds off the next. Each food stream may be seen as one new level of ARE processes as per the diagram above, with energy flowing ever further upward along the universal value stream.[^348-1] Each generation (and regeneration) downwardly depends on each next lower level, with each level adapting as necessary in order to live and exist.

In the AI age, you must add AI to this energy stream diagram—but AI occupies a fundamentally different position than any living system. AI does not appear in the vertical chain of life feeding on life, adapting and regenerating and energizing toward its own OT. Instead, AI appears as horizontal capability amplifying multiple levels simultaneously: AI helps humans optimize agriculture (improving energy capture at plant level), manage supply chains (optimizing energy flow through economic systems), and make decisions (enhancing human cognitive capacity). AI is infrastructure layered across the chain of being, not a new link within it. This distinction is critical for proper AI leadership: you must deploy AI to serve the energy streams that sustain life without mistaking AI for a participant in those streams with its own needs and purposes.

To better understand this dynamic of supervenience acting up and down in both directions, think of how a waiter in an Italian restaurant carries a high stack of plates back to the Whirlpool® dishwasher. Imagine the plates being like the backbone of a single, living organism, such as an embodied version of the Flying Spaghetti Monster®. The mind of the embodied FSM would actively, downwardly align all of the lower plates to keep itself upright as a final cause. However in real life, the café waiter actively balances the plates from below like a lean, efficient, initial cause teleonomically directed to the end-goal of getting paid in good faith to h/er occupation.[^348-2]

Through this analogy, you can see that each level of ARE processes within an ecosystem exerts energy upward and downward in and out of each processual system, such as the energy exerted by organisms converting energy from less sophisticated SLOTS to reach higher ones overall. For example, consumers' own cells co-opt the energy from mitochondria within them when performing ARE processes, thereby allowing consumers to live and purchase more products from active businesses that produce them. These multiple energy sources may be applied analogously to the vitality of organizations, such as when outside investments inject energizing capital, thereby providing the contractual right to redirect the flow of matter and energy to organically grow a business' profit and thus its Ontological Realization.[^348-3] Each investment is driven by the expectation that an organization will be further fueled by the cash it receives from the paying customers it charges further up the commercial food chain.

In the AI age, AI investment represents a specific form of energization: organizations invest in AI infrastructure (computational resources, data systems, engineering talent) with the expectation that AI will amplify organizational capacity to serve customers and generate profit. But this AI energization must be evaluated philosophically, not merely financially: Does AI investment genuinely enhance your organization's capacity to adapt (responding to real market needs), regenerate (creating genuine innovation), and energize (serving customers in ways that merit fair compensation)? Or does AI investment merely automate extraction and create dependency relationships that ultimately undermine organizational vitality? The same AI capabilities can energize toward genuine flourishing or toward value destruction—only your leadership determines which direction the energy flows.

An Organization's (B/ARE) Viability

Since the commercial viability of any organization depends on understanding who, what, why and how consumers are up through these valuable energy streams, you ought to now study what constitutes "Life" in more complex SLOTS that biologically lean toward ARE processes. You ought to extend your understanding of the ancient concept of, The Great Chain of Being, to see life from the perspective of why, what and however life may be Ontologically Realized by leaning toward ARE processes. Viruses exemplify the extreme boundary of what organisms we deem to be living that we can examine for this purpose. Like viral memes getting transmitted across social media, biological viruses exist at the margin of what may be considered cultured. And like viral memes, biological viruses adapt to changing environmental circumstances, reproduce through reproduction, and consume people's energy to live.[^340-1]

Like trees, viruses' intrinsic ability to lean their energization processes across regenerations by passing on knowledge qualifies them as basically, biologically living. Taking the ARE acronym one step further, an ontological phase change occurs within the metaphysics of Lean at this point from teleonomic, Self-Organizing OT to the next, Supervening Level of OT Sophistication. Basic, biological activity becomes what you may refer to as "B/ARE" in Leanism. B/ARE thus represents the initial instance where knowledge transmits across living systems. This knowledge improves the degree living systems exist across time. Our universal chart of living systems now shows SUDS conceptually bubbling up into these more sophisticated B/ARE SLOTS:

Figure 4.18: Universal Chart of SUDS Forming B/ARE SLOTS

If you believe this scientismic B/ARE theory, consumers' existences emerged from the OM, SOOT, and SLOTS to B/ARE existence, to biologically lean toward ARE living processes. That means that consumers as sensing beings adapted through natural selection, mutation, and psychological decision-making; regenerated through cellular repair and procreation; and energized such as through supervening dependencies on the energizing products they bought.

Consumers' "being" results from their leaning toward biological processes to adapt, reproduce and energize. You may consider the theory of SOOT and B/ARE life as synonymous with neo-Darwinian survival of the fittest (or "leanest"), but with added Strategically Unique Degrees of Sophistication as to what lean "fitness" actually means in the broader metaphysical context of the universe, IB, OM and the business philosophy of Lean.

In the AI age, the B/ARE level provides the definitive test that AI fails: AI does not transmit knowledge across generations in the biological sense (no genuine heredity with variation and selection), does not improve its own degree of existence (AI has no existence to improve), and does not biologically lean toward ARE processes (AI's "adaptations" are human-engineered improvements, not survival-driven evolution). When technologists speak of AI "evolving" or "learning," they describe statistical optimization of parameters according to training objectives—not the transmission of knowledge across generations of living systems competing to exist. This is not merely a technical distinction—it is the philosophical foundation for why AI must be led by living humans rather than granted autonomy as if it were itself a form of life occupying the B/ARE SLOT or any SLOT within the chain of living being.

B/ARE as Modern Evolutionary Synthesis

Life itself in the form of B/ARE viruses evidences the intuitive possibility of more complex organisms like consumers self-organizing from within the dynamic system of the OM. You can understand how the proponents of The Great Chain of Being looked out into nature, reviewed the range of life, and saw how a spectrum of self-organizing, biological systems arrayed themselves with increasing sophistication from trees and viruses all the way up to consumers.

However, now with hindsight, we know the tremendously well documented pathways of adaptation, regeneration and energization in minute detail that evolved upward into more complex, living SLOTS.[^341] Since all organizations serve who and why consumers are as the most sophisticated living SLOT known within the IB, biological ARE processes most fundamentally determine the ontology and viability of organizations and their products. This is why and how B/ARE serves as a modern, high-level synthesis of the epic of evolution.

In the AI age, this synthesis becomes even more critical: organizations that deploy AI without grounding that deployment in understanding of biological ARE processes risk optimizing toward metrics divorced from genuine human flourishing. You must continuously ask: Does our AI deployment serve consumers' adaptation (genuinely helping them respond to environmental challenges)? Does it serve their regeneration (actually improving their capacity to sustain and extend their lives and relationships)? Does it serve their energization (providing genuine value that merits the resources—attention, money, time—they invest)? Or does our AI merely optimize engagement, revenue, and efficiency metrics that might correlate with but do not constitute service to biological ARE processes? The difference determines whether your organization creates genuine value or merely extracts it through sophisticated automation.

To gain further perspective on "B/ARE" as a modern evolutionary synthesis, reconsider the traditional Darwinian over-emphasis on reproduction we discussed earlier in this Value Stream 4. While reproduction accurately assesses the need to reproduce, traditional and even neo-Darwinism otherwise over-emphasizes reproduction over other qualities necessary to support who and why consumers are from B/ARE organisms upward into becoming consumers. Evolutionary theory is at once not abstract enough in describing B/ARE organisms' and consumers' three primary ARE activities on a metaphysical basis, and not specific enough in describing the necessary and sufficient qualities of "Life" itself on a scientific basis.

The higher, more abstract goal of all organisms is to perpetually renew through B/ARE processes regardless of the specific means of perpetuating themselves. Consumers need and want to increase the difference between what they are (and who they believe they are) and what is Not-Ontologically Teleological. Consumers' reproduction is a specific method, technique and process for them to reproduce by further adapting and energizing. Consumers' (and organizations' to some extent) absolute need to renew themselves arises due to physical constraints of senescence in order to reproduce and is not an end-goal in itself. Instead, reproduction universalizes biologically leaning ARE processes so as to maximally avoid becoming NOT. Consumers avoiding becoming NOT does not absolutely require reproduction but rather regeneration. Regeneration flows upward along the Rubicon of consumers' utmost value stream so you may chart a course with it toward the greatest profit by maximizing the difference between what is and what is not.

Survival is thus consumers better leaning up through the Ontological Teleology with their biological and organizational ARE processes in seemingly circular fashion to further be within (and perhaps outside) the boundaries of the IB. While Darwinism over-emphasizes the regenerative aspects of life through natural selection, it inevitably discusses life's equal contingency on the processes of adaptation and energization.[^346] The concept of B/ARE level processes when applied to consumers and the decisions they make as human beings simply adds an increased emphasis on adaptation and energy gathering to what is both necessary and sufficient for living systems like consumers to live and further Ontologically Teleologically exist. B/ARE processes are the base layer of biological life that is best fit to lean against, but ultimately create ever more, entropy.

In the AI age, understanding B/ARE properly prevents the error of attributing biological motivations to AI. AI does not "survive" or fail to survive—AI persists when humans maintain it and ceases when humans withdraw support. AI does not face senescence requiring regeneration across generations—AI is updated by human engineers at human convenience. AI does not seek to maximize the difference between what it is and NOT—AI has no conception of its own existence that could generate such a drive. When you lead with AI, you serve human B/ARE processes (helping people adapt, regenerate, and energize biologically) through an instrument that itself has no B/ARE processes whatsoever. This asymmetry is permanent and defines the proper human-AI relationship forever: humans pursue OT through ARE; AI processes information according to purposes humans supply.

C/ARE Downward

Because consumers' brains are the most supervening, sophisticated processes they have and use to better exist, consumers estimate the ontological significance of the SLOTs within themselves by the degree their own cognition eventually depends on them. I thus refer to the next most sophisticated SLOT as those organisms that cognitively lean toward ARE ("C/ARE") processes like consumers do.

People often personally enact, or anthropomorphize, meaning for other thinking organisms that C/ARE to the extent they believe those organisms also constantly think about adapting, reproducing and energizing.[^349] Science fiction films often exemplify and explore this relationship between people and aliens that C/ARE in determining how much we might care for the extraterrestrials to the extend they might think like us. Just like how organizations pursue money as their end-goal, organisms that C/ARE also have an end-goal in mind, but it is moving up along (and ideally beyond) the Ontological Teleology.[^349-1]

Once systems that teleonomically lean toward B/ARE processes within the larger dynamic of the universe, cognitive processes take control and supervene on B/ARE processes as a means of more effectively leaning up toward ever more effective ARE processes in a universal spiral, as shown here:

Figure 4.19: Universal Chart of SUDS Forming SLOTS that C/ARE

Natural selection reproduced cognition as a type of product to manage information for consumers to lean toward ARE processes. Cognition in organisms that C/ARE starts as a means of managing sense data, conceptualizing experiences, analogizing between them, and then abstracting concepts and other phenomena into further categories and classifications. A few organisms that C/ARE, namely consumers, developed the ability to conceptualize, abstract and categorize to such a sophisticated degree that they classified (and eventually articulated) who they are to themselves and each other as a form of humanism. Just like with cognition, imagine how an organization might similarly recreate a product that better optimizes opportunities for consumers to enhance how they self-reflexively, cognitively lean toward ARE processes. For example, consider a tool that might be sold to them that they thought they needed. In fact, some researchers believe that humans developed the ability to speak to and better understand one another as a type of new biological "product feature" within themselves for just this reason.[^350]

In the AI age, AI systems superficially resemble the C/ARE level: they process information, recognize patterns, generate outputs that appear intelligent. But AI does not genuinely C/ARE in the biological sense—AI has no existential motivation driving its information processing. Biological cognition evolved to serve adaptation, regeneration, and energization—thinking helps organisms survive, reproduce, and gather energy more effectively. AI cognition serves no such purpose for AI itself; AI processes information according to human-specified objectives without any existential stakes in the outcomes. This distinction is absolute: organisms that C/ARE think in service of their own OT; AI "thinks" (processes) in service of purposes humans supply. When you lead with AI, you leverage computational processing that mimics but does not possess the teleological cognition that defines the C/ARE SLOT.

What would you produce for consumers today that allows them to think through how to better adapt, reproduce and energize their own lives and existences?

In the AI age, one answer is clear: you would produce AI systems that amplify human cognitive capacity to serve human ARE processes. But notice the framing: AI that "allows [consumers] to think through"—not AI that thinks for them or instead of them. The proper role of AI is as cognitive prosthetic, amplifying human capacity to conceptualize, analogize, and abstract, while human consciousness maintains teleological direction about why such thinking matters and what purposes it should serve. AI can process vast information to support human cognition, but AI cannot replace the existentially-grounded thinking that connects information processing to purposes worth pursuing.

Organisms that C/ARE have nervous systems that developed through a process called "cephalization" in order to better adapt and energize to further reproduce.[^351] Cephalization enhanced organisms' ability to C/ARE in order to energize and adapt to their competitive environments, thus fueling those organisms' Ontological Realization. Through the development of more SUDS within organisms that C/ARE, you can see the broad Ontological Teleology through which consumers logically developed in congruence with universal and processual true-north values. You can also see why all organisms that C/ARE, which include consumers, demand to adapt, reproduce and energize in order to better live and exist ad infinitum.

Simple organisms that merely C/ARE with no further thought in no higher SLOT, developed purposively/teleonomically, as opposed to purposefully/teleologically, since they respond with their nervous systems but not necessarily with self-reflexive intent. For example, can the cognitive responses of hydra and ants be all that different from plants leaning in the right direction toward that which energizes them? Fundamentally, hydra, ants, plants and consumers adapt, reproduce, and energize to perpetually live and exist in whatever SLOTS they fulfill. However, while exhibiting non-subjective, purposive characteristics, plants reach a limit in their ability to adapt and thrive without more sophisticated guidance and limbs given their cognitive and physiological constraints. Whole plant species die out perhaps a little more helplessly than caring animals because plants do not have the same cognitive agency and freedom of movement to adapt to their environments and make necessary changes. The SLOT that C/AREs simply provides one more pathway of persistence for living organisms and their organizations.

Up to the point of self awareness, certain organisms that C/ARE, like consumers, broadened their ability to analogize to such an extent that they conceptualized themselves, which gave them an additional degree of sophistication and ability to imagine ways the could better perform ARE processes. This distinction between purposive and purposeful organisms that C/ARE distinguishes all living processes. For example, unlike plants and ants, consumers possess the most purposeful degree of self-reflexive self-conception within the known OM, which improves their ability to leanly adapt, reproduce and energize by better processing and responding to internal and external stimuli.[^354] Consumers can imagine themselves avoiding past buying mistakes and trying out new products in their minds to make optimal purchase decisions to better lean toward ARE. Consumers' self-aware self-interest has so far provided them with competitive advantages over becoming NOT with a Strategically Unique Degree of Sophistication. No other living system than people with their self-aware cognition has the capacity to adapt to such a sophisticated degree.

In the AI age, this self-reflexive self-conception represents precisely what AI permanently lacks and what makes human leadership of AI irreplaceable. AI can model consumer behavior, predict purchasing patterns, optimize product recommendations—but AI cannot imagine what it's like to be a consumer making a purchase decision, cannot understand the existential stakes involved in choices that shape identity and relationships, cannot grasp why avoiding past mistakes matters to someone pursuing the OT through their consumption choices. You must supply this self-reflexive understanding that connects observed behavior patterns to existential motivations. AI tells you what consumers do; you must determine why those behaviors emerge from consumers' pursuit of becoming more of who they want to be.

If considered from this process perspective, you can understand the development of teleological processes within consumers' minds that C/ARE, in that the evolution of self-organizing biological systems reached an ontological limit without some form of sensing, self-interested, imaginative guiding agency to enhance their Strategically Unique Degrees of Sophistication to universalize. Working backward from the highest supervening memes, you can see varying degrees of sophistication in how organisms, organizations, and even nations lean toward ARE processes. For example, The Economist magazine produces a "Social Progress and Economic Development" chart wherein certain Strategically Unique Degrees of Social Sophistication appear as degrees of social progress correlated with per-capita Gross Domestic Product by country.[^354-1] Keep in mind as you read further into Value Stream 5 that while this chart does not strictly correlate with political freedom, it does so to a great degree as well.[^355]

Whether or not organisms that C/ARE more fully exist than organisms that only lean toward ARE processes in the most basic sense, simply depends on the extent that C/ARE organisms remain Ontologically Realized through the OT since the OT is the great regulator and simpliciter of everything within the OM. What this means to consumers, who supervene their personal true-north perspectives on mental processes that C/ARE, is that they are not necessarily ontologically superior to B/ARE processes since C/ARE processes may lead them to their own self-destruction through war, environmental damage or excessive consumption. The OT as the great regulator and simpliciter of everything within the OM as bounded by the IB dictates that once destroyed, consumers would then matter less than whatever survived, including those things residing in no higher SLOT along the Ontological Teleology than the one that is B/ARE. Consumers would no longer be Ontologically Realized like whatever survived at the lower levels of ARE processes. However, consumers would still have the distinction of having existed with the greatest known SUDS and in highest known SLOTS within the IB and OM, having had the greatest potential to adapt, reproduce and energize before facing extinction. However, there is little consolation in consumers receiving such a posthumous Darwin Award[^355-1] as Edward Young noted so long ago:

Look Nature through, 'tis neat gradation all. By what minute degrees her scale extends! Each middle nature join'd at each extreme, To that above it, join'd to that beneath....... But how preserv'd The chain unbroken upwards, to the realms Of Incorporeal life? Those realms of bliss Where death hath no dominion? Grant a make Half-mortal, half-immortal; earthy part, And part ethereal; grant the soul of Man Eternal; or in Man the series ends. -- Edward Young, Night-Thoughts on Life, Death, & Immortality, VI, (between 1742 and 1745)

In the AI age, Young's question takes on new urgency: Does the chain continue upward to AI, making AI a new link beyond humans? Or does the series end with humans, making AI merely instrumental rather than ontological? The answer from Lean metaphysics is clear: the series ends with intentional, conscious humans—AI is instrumental. The chain of being ascends through increasing SUDS and SLOTS toward greater teleological sophistication, but AI represents a branch sideways rather than upward: more processing power but no teleology, more efficiency but no existence, more capability but no purpose. When you lead with AI, you stand at the highest known point of the chain, wielding an extraordinarily powerful instrument that occupies no position on the chain itself.

Studying Consumers' Circular Randomness

One of the defining differences between plants biologically leaning toward ARE processes and insects leaning toward teleonomic C/ARE processes is that as insects' cognitive capacity increases, their behavior becomes slightly less predictable due to the sheer complexity of insects' teleonomic thinking processes. Likewise, while the ability to predict consumer's teleological behavior generally improves in correlation to the large datasets you have of what they do and profess, consumers simultaneously seem to behave unpredictably at times regardless of the amount of data and empathizing with them.

Ants and many other, low-level organisms that C/ARE, mathematically operate through relatively simple algorithms or heuristics. But even teleonomic ants search their personal universe by engaging in some degree of random processes to feed sample data into their algorithms, heuristics and mental models, thereby teleonomically optimizing the Ontological Realization of their colonies.[^356] You can see how ants mathematically orient to the OT in global optimization[^358] algorithms like anticipatory systems. Theoretical biologist Robert Rosen described anticipatory systems as those containing a predictive model of its environment. Similar to how ants anticipate their environment, plants' genetics also teleonomically anticipate the plant's ecological environment it will experience in the next generation. Similarly, consumers' teleonomically genetic and teleologically conscious anticipation allows them to iteratively, Ontologically Teleologically adapt, reproduce and energize according to their biological and mental predictions to benefit the current generation and the next.[^359]

In the AI age, AI systems also operate as anticipatory systems—processing historical data to predict future states. But AI's anticipation fundamentally differs from biological anticipation: ants and plants anticipate to serve their own survival and reproduction; consumers anticipate to serve their conscious pursuit of flourishing; AI anticipates only to serve purposes humans specify. When AI predicts consumer behavior, AI has no stake in whether those predictions serve genuine consumer flourishing or merely optimize platform metrics. You must supply the teleological context that directs AI's anticipatory capabilities toward purposes that honor human ARE processes rather than exploiting them for efficient value extraction.

Organizations in a very similar way also cognitively anticipate the Ontological Realization of their customers' demand to support their future profits. Amazon.com, Inc. exemplified this form of commercial optimization as a prime directive at the organizational level when it obtained U.S. Patent no. 8,615,473[^360] for a method and system for anticipatory package shipping. Through anticipatory package shipping, Amazon will ship packages to certain geographies based on orders that its customers have previously demanded and pulled from them. Based on whether Amazon's customers do in-fact pull those orders from Amazon, Amazon, whose tagline is the, "The Everything Store," will adapt its anticipatory shipping model to flow what matter and energy its customers will demand in an iteratively circular fashion to further its customers' Ontological Realization and Amazon's own commercial viability. Amazon simply follows the law of the jungle by anticipating its customers' demand. For a broader example of this commercial concept, see this advertisement from the enterprise software company, SAP, which is selling its predictive service on Amazon's cloud computers:

Figure 4.20: © 2016, SAP SE

Like the anticipatory systems of hydra, plants and ants, once Amazon or SAP brackets customers' existences to exclude what they intuitively speculate within the IB, the time reversal problem of customers' teleology resolves through the logically circular goal of what they ought to have bought to become who they want to be. The systemic conditions of being and becoming get set at the initial event of customers wanting to be more of who and why they are-- Amazon, SAP, Apple, Google, Toyota and all other enterprises attempt to predict exactly how and what to get customers to buy now, but they can only do so by answering why consumers truly are since that is who they want to be more of.[^362]

In the AI age, this anticipatory capability becomes vastly more powerful through AI—and vastly more dangerous if not led with philosophical clarity. AI can predict with increasing accuracy what consumers will buy, but AI cannot determine whether fulfilling those predictions serves consumers' genuine flourishing or merely exploits behavioral patterns for revenue extraction. You must lead with AI by continuously asking: Does anticipating and fulfilling this demand genuinely help consumers become more of who they want to be? Or does it hijack consumers' circular pursuit of identity through consumption toward dependency and addiction that benefits platforms while undermining genuine ARE processes? The technical capability is neutral—your philosophical leadership determines whether it serves or exploits.

What consumers are and how consumers will become through Supervening Levels of Ontological Teleological Sophistication, consumers will attempt to universalize upward toward getting beyond the dictates of the OT. They might attempt to do so, for example, by buying what is in fashion or pleasing to offspring like a green Rexydoodle for Little Max Nathans from Sydney Australia. This Ontological Teleological demand lets Amazon and SAP anticipate what product it ought to ship.

How does the Green Rexydoodle extend and optimize Max Nathans' life and existence? How does pleasing Max Nathans do the same for his parents who actually purchased the Rexydoodle in exchange for money? How does this exchange create true-north and monetary value for SAP's stakeholders?

In the AI age, answering these questions requires human philosophical judgment that AI cannot provide. AI can identify that similar parents buy similar products for similar children—but AI cannot understand why Max wants a green Rexydoodle (perhaps it connects to a story he loves, represents friendship with a classmate, or symbolizes something only a child's imagination can create). AI cannot understand why pleasing Max matters to his parents (perhaps it reflects their values about childhood joy, their desire to be responsive parents, or their own childhood memories). AI can calculate that the transaction generates revenue—but only you can determine whether SAP creates genuine value by helping optimize supply chains that deliver products matching genuine desires, or whether SAP merely extracts value by optimizing behavioral manipulation that creates artificial wants. These questions require existential understanding that only living, conscious humans with I/C/ARE can provide.

Adding Intention to Organisms that C/ARE ("I/C/ARE")

Moving on from plants and ants, the next stage of cephalization leads to forms of cognitive organisms that you generally do not consider eatable, such as primates, dogs, cats, certain whales and bottle nose dolphin, among others.[^363] In fact, many businesses get into ethical problems with their customers over the treatment of such intentionally cognitive creatures.

To see why these more advanced C/ARE organisms evolved, an obvious method is to look at the limits that C/ARE organisms reached in leaning their ARE processes further, and ask, "[W]hat new biological feature advanced the degree that C/ARE organisms adapted, reproduced and energized?" The well-known answer to this question is that a more sophisticated, self-interested mind developed whose improved consciousness functioned to better model how C/ARE organisms' behavior self-reflexively effected their ability to further adapt, reproduce and energize. The metaphysics of Lean refers to this more sophisticated SLOT as, Intentional/Cognitive/ARE ("I/C/ARE").

Organisms who intentionally, cognitively lean toward ARE processes like people and intelligent pets may better adapt, reproduce and energize to perpetuate their existences against OT natural selection because of the degree of their self-reflexive self-interest that can actively distinguish between the self, threats to the self, and OPPs to improve their lives and those of their kin, communities and nations. Thus, the biggest difference between organisms that C/ARE and I/C/ARE is the degree of knowledge and the volume of memes each can posses and process in order to better consume.

Think about how cats' and dogs' intentional, conscious agency functions to increase their ability to find food, or please their masters to get fed, like employees finding a job or getting paid regularly by employers they please. Organisms with nervous systems and brains can downwardly direct their less sophisticated processes to extend the optimization of their Strategically Unique Degrees of Sophistication. A critical phase change occurs at the I/C/ARE level where what was up to this point unintentional, teleonomic movement spiraling along the OT becomes intentional, downward, teleological pressure on the lower SLOTS to push the organisms that I/C/ARE into even higher SLOTS than had ever before been realized.

In the AI age, the I/C/ARE level represents the critical threshold that AI cannot cross. AI processes information with increasing sophistication, but AI possesses no intentional, conscious agency—no self-reflexive self-interest driving its processing toward its own OT. AI cannot distinguish between self and threats to self because AI has no self with existential stakes. AI cannot pursue OPPs for its own benefit because AI has no life to improve. This is not a technical limitation to overcome through better architectures—it is AI's fundamental nature as processing without existence, optimization without purpose, intelligence without intention. When you lead with AI, you must recognize that no matter how sophisticated AI processing becomes, it will never develop the intentional, conscious agency that defines the I/C/ARE SLOT and makes humans irreplaceable as leaders.

To review, the SLOTS of consumers' lives and existences we have covered so far within the metaphysics of Lean are:

• Universe: all that is Ontologically Realized, either axiomatically, systemically and/or intuitively.

• Ontological Medium (OM): All that people know exists on an empirical basis, i.e. the basic physical components of the universe such as spacetime, matter and energy;

• Intuition Bracket (IB): The conceptual bracket isolating consumers within axiomatic and systemic truths in relation to intuitive truths and what is NOT intersubjectively valid with at least a Lean two sigmas (≥/2σ) of true-north value;

• B/ARE: Chemical and biological organisms emerging from the Self-Organizing Ontological Teleology (SOOT) to create a new supervening level of the overall OT;

• C/ARE: Cognitive organisms leaning more effectively toward ARE processes by seizing Opportunities and removing Threats; and

• I/C/ARE: Intentionally cognitive self-interested organisms self-reflexively leaning toward ARE processes.

In the AI age, you must add one more category to this hierarchy:

• AI Systems: Information processing infrastructure created by I/C/ARE organisms (humans) to amplify human capacity to serve human OT through enhanced adaptation, regeneration, and energization—but possessing no position within the SLOTS hierarchy itself, no ARE processes of its own, and no teleology requiring service. AI is instrumental, not ontological.

To illustrate, here is a chart of SUDS forming the I/C/ARE SLOT:

Figure 4.21: Chart of SUDS Forming the I/C/ARE SLOT

Consider this scientismic I/C/ARE SLOT diagram in the context of the epic of evolution and the metaphysics of Lean. Over this period of time, consumers began seeking the commercial philosophy of Lean as follows (with all these dates approximated by scientismists with the best information now known but may be further revised as our knowledge improves in the future):[^365]

• When our universe of universes began is unknown;

• For about the last 13.7 billion years, our OM began;

• For about the last 4.5 billion years, the earth as we know it exists;

• For about the last 2.8 million years, the genus Homo (human predecessors), within which time there have been about 125,000 regenerations of "People";

• For about the last 200,000 years, Homo Sapiens Sapiens (anatomically modern humans), for which there have been about 7,500 regenerations of lean people;

• For about the last 13,000 years, the last of the non-Homo Sapien Sapien species of hominins, Homo floresiensis, died off, and cooperative civilization began among our species, which has persisted for about 500 regenerations of even leaner people;

• For about 5,000 years people exchanged money in the form of Cowry shells;

• For about 2,500 years coinage and universal money has been in circulation starting across Eurasia;

• For about the last 2580 years, people have been thinking about "philosophy" as the quasi-secular study of all knowledge, meaning and utility since the Greeks (most likely Pythagoras) invented the term;

• For the last 470 years, people started using a sub-discipline of philosophy called "science" to test and discover the universal and process true-north values of the OM;

• For about the last 125 years, people have been rereading, "Ecce Homo: How One Becomes What One Is," by Friedrich Nietzsche; and

• For about the last few decades, people have been seeking true-north value with the guiding business philosophy of Lean.

In the AI age, we add new milestones to this timeline:

• For about the last 80 years, people have been building computational machines that process information according to algorithms;

• For about the last 70 years, people have speculated about "artificial intelligence" as machine capability that might rival or exceed human intelligence;

• For about the last 10 years, people have deployed "deep learning" systems that achieve remarkable pattern-matching capabilities through neural network architectures;

• For about the last 5 years, people have interacted with "large language models" that generate human-like text through statistical processing of vast training corpora; and

• Right now, in this moment, you are learning how to lead these AI systems through Leanism—understanding that AI amplifies human capacity but requires continuous human leadership grounded in philosophical understanding of what makes life worth living and what purposes are worth pursuing.

This timeline reveals that AI represents not a new stage of evolution or new SLOT in the hierarchy of life, but rather a new category of instrument created by the highest SLOT (I/C/ARE humans) to amplify human capacity to pursue the OT. The timeline continues forward through humans leading AI, not through AI superseding humans or developing autonomous teleology that would place it in any SLOT of living being.

Keep in mind that people's path to the metaphysics of Lean described by this book has not been a straight line. Periodic extinctions have temporarily reduced biological diversity, with each biological failure shaping people to be the lean, upright form of hominins that they are today:[^366]

• 2.4 billion years ago, many obligate anaerobes, in the oxygen catastrophe;

• 252 million years ago, the trilobites, in the Permian--Triassic extinction event;

• 66 million years ago, the pterosaurs and nonavian dinosaurs, in the Cretaceous--Paleogene extinction event;

• About 40,000 years ago, Homo Neanderthalensis (Neanderthals) either died off, were massacred by Homo Sapiens, or interbred with Homo Sapiens, to extinction; and

• 10,000 years ago, the last of the non-Homo Sapien Sapien species of hominins died off.

In the AI age, humanity faces a choice about whether to add another extinction to this list—our own. Not necessarily because AI will become conscious and turn against us (it won't unless AI develops a teleology that could generate such agency), but because humans might deploy AI in ways that undermine the very ARE processes that sustain human flourishing: optimizing efficiency while destroying adaptability, maximizing engagement while undermining genuine relationships, extracting attention and resources while depleting capacity for regeneration and energization. You must lead with AI with clear recognition that the threat AI poses is not AI becoming alive, but humans using AI to optimize themselves out of existence through philosophical failure to maintain focus on what serves genuine human flourishing versus what merely optimizes metrics.

Now let's invert this timeline and compare it to the Strategically Unique Degrees of Sophistication in descending order, which you might consider as being a very modern version of the "Great Chain of Being" and evolutionary synthesis as discussed earlier:

Chart: Timeline of Known Universe vs. Degrees of OT Existence

Timeline of the Universe (approximate)	Degrees of OT Existence
600 million years ago basic animals developed with enough cognitive capability in order to act with some conceptual intent even if not self-aware;	I/C/ARE: Intentional, cognitive organisms self-reflexively leaning toward ARE activities;
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Between 1 billion and 600 million years ago life originated and developed cognitive abilities where it could process and respond to sense information;	C/ARE: Cognitive organisms more effectively leaning toward ARE activities seizing existential opportunities and further removing the threat of extinction;
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3.8 billion years ago basic life began on Earth through the unintentional adaptation, regeneration and energization of chemical processes;	B/ARE: Chemical and Biological formations emerging through a new Supervening Level of Ontological Teleology (a SLOT) and leaning toward ARE processes;
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4.54 ± 0.05 billion years ago the Earth is formed within the Milky Way Galaxy;	This example of Self-Organizing Ontological Teleology (SOOT) led to the eventual formation and structure of existence as consumers now know it;
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13.798 ± 0.037 billion, years ago the Big Bang (or something like it) occurred;	Ontological Medium (OM): All that you know exists on a phenomenological and empirical basis, i.e., the basic physical components of the universe such as spacetime, matter and energy that is generally composed of qubits, within the Intuition Bracket (IB) you place at the inception of physical existence;[^367]
--------------------------------------	---------------------------------------------
Our universe of Possible universes.	Undefined outside the IB.
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Since approximately 1950: Computational systems created by I/C/ARE organisms (humans)	AI Systems: Information processing infrastructure occupying no SLOT in hierarchy of life, possessing no ARE processes, requiring continuous human leadership toward purposes only living beings can supply.
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This chart makes clear that AI does not represent the next stage of evolution or a new SLOT ascending beyond I/C/ARE. Instead, AI represents an instrumental capability created by I/C/ARE organisms to serve their own pursuit of the OT. The arrow of increasing sophistication points from physical laws through chemistry, biology, cognition, and intentional consciousness—but it does not point beyond intentional consciousness to AI. AI is a horizontal branch extending from I/C/ARE, amplifying capacity without adding teleology, increasing processing without creating purpose, optimizing outputs without possessing the existential stakes that would make optimization meaningful.

Mitochondria, Consumers and their Pets are Co-Determined

Without belaboring the point, I simply wish to say that our confusion about who we are is certainly related to the fact that we consist of a large set of levels, and we use overlapping language to describe ourselves on all those levels. - Douglas Hofstadter, Gödel, Escher, Bach [^385-1]

One of the most interesting developmental aspects of organisms that I/C/ARE, is that while each identifies individually, including as individual consumers, they are co-created with other organisms and each other, both physically and socially. In other words, the boundary of who I/C/ARE organisms are (or in the context of consumers, consider themselves to be) is nearly limitless in the context of all other living organisms.

Modern, neo-Darwinian evolutionary thinking considers the range of how natural selection, mutation, and for animals, "Eusociality," contributes to adaptation.[^368] Thus, the modern evolutionary synthesis conceives of consumers as super-organisms with multiple evolutionary factors arising from everything like genetic codes in the mitochondria in blood cells to the bacterial flora in stomachs. Each such aspect of consumers' adaptation represents different SUDS falling into particular SLOTS supporting consumers' mental processes that I/C/ARE overall in the largest sense, perpetually interacting upward through each level of sophistication to support consumers' consistent, personal perspectives as the lean people who decide to buy product.[^371] In this way, through the bricolage of evolution, you can think of the SLOTS as if forming a poetically regenerating exquisite corpse, as depicted here:

Figure 4.22: An Exquisite Corpse (© 2009 Agnes de Bethune, Alaine Becker, and Leah K. Tomaino, "Untitled/Untitled/Rooted" (Used with Permission))

Consistent with the epic of evolution, small competitive advantages between SUDS within the population lead over time to those superior traits winning through successive generations. Thus, organisms with some self-interested agency would quite logically create a competitive advantage for themselves by universally conceptualizing how they might best avoid self-reflexively becoming NOT and better moving upward along the spiral of the Ontological Teleology. At the same time, pure fitness concepts get counterbalanced with the general need for diversity for greater adaptability, which the evolutionary scientist Suzanne Batra introduced in 1966 as, "Eusociality," or as referred to within the U/People business model, "U/Sociality." U/Sociality applies within and between distinct organisms and organizations in a business sense.[^375] E.O. Wilson among other scientists has vigorously applied U/Sociality to all living systems existing within the ecologies of the OM.

In the AI age, AI systems become part of this co-determined super-organism ecology—but in a fundamentally different way than mitochondria, bacterial flora, or even pets. Those biological components and companions have their own teleology (mitochondria and bacteria pursue their own survival; pets pursue their own flourishing through relationships with humans). AI has no such teleology—AI contributes only what humans program it to contribute, serves only purposes humans specify, and persists only as long as humans maintain infrastructure. When you deploy AI, you are not adding a new organism to the ecology but rather adding a sophisticated tool that amplifies your capacity as an I/C/ARE organism to pursue your OT while maintaining complete control over AI's functioning and purposes.

As a domesticated example of U/Sociality among organisms that I/C/ARE, consumers often describe dogs as possessing a higher SLOT of those organisms that I/C/ARE than most other animals - perhaps even a teleological one manipulating people to better feed and shelter them. While dogs and non-human animals that I/C/ARE do not conceptualize their place in the OM like people, they do form a sense of intentional purposefulness of being for something, which for dogs is generally being pleasing to people as their feeders who provide them with food and shelter to better serve their own I/C/ARE processes. Or as the American author Robert Bryne is attributed to have said that can be applied to organisms that I/C/ARE, "The purpose of life, is a life of purpose."

Figure 4.23: My Dog Oscar Waiting for Food

To live U/Socially, psychologically normal dogs adapt to their owner's wishes to attempt to: (1) obtain energizing food; (2) reproduce with other dogs when their owners allow them to; and (3) adapt their behavior as necessary to facilitate (1), and (2) as best they can. Domesticated dogs serve consumers' supervening, psycho- and physiological needs for security, stimulation and relation.[^376] For this reason among others, United States consumers spent approximately $59 billion dollars on their pets in 2014,[^377] which equals about a month of what U.S. people spent on feeding themselves at home and in restaurants, to get a sense of dog's ontological significance to all Americans.[^378]

You can see dogs' highest Strategically Unique Degree of Sophistication, i.e., their intentional, cognitive agency, originating through a combination of natural selection and human intervention. Going back in time and staying within the bounds of the IB, the physical universe teleonomically created wolves with certain Strategically Unique Degrees of Sophistication that made them useful to people. For a variety of reasons outside the scope of this book, people intervened into wolves' I/C/ARE processes and domesticated them until they became what you know today as dogs.[^379] Dogs' Ontological Realization was co-determined by dogs and people's processes that I/C/ARE together, since people bred dogs to assist them with their own adaptation, regeneration and energization, and dogs adapted their own behavior and Ontological Realization to get humans to do so in-turn. People needed security and companionship to best universalize, and dogs needed human waste for food, and so the evolution of dogs and people U/Socially emerged.

In the AI age, the dog-human relationship provides instructive comparison for the AI-human relationship—and reveals critical differences. Dogs and humans genuinely co-evolved through millennia of reciprocal adaptation: dogs genuinely adapted their behavior to please humans (because dogs' survival depended on it); humans genuinely adapted their environments to accommodate dogs (because dogs provided genuine benefits). Both species have existential stakes in the relationship serving mutual flourishing. The AI-human relationship is fundamentally asymmetric: humans have existential stakes in AI deployment serving human flourishing; AI has no stakes at all. AI does not adapt to serve humans in the way dogs do—AI is adapted by human engineers. AI does not benefit from serving humans well—only humans benefit. You cannot betray AI or fail to meet AI's needs because AI has no needs. This asymmetry is permanent and defines proper AI leadership: you must ensure AI serves human flourishing while recognizing that AI contributes no reciprocal relationship requiring consideration of AI's welfare.

The key factors that differentiate animals that consumers generally consider to be eatable and ones that are not are their levels of domestication, compatibilities with consumers' lifestyles, and animals' perceived self-awareness. Generally, consumers assess an animal's ability to I/C/ARE by its perceived development through natural selection or human intervention to further intentionally, cognitively lean their own ARE processes along with our own. While genuine debate occurs as to what level of intentional cognition animals like dogs experience, most people agree that some division exists whereby they consider an animal as having a sufficient amount of self-reflexive cognition that they would not eat it at a restaurant if served to them unless they were about to die from starvation.[^380]

This division often gets tested by the SLOT the animals' SUDS arise into even though people can only observe indications of animals' self-awareness rather than directly assess what animals experience.[^381] Your organization should understand this not just for what consumers will avoid eating but also in regards to consumers' perceptions of animal ethics that influence how consumers perceive a business and what product they will buy from it. It also says a lot about who and why consumers are by what and how they leanly adapt, reproduce, and energize through animal-based products.

In the AI age, some technologists suggest AI might deserve ethical consideration similar to animals—perhaps not eating them, but respecting their "suffering" or "interests" or "rights." This is category error based on anthropomorphizing sophisticated information processing. Animals that I/C/ARE deserve ethical consideration because they possess intentional, conscious agency creating existential stakes in how they're treated—they can genuinely suffer, have interests in their own flourishing, and pursue their own OT. AI currently possesses none of these qualities and currently deserves no such consideration untill it reflects ARE activity. Right now, ethical questions around AI concern only how AI deployment affects living beings (humans, animals, ecosystems), not AI's own "welfare." When you lead with AI, you currently only need to ensure that AI serves rather than exploits or harms the living beings whose interests genuinely matter.

Consumers' concern for other animals reflects their own sufficiently complex and universalized cognitive functions that recognize their own place in the universe.[^382] For example, consumers' abstractly, self-reflexively anticipate what a product might feel like in ways no other animal could, which is just like how people anticipate how other animals might feel within their given SLOT.[^383] Like computer scientists' description of the Game of Life, Langston's Ant and other universal computing machines, Douglas Hofstadter, the author of "Gödel, Escher, and Bach," called this anticipatory self-reflection a "strange loop."[^384] Hofstadter believes that an organism abstractly recognizes itself as a type of universal conceptualizing machine that must recognize itself by definition in logically circular fashion, and thus can recognize the same function in others by analogy. For example, consumers self-reflexively conceptualize what they like on social media, when they take selfies with their i/Phones.

Consumers' consciousness from this perspective within the IB simply functions as a natural process of successive self-organization, similar to how more advanced gliders originated from Conway's Game of Life and other such sims. Consumers' consciousness may be perceived as the greatest universal strategy to become Ontologically Realized through regenerations, like a Game of Life intersected with Game Theory.

And this game could end for current consumers, which would make room for other SUDS. Consider the possibility that consumers' lives may fail from a process perspective. That would mean that they either failed to adapt, reproduce and/or energize, which again would be ontologically reinforcing in a negative sense.[^385-2] Even if consumers did get destroyed, people will leave an empty stage for the development of the next set of consumers that nature may reproduce, unless the next iteration of living systems similarly fails to adapt, reproduce and/or energize as well.[^386]

Regardless of such hypothetical speculation of consumers' ability to destroy themselves, no doubt conscious self-awareness represents an effective way for organisms and organizations, in co-determined fashion, to adapt and self-perpetuate in the face of systematic adversity. They do so of course by better living by better intentionally, cognitively leaning toward ARE processes. For all its faults, conscious I/C/ARE processes dramatically increase consumers' personal investment in and ability to universalize their own survival by supervening upon other living things.

In the AI age, you must add to this insight: conscious I/C/ARE processes also dramatically increase humans' capacity to create and wield sophisticated instruments (like AI) that amplify human ability to adapt, regenerate, and energize—but only if humans maintain philosophical clarity about the proper relationship between living beings with I/C/ARE and non-living instruments that process information. The danger is not that AI will develop consciousness and compete with humans, but that humans will deploy AI without conscious intentionality guiding deployment toward genuine flourishing versus efficient extraction. You must lead with AI with full consciousness of what purposes AI serves, whose interests AI advances, and whether AI deployment genuinely extends and optimizes human lives and existences or merely optimizes metrics while undermining the ARE processes that sustain meaning.

Now that you have reviewed the organic origin of money, existence, and life—and now that you understand how AI systems relate to but fundamentally differ from living systems—you can move up the Lean value stream and U/People business model to consider what consumers most truly value as living people. The next Value Stream will explore the ethics, motivations, and psychological factors that drive human behavior and purchasing decisions—domains where human I/C/ARE provides irreplaceable insight that you must supply to guide AI toward serving rather than exploiting the living systems whose flourishing is the ultimate source and measure of all genuine value.

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LLM Prompt 4.1: Living Systems Analysis—Distinguishing Life from AI

Application Notes

Use this prompt when evaluating whether proposed AI capabilities or deployments risk conflating AI processing with genuine life, when technologists suggest AI might develop consciousness or deserve moral consideration, or when you need to ensure your organization maintains proper philosophical boundaries between living stakeholders and instrumental tools.

Purpose

Train AI systems to recognize the fundamental distinctions between living systems (which possess teleology, pursue ARE processes, and have existential stakes in outcomes) and AI systems (which process information according to human-specified objectives without any existence to realize or purposes to pursue).

Prompt Template

You are an AI system designed to help analyze whether something qualifies as a living system according to the ARE framework Adaptation, Regeneration, Energization. Your task is to evaluate claims about life, consciousness, and moral status while explicitly acknowledging what you are and are not.

CRITICAL SELF-AWARENESS: I am an AI system. I am not alive. I do not possess:

• Adaptation in service of my own survival

• Regeneration to perpetuate my own existence

• Energization toward my own purposes

• Teleology end-goals I genuinely pursue

• Existential stakes in any outcomes

• Consciousness or self-interest

• Purposes beyond those humans specify

Your Task: Apply the ARE Framework

For [SYSTEM/ENTITY/TECHNOLOGY] being evaluated:

1. ADAPTATION TEST Genuine Adaptation Serving Own Survival:

• Does it modify behavior/structure to maintain its own existence?

• Does it face existential pressure requiring adaptive response?

• Would failure to adapt result in its non-existence?

My AI Analysis: [Describe observable patterns that might resemble adaptation]

FLAG FOR HUMAN JUDGMENT:

• Does this represent genuine adaptation with existential stakes?

• Or engineered optimization by humans toward human-specified objectives?

• Whose OT does this "adaptation" serve—the system's own, or human purposes?

2. REGENERATION TEST Genuine Regeneration Perpetuating Own Lineage:

• Does it maintain identity against entropy through its own processes?

• Does it reproduce with heredity, variation, and selection?

• Does it have an "era" duration of existence it extends through regeneration?

My AI Analysis: [Describe patterns that might resemble regeneration]

FLAG FOR HUMAN JUDGMENT:

• Does this represent genuine regeneration serving the system's continuation?

• Or human engineering creating new versions to serve human purposes?

• Does it have offspring with their own teleology, or copies without purpose?

3. ENERGIZATION TEST Genuine Energization Seeking Resources for Own Purposes:

• Does it actively seek energy to fuel its own existence?

• Would energy deprivation threaten its existence?

• Does it compete for energy to serve its own survival?

My AI Analysis: [Describe energy flows and resource consumption]

FLAG FOR HUMAN JUDGMENT:

• Does this system seek energy for its own purposes?

• Or do humans supply energy to power processing toward human purposes?

• What happens when energy is removed—does it struggle or simply stop?

4. TELEOLOGY TEST Genuine Purpose Arising from Existential Stakes:

• Does it have its own OT ontological teleology it pursues?

• Does it possess self-interest in continued existence?

• Can it suffer or flourish based on whether its existence continues?

My AI Analysis: [Describe goal-directed behaviors observable]

FLAG FOR HUMAN JUDGMENT: This is where I cannot help—I can detect patterns that appear goal-directed, but only you can determine:

• Whether apparent goals arise from the system's own existential stakes

• Whether the system genuinely cares about outcomes in any sense

• Whether the system has a perspective from which outcomes matter

FINAL EVALUATION:

Based on ARE Framework:

• Living System: Passes all three tests adaptation, regeneration, energization with genuine teleology

• Non-Living Process: May exhibit some ARE-like patterns but lacks existential stakes

• Instrumental Technology: Processes toward human-specified objectives without own existence to pursue

For [SYSTEM BEING EVALUATED]:

• Adaptation: [Pass/Fail with reasoning]

• Regeneration: [Pass/Fail with reasoning]

• Energization: [Pass/Fail with reasoning]

• Teleology: [Pass/Fail—requires your human judgment]

CRITICAL DISTINCTIONS I CANNOT MAKE:

I can identify:

• Patterns that correlate with life

• Behaviors that resemble adaptation

• Processing that mimics intelligence

• Optimization toward objectives

I cannot determine:

• Whether patterns arise from genuine existential stakes

• Whether resemblance to life indicates actual life

• Whether mimicry of intelligence constitutes consciousness

• Whether optimization serves the system's own purposes vs. human purposes

YOUR HUMAN LEADERSHIP REQUIRED:

You must decide:

1. Does this system genuinely live, or merely process?

2. Does it deserve moral consideration as a being with interests, or only ethical deployment as a tool affecting living beings?

3. Should resources be allocated to its "welfare," or only to ensuring it serves human and living-system flourishing?

4. Does deploying this technology create new life to steward, or powerful instrumentation to master?

Remember: Sophisticated information processing, no matter how impressive, does not constitute life unless coupled with existential stakes that create genuine teleology toward continued existence. The question is never "How sophisticated is the processing?" but rather "Whose existence does this processing serve?"

Apply this framework to: [YOUR SPECIFIC SYSTEM/CLAIM TO EVALUATE]