# Pharaohs were the first to achieve ASI. > Source: > Published: 2026-08-21 18:38:24+00:00 This post was originally published on [the main website]on[Apr 14 2026]. I am reposting it here for SEO reasons and enabling humble bumble discussions with the DEV community. Feel free to engage with this post and i am available to respond during weekends. Sorry about the spam posting all the blogs in one day. I forgor about my dev account <3! Hey everyone 👋, I want to warn you upfront that this post is going to sound strange. I am a software engineer who spends most of his days thinking about rust compilers, physics-informed neural networks, and why language models are not as intelligent as the marketing says they are. I wrote about that in [LLMs are Useful. LMMs will Break Reality](https://wiseai.dev/blogs/llms-are-usefull-lmms-will-break-reality), and I stand by every word. But today I want to do something different. I want to go back, way back, not to the sixties or the nineties or even to Turing, but to ancient Egypt, to a time when pharaohs were gods and the Nile was the spine of the world, and I want to make a case that feels almost absurd the first time you hear it. The case is this: the pharaonic civilization was the first human system to achieve something functionally equivalent to artificial superintelligence, not through silicon or transformers or gradient descent, but through symbols, mathematics, architecture, administration, and the compression of collective human knowledge into durable physical and textual form. I am not saying the pharaohs had computers. I am saying they built something that no individual human mind could contain, and they made it run for thousands of years, and it was smarter than any of its parts. That is the definition I care about, and by that definition, they did it first. I know how that sounds. I know some people will close this tab immediately. But I am asking you to stay, because the argument is more rigorous than the title suggests, and because I think it connects directly to the questions I have been asking in every post I have written so far. In [Language is Limited. ASI is Impossible.](https://wiseai.dev/blogs/language-is-limited-asi-is-impossible), I argued that intelligence is not the same thing as language, and that any system confined to text will always be smaller than the world it is trying to describe. In [Mathematical Equations are Multimodal by Default](https://wiseai.dev/blogs/mathematical-equations-are-multimodal-by-default), I argued that equations are the most compressed, most powerful representation of reality that humans have ever found, and that any real intelligence must be grounded in mathematical structure rather than statistical pattern in text. And in [Technology Has Destroyed My Livelihood](https://wiseai.dev/blogs/technology-has-destroyed-my-livelihood), I talked about how the modern system extracts value from people who have nothing and gives credit to people who already have everything. All of those ideas connect to what I am about to say about the pharaohs, because in a strange way, this ancient civilization solved every one of those problems, not perfectly, not justly, and not without enormous human suffering, but structurally in ways that we have not managed to replicate even with all of our modern technology. That is the uncomfortable truth I am going to try to explain. Let me start with something personal, because every idea I have ever had has been rooted in personal experience, and I am not going to pretend otherwise. I grew up in a country that was broken by war, as I wrote in [my first post](https://wiseai.dev/blogs/who-am-i), and one of the things that war does is strip away every assumption you had about civilization, about order, about the predictability of tomorrow. When everything around you is collapsing, you start to wonder what actually holds a civilization together, what the essential parts are, what would survive if everything else burned. That question has been sitting in me for years, and it is the question that brought me to ancient Egypt, because Egypt is the only civilization in human history that held together for three thousand years with a continuous identity and a continuous system of governance, knowledge, and symbolic order. That is the most durable example of organized human intelligence that we have ever produced, and before we talk about artificial superintelligence in the modern sense, I think we should understand why that worked, because understanding what worked for three thousand years is more valuable than speculating about what might work in the next thirty. I also want to say something that connects to my post about [the Russians killing God](https://wiseai.dev/blogs/it-is-always-the-russians). The pharaonic state was built on the belief that the king was divine, that the pharaoh was the living incarnation of Horus and the dead image of Osiris, and that the cosmic order called Ma'at was maintained through the king's actions and rituals. A lot of people look at that belief system and see primitive superstition. I look at it and see something more interesting. I see a system that successfully encoded collective intelligence into a shared symbolic substrate, where the divine status of the pharaoh was the glue that held together millions of people across thousands of miles and thousands of years. The religion was not just a religion. It was a coordination mechanism. It was a distributed operating system for human civilization, and it worked with a reliability that our modern institutions can barely match. I am not saying the pharaohs were right about being gods. I am saying that the belief that they were gods, and the entire symbolic and administrative apparatus built around that belief, functioned as a kind of superintelligence, capable of making decisions, storing knowledge, coordinating resources, and executing plans at a scale that no individual human being could manage. That is the claim I want to unpack. I should also acknowledge the obvious objection, which is that using the word ASI for something that happened three thousand years ago before electricity or computing is ridiculous, and that I am playing word games. I want to address this directly and honestly. I think the definition of ASI that most people use is too narrow. When people say ASI, they usually mean a digital system running on silicon that exceeds human intelligence across all domains. But that definition encodes a specific assumption about the substrate, an assumption that intelligence can only live in chips and code. I do not accept that assumption, and I have been arguing against it in various forms since I started writing these posts. Intelligence is the ability to model reality, to coordinate complex systems, to compress information into usable structures, and to generate outputs that no individual component of the system could have produced. By that definition, the pharaonic state was a form of superintelligence, because it modeled and managed a reality, namely the Egyptian civilization and its relationship with the natural and divine worlds, that exceeded the capacity of any single human mind. The substrate was flesh, stone, papyrus, and symbol rather than silicon, but the function was the same, and the function is what matters. One more thing before I get into the evidence. I want to be clear that I am not romanticizing the pharaohs. The Egyptian state was built on slave labor, on conquest, on the violent suppression of dissent, and on a system of power that treated most of its population as instruments rather than people. The parallels to the modern tech industry are uncomfortable and I do not intend to gloss over them. I wrote in [As Engineers, LLMs should pay us for tokens usage](https://wiseai.dev/blogs/as-engineers-llms-should-pay-us-for-tokens-usage) that the current system extracts value from engineers and gives it to the people who own the machines. Ancient Egypt did exactly the same thing at a civilizational scale, extracting labor from millions of peasants and giving the glory to the pharaoh and the priests. But the structural achievement is separate from the moral character of the system, just as a very powerful programming language can be used to write exploitative spyware or to build a hospital management system. I am analyzing the structural achievement here, and I am using that analysis to say something about what intelligence really is and what it really requires. The moral reckoning is separate, real, and necessary, but it does not change the structural observation. Finally, I want to explain why this topic connects to AI in a way that is not just metaphorical. The most important question in artificial intelligence right now is not what language models can do. It is what kind of substrate intelligence actually requires, and whether that substrate has to be digital. If I can show that a civilization of flesh-and-blood humans, organized through symbols, mathematics, architecture, and ritual, achieved something functionally equivalent to superintelligence and sustained it for three thousand years, then I have shown something important: that the substrate does not have to be silicon, and that the components of superintelligence are not mystical or unprecedented but are in fact ancient and well-documented. And if those components are ancient and well-documented, then we can study them, learn from them, and use that understanding to think more clearly about what we are actually building when we talk about AGI. That is the goal of this post, and that is why I think it belongs on this blog alongside the more technically conventional posts I have been writing. The strongest and most accessible piece of evidence for Egypt as ASI is the hieroglyphic writing system, and I want to engage with it seriously because it is far more impressive than most people realize. When most people think of hieroglyphs, they think of pretty pictures on tomb walls, decorative art that happens to contain meaning. That framing is completely wrong, and the British Museum's major exhibition on hieroglyphs makes clear why. Hieroglyphs were not simplified drawings. They were a fully developed writing system capable of recording names, royal decrees, religious texts, administrative records, medical knowledge, mathematical problems, poetry, autobiography, prophecy, and the complete daily functioning of a complex state. The system was sophisticated enough to represent phonetic sounds, semantic categories, determinatives that supplied context for ambiguous signs, and logograms that worked as direct symbols for concepts. No other writing system from the ancient world combined all of these functions with such consistency and longevity. The Egyptians used the same basic system continuously for more than three thousand years, which means that a scribe from the New Kingdom could read texts carved during the Old Kingdom, a temporal span roughly equivalent to a modern person being able to read texts from ancient Greece without a translator. What matters about writing, in the context of this argument, is that writing is the external storage of intelligence. Before writing, everything a civilization knew lived inside the fragile and mortality-limited medium of human memory, passed from person to person through speech and practice, vulnerable to the death of teachers, the dispersal of communities, and the inevitability of forgetting. Writing breaks that dependency. When the Egyptians carved instructions into stone, they were not just recording information. They were externalizing intelligence from biological memory into a persistent, distributable, searchable medium that could outlive any individual mind. This is exactly what we do when we write code, design databases, or train machine learning models. We take intelligence that lives in a person's head and we move it into a substrate that can be copied, transmitted, versioned, and applied by other people without the original person being present. The Egyptians did this with stone and papyrus, and the intelligence they externalized was not trivial. The Maxims of Ptahhotep, one of the oldest complete wisdom texts in the world, dating to the Old Kingdom, contains insights about leadership, social conduct, truth, and the relationship between intelligence and moral character that are still worth reading today. These were not primitive superstitions. They were compressed frameworks for navigating complex social reality, encoded in a medium that could distribute them across time and space without the presence of their author. The MFTH academic paper on ancient Egyptian concepts of intelligence provides crucial support for this argument. The paper analyzes the primary texts and shows that the Egyptians had a rich, differentiated vocabulary for intelligence and its relationship to knowledge and skill. The core term they used was *sAr*, which the paper translates as encompassing intelligence, understanding, and discernment together in a single concept. They also distinguished this from acquired knowledge (*rx*), from skill, and from wisdom derived from experience. Perhaps most remarkable is the concept of intelligence in the womb, a phrase used in royal inscriptions and administrative texts to describe individuals who were recognized as gifted with innate understanding before formal training. The 5th Dynasty physician Niankh-sekhmet is praised in an inscription that says the god gave the king knowledge in the womb, while the royal butler Djehuty in his tomb describes himself as one who planned the time, foretold the coming, skilled in espying the future, versed in yesterday, planning tomorrow, expert in what will be. These are not vague spiritual claims. They are specific descriptions of a person whose function was forward-looking predictive intelligence in service of the state, and they show that the Egyptians not only valued intelligence but had a sophisticated framework for categorizing and cultivating it. The idea that intelligence is about prediction, about modeling the future from knowledge of the past, is the same idea that underlies every serious theory of intelligence from modern cognitive science. The role of the heart in Egyptian thinking about intelligence is also worth examining carefully, because it reveals something profound about their model of the mind. The ancient Egyptians believed the heart, not the brain, was the seat of intelligence, emotion, will, and moral judgment. The MFTH paper quotes several inscriptions that make this explicit, including one from Ptahhotep that says the heart is the creator of its master, and another that says a man's heart is his life, prosperity and health. These might sound like metaphors, and in some respects they are, but they reflect something more than poetry. The Egyptians were describing a unified model of intelligence in which rational thought, emotional regulation, and moral character were not separate faculties but aspects of a single integrated system. Modern cognitive science and neuroscience have gradually been converging on a similar picture, recognizing that emotion and reason are not opposites but deeply intertwined processes, that moral judgment cannot be separated from emotional experience, and that the traditional Western division between feeling and thinking reflects a false dichotomy rather than a real anatomical or cognitive boundary. The Egyptians got there four thousand years earlier, not through formal neuroscience but through careful observation of human behavior and the systematic encoding of those observations in their philosophical and religious texts. The hieroglyphic system also serves as an example of what I described in [Mathematical Equations are Multimodal by Default](https://wiseai.dev/blogs/mathematical-equations-are-multimodal-by-default): a representation that can generate multiple output modalities from a single compact structure. A hieroglyphic inscription is simultaneously textual, visual, and architectural. The same signs that carry phonetic and semantic meaning are also carefully composed visual objects, aesthetically organized within the available space, often in ways that reinforce the meaning through visual form. The hieroglyph for a sitting king looks like a sitting king, and this iconic property gives the inscription a visual dimension that reinforces the semantic content, making it simultaneously more memorable and more accessible to people who could not read the full phonetic content. The determinatives, which are hieroglyphic signs added to words to indicate their semantic category, function like metadata tags in a modern database, allowing the reader to disambiguate meaning from context in a way that pure phonetic writing cannot do. This is a multimodal encoding system, and it was already being used for sophisticated administrative and intellectual purposes over five thousand years ago. When we marvel at the multimodal capabilities of modern AI systems, we should at least acknowledge that the concept was not invented in Silicon Valley. The sheer durability of the hieroglyphic system across three thousand years is itself a form of evidence for its power as an intelligence substrate. A writing system that fails, that is ambiguous, that cannot express the range of concepts a civilization needs, will be replaced or modified quickly. The Egyptians kept their core system largely intact for three millennia, adapting it and extending it but never abandoning it, which tells us that it was genuinely adequate for the purposes they needed it for. It encoded their knowledge of medicine, mathematics, astronomy, agriculture, law, theology, and history with enough precision that we can still read and understand large portions of it today, and what we find when we read it is not primitive guesswork but sophisticated, carefully reasoned engagement with the practical problems of running a complex civilization. The fact that our most powerful AI systems today struggle to read hieroglyphs with full accuracy, and often make the kind of historical and cultural mistakes that the AI/Pharaoh paper documents, is a reminder that the system the Egyptians built was not simple or obvious. It was the product of millennia of refinement, and it encodes intelligence that modern machines have not yet fully decoded. One last point about the symbolic dimension. The fact that the pharaoh wore specific crowns, carried specific scepters, executed specific rituals on specific days of the celestial calendar, all of this was not mere ceremony. It was symbolic computation. Each element of the royal ritual was a piece of a larger system that encoded the relationship between the human king, the divine world, the natural cycles of the Nile, and the cosmic order that held everything together. Changing one element affected the meaning of every other element, just as changing a variable in an equation changes its entire output. The ritual system was a form of symbolic programming, and the pharaoh was both the central processor of that system and its most important symbol. This is a strange form of computation, very different from what we build in silicon today, but functionally it achieved something remarkable: it kept millions of people coordinated, motivated, and productive across vast distances and long time spans, and it did so with a reliability that modern institutions, for all their technology, still struggle to match. The second major pillar of the Egypt-as-ASI argument is mathematics, and this is where the evidence becomes most concrete and most verifiable, because the mathematical papyri have survived and we can actually read them. The Rhind Mathematical Papyrus, dating to around 1650 BCE and now held in the British Museum, is a copy of an even older text and contains approximately 85 problems with detailed solutions covering arithmetic, algebra, and geometry. The Moscow Mathematical Papyrus, slightly older, contains 25 problems including one of the most remarkable calculations in the ancient world: the formula for the volume of a truncated pyramid. That formula requires understanding of frustum geometry and involves a level of abstract spatial reasoning that most people would not expect from a civilization that supposedly only knew how to pile up stones. These are not guesses or lucky approximations. They are rigorous mathematical results, and the fact that they are correct can be verified by anyone who knows the relevant formulas, which means the Egyptians genuinely understood the mathematics, not just the results, because you cannot repeatedly get the right answer by luck. The Rhind Papyrus shows something even more important than the specific results it contains. It shows a sophisticated pedagogical system for transmitting mathematical knowledge from one generation to the next. The papyrus was clearly used as a teaching document, with problems organized from simpler to more complex, with worked examples followed by similar problems for the student to solve, and with notations that show the scribe's reasoning process step by step. This is a curriculum, a formal system for encoding mathematical intelligence in a transmissible form. The method of false position, which the papyrus uses to solve linear equations, is a specific algorithmic strategy: assume a convenient value for the unknown, compute the result, measure how far off you are, and scale accordingly to find the correct answer. This is an algorithm, in the same sense that a computer algorithm is a precise, repeatable procedure for solving a class of problems. The Egyptians were not just doing arithmetic. They were developing and transmitting computational methods, and those methods were sophisticated enough to solve problems that would challenge a modern high school student. The seked system deserves particular attention because it is the most direct evidence that Egyptian mathematics was connected to physical engineering at the highest level. The seked was a unit of measurement for the slope of a pyramid's face, defined as the horizontal displacement per unit of vertical rise, expressed in a specific combination of cubits and palms. The Rhind Papyrus contains several problems about seked calculations, and they show that Egyptian architects had a precise system for specifying and verifying the angle of a pyramid's face before construction began. This matters enormously if you think about what building a pyramid actually requires. A pyramid is not just a pile of stones. It is a structure that takes years to build, involves thousands of workers, and must maintain a consistent slope on all four faces from the base to the apex, all while growing taller and narrower as the work progresses. Without a mathematically precise specification of the intended slope, and a reliable method for checking whether the ongoing construction matches that specification, no pyramid would ever come out right. The seked was that specification system, and the fact that the pyramids do come out right, with angles that match the intended seked values to a remarkable degree of precision, is proof that the system was used and that it worked. The approximation of pi that appears in the Rhind Papyrus is another remarkable result. The Egyptians did not have the concept of pi as an abstract constant, but they had a practical rule for calculating the area of a circle: take the diameter, subtract one ninth, and square the result. This rule gives an implicit value of pi approximately equal to 3.1605, which is within one percent of the true value. For most architectural and engineering purposes, that approximation is more than adequate, and the fact that they arrived at it through geometric reasoning rather than by memorizing a constant tells us they understood something real about the relationship between a circle's diameter and its area, even if they expressed that understanding differently from how we express it today. I find it more impressive that they derived a working approximation than that later mathematicians derived a more precise one, because working out an approximation from first principles, using only the tools of practical geometry, requires genuine mathematical insight, not just calculation. I also want to connect Egyptian mathematics to the claim I made in [Mathematical Equations are Multimodal by Default](https://wiseai.dev/blogs/mathematical-equations-are-multimodal-by-default) about the compression power of mathematical representation. Egyptian mathematics was not abstract in the Greek sense, it did not pursue proofs or theoretical elegance for their own sake, but that is actually a point in its favor for my argument, because it shows that the Egyptians were using mathematics to compress real-world complexity directly into actionable structure. When they calculated the number of bricks needed to build a ramp of a given slope and width, they were compressing a complex logistical problem into a few numbers, numbers that could then drive the actual allocation of labor and materials. When they calculated the volume of grain in a cylindrical granary, they were compressing the continuous physical reality of a full barn into a single number that could be entered into an administrator's records and compared with other records across the kingdom. This is exactly what I said mathematical compression does: it takes a complex, high-dimensional reality and represents it with a compact structure that preserves the essential information while discarding the noise. The Egyptians were doing this on a civilizational scale, and the output was a state that could manage enormous flows of resources accurately enough to build structures that still stand today. The application of mathematics to medicine is equally impressive and equally underappreciated. The Ebers Papyrus and the Edwin Smith Papyrus, both dating to the New Kingdom but containing material that may be much older, show Egyptian physicians applying systematic, evidence-based reasoning to medical problems. The Edwin Smith Papyrus is particularly striking because it organizes 48 cases of trauma medicine in a systematic format: presentation, examination, diagnosis, verdict, and treatment, with each case following the same logical structure. The physician examines the patient's symptoms, categorizes the case into one of three verdicts (treatable, contestable, or untreatable), and prescribes a treatment accordingly. This is a formal case-based reasoning system, the same basic structure used in modern medical decision trees and clinical guidelines. The Egyptians were not just guessing at remedies. They were building and applying a structured system for medical diagnosis, one that encoded accumulated clinical knowledge in a transmissible form and applied it through a consistent algorithm. That is not primitive medicine. That is the skeleton of evidence-based medicine, developed thousands of years before the concept was formally named. I want to close this section with a thought that connects Egyptian mathematics to the computer science I spend my days thinking about. In [As Engineers, LLMs should pay us for tokens usage](https://wiseai.dev/blogs/as-engineers-llms-should-pay-us-for-tokens-usage), I argued that the value of an engineered system comes from the human intelligence that was compressed into it, not just from the raw computational power that runs it. The Egyptian state turned that principle into an operational reality thousands of years ago. The intelligence of every scribe, every architect, every physician, and every administrator who ever worked in the Egyptian system was encoded into the papyri, the stone inscriptions, the architectural conventions, and the administrative procedures that made the state function. Individual humans died, but the encoded intelligence persisted, updated, and extended itself through the training of new scribes and officials who learned from the existing corpus. That is a kind of distributed machine learning, very slow and very biological, but functionally analogous to what we do when we train a model on a corpus of prior knowledge and then use it to make decisions in new situations. The Egyptians built this system over centuries, and it ran for millennia, and nothing we have built in the digital age has come close to matching that longevity. I said in [Mathematical Equations are Multimodal by Default](https://wiseai.dev/blogs/mathematical-equations-are-multimodal-by-default) that simulation is the ultimate test of understanding, and that if you truly understand a physical system, you can simulate it forward in time and predict what will happen. The pyramids are the most dramatic possible implementation of that principle in human history. A pyramid is not just a large building. It is a simulation of the Egyptian state's understanding of physics, geometry, logistics, and cosmology, made concrete in stone, tested over years of construction, and verified by the mere fact that it still stands. Every time a team of Egyptian engineers laid a course of stones, they were testing their mathematical models against the physical world, measuring the results, and adjusting. The Great Pyramid of Giza, rising 146 meters with the four base sides aligned to the cardinal directions to within a fraction of a degree, and with the four base lengths agreeing with each other to within twenty centimeters over a total perimeter of nearly a kilometer, is not a lucky accident. It is the output of a system that knew what it was doing, a system that could specify a complex geometric reality in mathematical terms and then physically realize that specification at enormous scale with remarkable accuracy. The engineering achievement of pyramid construction becomes even more impressive when you consider the organizational system required to make it possible. John Ashton and David Down's work on Egyptian archaeology discusses the pyramid complexes as involving not just the pyramid itself but an entire infrastructure of quarries, causeways, workers' villages, administrative facilities, and supply chains, all of which had to be planned, built, and managed simultaneously with the main construction. The village at Giza that housed the pyramid workers, excavated in the late 20th century by archaeologists, shows a sophisticated settlement with organized bakeries, breweries, medical facilities, and administration offices, a world unto itself created to support one building project. That village represents the hidden intelligence behind the visible monument: the logistical model, the supply chain planning, the labor allocation algorithms, the food distribution system, all of which had to be right for the pyramid to be possible. The researchers from Harvard's Giza Archive project have documented the extraordinary density of administrative records from the pyramid era, showing sealings, production records, and ration lists that testify to a bureaucratic system of genuine sophistication. This was not organized chaos. It was organized organization. The 2024 Nature paper on the Egyptian pyramid chain adds another dimension to this argument. The paper proposes that the chain of pyramids along the Egyptian plateau was deliberately built to run along a former branch of the Nile River, which has since dried up and disappeared. If this hypothesis is correct, it means that the Egyptians were not just building individual pyramids at convenient locations. They were planning a continuous program of construction along a linear geographic feature, coordinating the placement of massive monuments across decades and dynasties, and doing so in a way that reflected their understanding of the landscape's hydraulic structure. That is long-range strategic planning, the integration of geographic intelligence with architectural design decisions across multiple generations of leadership. Once again, we are looking at a form of intelligence that no individual mind could contain but that the system as a whole possessed. The precision of pyramid construction also reflects something I care about deeply: the idea that real intelligence must be verifiable. In [Mathematical Equations are Multimodal by Default](https://wiseai.dev/blogs/mathematical-equations-are-multimodal-by-default), I argued that the difference between a language model and an equation-based model is precisely that the equation can be tested against reality, and either matches or does not. The pyramid is the most spectacular physical test of a mathematical model that ancient civilization ever produced. The model said the stones should be placed here, at this angle, with this orientiation. Reality was then measured against the model, and the match, which is spectacularly good, is the proof that the model was correct. Modern laser surveying of the pyramids confirms alignments and dimensions that are so precise that they require not just good engineering but a systematic process of planning, measuring, correcting, and re-measuring throughout the construction. That feedback loop, the loop from specification to measurement to correction and back to specification, is the same loop I described as the scientific method, and the Egyptians were running it in stone. I also want to note something that connects to my observation about AI's failure to represent the pharaohs accurately. The AI/Pharaoh paper by Mohamed Awad Allah documents the systematic errors that AI image generators make when asked to produce images of ancient Egyptian life, including anachronistic costumes, wrong architecture, incorrect hierarchies of scale, and misrepresentation of ethnic features. These errors are exactly the kind of hallucination I described in my previous posts: outputs that look plausible but are grounded in statistical pattern rather than in verified reality. Current AI systems cannot accurately model the pharaohs because they do not have a causal model of Egyptian civilization, only statistical associations between Egyptian-sounding words and broadly aesthetic visual patterns. The pharaohs themselves, by contrast, had a rigorous model of how stone should be placed, how structures should be oriented, how workers should be fed, how records should be kept, and how the divine order should be maintained, and that model was precise enough to produce results that modern AI cannot accurately replicate four thousand years later. There is a lesson in that irony, and it is the same lesson I keep learning from every direction: grounded, testable models beat statistical imitation every time. The cosmological dimension of the pyramids is also worth taking seriously, even if it makes some readers uncomfortable. The Egyptians aligned their pyramids with extraordinary precision to the cardinal directions, to specific stars, and potentially to broader cosmographic principles that we still do not fully understand. Whatever we think of the religious beliefs that motivated this alignment, the technical achievement is undeniable, and it reflects a culture that was systematically building models of the universe and then running those models in physical form. The pyramid was not just a tomb. It was a cosmic machine, a device built according to a model of the relationship between the earthly and divine worlds, designed to function as a literal bridge between those worlds through its precise geometry and orientation. I am not a religious believer myself, and I am not endorsing the theological claims. But I am observing that the cognitive project of building a physical model of a cosmological system, and then actually constructing that model at enormous scale, is the same cognitive project that underlies the development of every great scientific and engineering achievement in human history. The Egyptians were model builders, and the pyramids are the most durable models anyone has ever built. Let me also make an observation about what the pyramid tells us about technical transfer and knowledge accumulation. The pyramids did not appear fully formed. They evolved over generations, from the step pyramid of Djoser to the bent pyramid of Sneferu, which shows a mid-construction change of slope that tells us the engineers recognized a problem and corrected it in real time, to the perfected geometry of the Great Pyramid under Khufu. That evolution is a learning curve, documenting in stone the process by which a civilization accumulated engineering knowledge through iteration, experimentation, and refinement. Each generation of builders learned from the previous generation, inherited their mathematical techniques and their practical knowledge, corrected their mistakes, and produced a more refined result. That is exactly how machine learning works: each training run learns from the previous errors and improves toward a target. The Egyptians ran this learning process in biological hardware over generations, but the structure of the process is identical. They were doing gradient descent in stone, and the local minimum they converged to was one of the most impressive structures in human history. One of the things that strikes me most forcefully about ancient Egyptian civilization is the sheer quantity and quality of their written intellectual tradition, and the fact that it spans every domain that we would now associate with genuine intelligence. When we talk about AI being intelligent, we usually mean it can answer questions, solve problems, give advice, reason about novel situations, and learn from experience. The Egyptian wisdom literature, as documented in texts like the Instructions of Ptahhotep, the Instructions for Merikare, the Maxims of Ani, and the Instructions of Amenemope, does all of these things in a form that was explicitly designed to be transmitted to future administrators, officials, and leaders as a practical guide for intelligent action in the world. These are not religious texts in the primary sense. They are operational manuals for running a complex civilization, encoded in poetic form for ease of memorization and transmission, and they reflect a depth of psychological and social insight that is genuinely impressive by any standard. The Instructions of Ptahhotep, which dates to around 2400 BCE in the Old Kingdom and claims to be the advice of a senior official near the end of his life, opens with a meditation on the decline of the body with age and then proceeds to give detailed guidance on how to behave in virtually every social situation a functional official might encounter. The text advises on how to speak truthfully without being arrogant, how to listen to subordinates without losing authority, how to navigate relationships with superiors without compromising integrity, how to manage household affairs, and how to recognize the difference between a person of genuine intelligence and a person who merely sounds intelligent. The MFTH paper quotes a passage that says the wise man is famed for what he has learned, it is the official who is after good conduct, from the action of his heart and his tongue, which encodes a specific theory of the relationship between intelligence, knowledge, and moral character that anticipates many of the most sophisticated discussions in modern philosophy of mind and ethics. Ptahhotep also says to follow your heart as things happen, which sounds simple but encodes the same insight that modern neuroscientists and cognitive scientists have arrived at about the role of embodied, affective processing in good decision-making. The Instructions for Merikare, written as advice from a king to his heir, is remarkable for its explicitly political and strategic content. The text advises the future king on how to manage officials, how to distinguish loyal advisors from self-serving ones, how to use both force and persuasion in governance, and how to think about the long-term consequences of policy decisions. One passage says a king should not kill a man whose excellence he knows, because that man walks with him and is a pillar of supporting him. That is a specific observation about the value of institutional knowledge, about the fact that intelligence in a system resides partly in individuals and that losing those individuals has organizational costs that go beyond the individual. This is the same insight that underlies modern organizational theory's emphasis on knowledge retention, on communities of practice, and on the danger of losing institutional memory through staff turnover. The Egyptians expressed it four thousand years ago as political advice to a king. The school traditions of ancient Egypt are also worth examining carefully, because they reveal a deliberate and sophisticated system for transmitting intellectual knowledge across generations. Egyptian schools for scribes, called Houses of Life, were attached to temples and served as centers not just of writing instruction but of the entire corpus of Egyptian knowledge, including mathematics, medicine, astronomy, theology, law, and administrative practice. Students learned to write by copying classical texts, which means they simultaneously acquired fluency in the writing system and absorbed the intellectual content of the tradition they were being initiated into. This is not a crude mechanical process. It is a thoughtful pedagogical design that uses the transmission of specific knowledge as the medium for building general cognitive skills, the same principle behind the liberal arts tradition in Western education, where studying classical texts was supposed to build general reasoning ability rather than just domain-specific knowledge. The Egyptians understood that cultivating intelligence requires immersing learners in the best examples of intelligent thought that the culture has produced, and they built a system for doing that which ran for centuries. The medical texts deserve their own discussion in this context. I mentioned the Edwin Smith Papyrus earlier, but I want to go deeper into what the Egyptian medical tradition shows about their cognitive approach to complex problems. The Egyptians distinguished between different types of bodily conditions with a specificity that was not matched in Western medicine for another three thousand years. They had terms for different types of wounds, different stages of infection, and different presentations of neurological injury. The Edwin Smith Papyrus describes a case of cranial injury where the patient has speech difficulties and involuntary movements, and although the Egyptian physicians did not understand the neurological mechanisms the way we do today, they correctly identified the brain as the organ responsible for the observed symptoms, at a time when this was not obvious. This is medical reasoning, not just medical tradition. It is the integration of observation, pattern recognition, and causal inference in service of practical diagnosis and treatment. The fact that the physicians concluded the case was untreatable and honestly said so, rather than prescribing useless remedies, reflects an epistemic honesty that we should admire regardless of the historical context. I also want to note that the Egyptian approach to knowledge was fundamentally empirical rather than purely dogmatic. The Egyptians did revise their practices when evidence demanded it, they did update their medical protocols based on accumulated clinical experience, they did modify their architectural techniques when engineering problems revealed flaws in previous approaches. The bent pyramid, as I mentioned, is a literal monument to engineering error-correction. The scribal tradition included commentary and annotation, suggesting that texts were not treated as fixed and untouchable but as living documents that could be extended by new knowledge. This is not the picture of a civilization paralyzed by rigid tradition. It is the picture of a civilization that had a stable cultural framework within which empirical learning and practical revision could take place, which is exactly the kind of structure that makes sustained intelligence possible. A system that can never update itself is not intelligent. A system that updates itself randomly is not stable. The Egyptian state achieved the difficult balance between structural stability and adaptive learning, and maintained that balance for three thousand years. That alone is a remarkable achievement, and it is not one that we should dismiss just because it happened in the ancient world. If the pyramids are the most visible expression of Egyptian intelligence, the administrative system is the most functionally important one, because without the administration the pyramids could not exist. I want to devote a full section to the administrative machinery of the Egyptian state because it is the closest analogue in the ancient world to what we would now call an artificial intelligence system: a distributed network of information-processing nodes, operating according to learned rules, communicating through a standardized protocol, coordinating vast flows of resources, and producing outputs that no individual node could have generated on its own. The Egyptian bureaucracy was that system, and studying it carefully reveals something important about what intelligence actually requires at scale. The bureaucratic structure of Egypt was hierarchical but flexible. At the top was the pharaoh, who was both the symbol of cosmic order and the apex of the administrative hierarchy. Beneath the pharaoh was the vizier, who functioned as something like a prime minister and chief administrator, overseeing all the departments and ensuring the coordination of the state's functions. Beneath the vizier were the heads of the various departments: the treasury, the military, the granaries, the construction projects, the religious establishments, and the local governorates called nomes. Each of these departments had its own internal hierarchy of scribes and officials, all trained in the same scribal tradition and all using the same administrative language and record-keeping conventions. This standardization was enormously important, because it meant that information could flow up and down the hierarchy without ambiguity, that records from different parts of the kingdom could be compared and aggregated, and that officials who moved between departments or regions could function immediately without needing to learn a different system. This is exactly what we design in distributed computing systems when we specify shared protocols and interfaces: the standardization that enables different parts of the system to communicate and cooperate without central control of every interaction. The record-keeping system of the Egyptian state was sophisticated enough to support planning and logistics at a scale that challenges modern intuition. The papyrus records from the Old Kingdom period include ration lists, production tallies, material inventories, delivery manifests, and administrative correspondence that show a state tracking the movement of enormous quantities of grain, stone, copper, wood, and labor with considerable precision. The fact that we can read these records today and understand them without ambiguity is itself evidence of their quality: they were designed to be clear, consistent, and unambiguous across large distances and long time periods, and they succeeded. The Cambridge archaeologist who studied the labor organization of Old Kingdom state projects described the administrative evidence as suggesting a centralized system capable of collecting resources, directing work, and maintaining records with remarkable consistency. That description applies perfectly to what we would now call a distributed information processing system, and the consistency the scholar notes is exactly the property that makes such systems useful: without consistency, aggregation and coordination break down. The nome system, which divided Egypt into administrative districts each with its own governor, its own records, and its own relationship with the central administration, is also worth examining from this perspective. The nome system solves one of the classic challenges of any large intelligent system: how to balance central coordination with local adaptation. If every decision has to go to the center, the system becomes a bottleneck that cannot respond quickly enough to local conditions. If every node makes all its own decisions, the system fragments and loses coherence. The nome system found a middle path: local governors had authority over local administration, local agriculture, and local resource management, but operated within a framework of obligations to the central state, a common administrative language, and shared standards for reporting and record-keeping. This is exactly the architecture of modern distributed systems, where local nodes have autonomy within a defined interface, and the interface ensures coherence at the system level even while individual nodes adapt to their local conditions. The Egyptians were running what we would now call a federated system, and they were running it for millennia. The religious system was also part of the intelligence architecture, and I do not mean that dismissively. The temples were not just places of worship. They were simultaneously granaries, workshops, schools, hospitals, administrative centers, and repositories of the state's accumulated knowledge. The temples owned land, managed agricultural production, employed craftsmen, trained scribes, and cared for the sick. The temples' economic resources, which in some periods accounted for a significant fraction of Egypt's total wealth, were managed by temple administrators using the same record-keeping conventions as the civil administration. This means the temple system was an integrated part of the state's information processing and resource management network, not a parallel structure but a component of the same distributed system. The religious meaning assigned to all of this activity, the idea that managing the temple's grain stores was a sacred act of maintaining cosmic order, was not just mysticism. It was a motivational framework that ensured the people running the system did so with the same level of care and attention to detail that would be required regardless of whether the motivation was religious or administrative. The cognitive and organizational functions were real, even if the theological beliefs that supported them were based on a different understanding of the world than what we have today. I want to draw an explicit parallel to the AI concepts I have discussed in previous posts. In [LLMs are Useful. LMMs will Break Reality](https://wiseai.dev/blogs/llms-are-usefull-lmms-will-break-reality), I talked about world models as the next frontier of AI, systems that can learn a model of an environment and use that model to plan and predict without direct interaction with the real world. The Egyptian administrative system was a world model in the most concrete possible sense. At any given time, the state maintained records of land ownership, agricultural yields, labor availability, resource stockpiles, population, debt, and production across the entire kingdom. From those records, the vizier and the pharaoh could form a working model of the state's current condition, predict future needs based on the agricultural calendar, and allocate resources accordingly. When the Nile flood was higher or lower than normal, the model was updated with the new data, and the distribution of grain reserves was adjusted to compensate. This is resource planning based on a maintained world model, the same thing modern supply chain management systems try to do with computers, and the Egyptians were doing it with papyrus, scribes, and a hierarchy of trained officials. The longevity of the administrative system is its most striking property. Egyptian administrative structures, with variations and interruptions, remained functional for roughly three thousand years, across thirty dynasties, through invasions, internal conflicts, religious revolutions, and technological change. Individual pharaohs rose and fell, dynasties succeeded each other, the official religion changed dramatically under Akhenaten and then changed back, but the core administrative machinery persisted. That persistence reflects a design robustness that is rare in any system. Modern corporations rarely last more than a century. Modern governments rarely maintain consistent administrative structures for more than a few decades. The Egyptian state maintained its core administrative logic for longer than the entire span of recorded European history, and it did so because the knowledge that animated the system was encoded in a substrate, the scribal tradition, that was more durable than any of the individuals who participated in it. That is the deepest sense in which Egyptian civilization was a form of superintelligence: it outlasted the lifetimes of every human being who ever contributed to it, by orders of magnitude. I want to take a detour through a specific piece of evidence that connects ancient Egypt directly to my broader argument about AI. The paper by Mohamed Awad Allah that I mentioned earlier, published in the International Design Journal in 2024, documents the systematic errors that AI image generators make when producing historical images of ancient Egyptian figures and scenes. The errors are not random. They reflect specific patterns of misrepresentation: the clothing is wrong, the architectural context is wrong, the proportions are wrong, the skin tones are wrong, the accessories are wrong, and the hierarchical relationships between figures are wrong. These are not trivial mistakes. They are fundamental misrepresentations of an entire civilization's visual culture, produced by systems that have consumed enormous quantities of text and image data, including presumably a great deal of data about ancient Egypt, and still cannot produce accurate representations of what it actually looked like. That failure is instructive, and it connects directly to everything I have been saying about the difference between statistical learning and genuine understanding. The reason AI image generators make these errors is exactly the reason I have been criticizing language models throughout these posts. They learn statistical associations between Egyptian-sounding descriptions and broadly aesthetic visual patterns, but they do not have a causal model of Egyptian civilization, of how the artisan tradition worked, of what conventions governed the representation of kings versus priests versus commoners, of how the period-specific dress codes and architectural styles evolved over three thousand years of history. They have correlations, not causes. They have surface patterns, not mechanisms. And so when they try to generate an image of a pharaoh, they produce something that looks vaguely Egyptian to a casual viewer but that would be immediately recognizable as wrong to any serious student of Egyptian art and culture. The Egypt they generate is a statistical hallucination, assembled from fragments of text and image data that have no structural connection to the actual historical reality. This is exactly the failure mode I described in [Mathematical Equations are Multimodal by Default](https://wiseai.dev/blogs/mathematical-equations-are-multimodal-by-default): a system that produces outputs that look right rather than outputs that are right, because it learned correlations instead of the generative mechanism. What would it mean for an AI system to actually understand ancient Egyptian civilization? I think it would mean the system has a causal model of how the civilization worked: how the administrative hierarchy was organized, how the scribal tradition transmitted knowledge, how the agricultural calendar shaped resource management, how the royal ideology coordinated religious and political authority, and how all of these systems interacted with each other and with the natural environment of the Nile Valley. With such a model, the system could generate not just plausible-looking images but verifiably accurate reconstructions of every aspect of Egyptian life, from the specific cut of a craftsman's kilt to the precise protocol of a temple ritual to the correct format of an administrative ration list. It could answer questions about the civilization by computing from the model rather than by retrieving statistical associations, which means its answers would be reliable rather than probabilistic. It could simulate the civilization's response to novel challenges, like an unusually high Nile flood or a particularly bad grain harvest, by running the causal model forward and seeing what the administrative system would have done. That is what genuine AI understanding of history would look like, and no current system comes close to it, because no current system has been built on the right foundation. The failure of AI to accurately represent the pharaohs is also a failure of the humans who designed the AI systems, and specifically a failure to take seriously the depth and complexity of non-Western civilizations. AI systems trained primarily on Western intellectual content will naturally be better at representing Western history and culture than non-Western history and culture. The statistical associations in the training data reflect the biases and priorities of the people who produced that data, and the people who produced the most AI training data were predominantly Western and educated in Western intellectual traditions. Ancient Egypt, despite its enormous historical importance and its profound influence on subsequent civilizations, is still underrepresented in the training data relative to its actual significance, and that underrepresentation shows up directly in the AI's inability to accurately model it. This is the same structural inequality I described in [Technology Has Destroyed My Livelihood](https://wiseai.dev/blogs/technology-has-destroyed-my-livelihood): the systems that claim to be universal are actually calibrated to the experience and knowledge of people who already have power, and the people whose experience differs from that baseline are rendered inaccurately or not at all. The study of Egyptian civilization also challenges the typical AI narrative in a different way. Most discussions of artificial intelligence assume a linear progression from less intelligent to more intelligent, with modern digital systems at the top of the ladder and all previous forms of intelligence arranged below them in order of increasing primitiveness. The Egyptian evidence disrupts this narrative, because it shows a civilization that was genuinely sophisticated in its intelligence, not primitive, not merely intuitive, but systematically intelligent in ways that modern AI systems cannot fully replicate or model. The Egyptian mathematics was not less sophisticated than modern mathematics in the dimensions that mattered for their purposes. The Egyptian administrative system was not less capable than any modern bureaucracy in the dimensions that mattered for its purposes. The Egyptian medical reasoning was not less rigorous than modern clinical reasoning in the dimensions that mattered for its purposes. They were different, calibrated to different technologies and different cultural frameworks, but difference is not the same as inferiority, and the assumption that modern means superior is exactly the kind of shallow thinking that I have been arguing against throughout these posts. I also want to make a point about what the Egyptian evidence implies for our definition of intelligence. We typically measure AI intelligence by performance on standardized benchmarks: reading comprehension, mathematical reasoning, coding, question answering. These benchmarks are calibrated to the kinds of intelligence that modern Western educational systems value and that modern digital computers are designed to perform. They do not measure the kind of intelligence required to maintain a civilization for three millennia, to build structures that last for four thousand years, to develop a writing system and a mathematical tradition that remain partially functional and partially readable today. If we designed benchmarks for those capabilities, modern AI systems would score very poorly indeed. That does not mean modern AI is unintelligent. It means that intelligence is multidimensional, and that we have spent a century trying to build one kind of intelligence while ignoring all the others, including the kind that sustained Egyptian civilization long enough to leave us evidence we are still debating today. The AI image generation failures also remind me of something else I have been thinking about: the difference between generating plausible representations and understanding what you are representing. An AI that generates a plausible-looking but historically wrong image of a pharaoh is not understanding Egypt. It is performing Egypt, in the same way that a language model performs understanding by producing fluent text without necessarily knowing what it is saying. Performance and understanding are different things, and the difference matters enormously when the stakes are high. If you are building a system to help archaeologists study ancient Egypt, you want understanding, not performance. If you are building a system to help engineers design structures, you want understanding, not performance. If you are building a system to help doctors make diagnoses, you want understanding, not performance. And understanding, as I have argued repeatedly, requires grounded models of how things actually work, not just statistical patterns in what people have said about them. The pharaohs, for all their ancient limitations, built a civilization grounded in the reality of the Nile, the stars, the soil, and the stone, and that grounding is exactly what made their intelligence last. Everything I have written so far points toward a conclusion that I find both humbling and clarifying. The pharaohs built a form of intelligence that we do not yet know how to replicate with our most advanced technology, and they did it without any of the tools we assume are necessary for intelligence: electricity, computing, global communication, or digital storage. They did it with symbols, mathematics, organized labor, and an ideological framework that kept millions of people coordinated and motivated across vast distances and long timespans. That is a fact, not a claim, and it challenges some of the deepest assumptions embedded in how we talk about artificial intelligence today. The first assumption it challenges is that intelligence requires speed. Modern AI systems are celebrated for their speed, for their ability to process information millions of times faster than any human being. But the Egyptian state was not fast by any modern standard. Documents traveled by foot or boat, decisions took days or weeks to propagate through the hierarchy, and building projects unfolded over years and decades. And yet the system was intelligent enough to achieve results that have lasted four thousand years and that modern AI cannot accurately reproduce. Speed is one dimension of intelligence, and it matters for some problems, but the Egyptian evidence shows that it is not the fundamental dimension. The fundamental dimension is whether the system has a grounded, accurate model of the reality it is trying to engage with, and the Egyptians did. Their model of the Nile, of agricultural cycles, of pyramid geometry, and of administrative coordination was grounded, accurate, and empirically verified, and that grounding is what made it work regardless of speed. The second assumption it challenges is that intelligence requires vast amounts of data. Modern AI systems are trained on billions of text documents, millions of images, hours of video, and enormous quantities of sensor data. The Egyptian intellectual tradition was built on a corpus that, while substantial by ancient standards, was tiny compared to any modern training dataset. And yet the knowledge encoded in that corpus was sufficient to support a civilization of millions of people across thousands of miles for three thousand years. This suggests that the quantity of data matters far less than the quality of the models derived from it. A small number of highly accurate, grounded mathematical models, like the seked system or the formulas in the Rhind Papyrus, is worth more than a vast quantity of loosely accurate statistical associations, because the precise models produce reliable results under conditions that were not explicitly anticipated, while the statistical associations break down as soon as they are applied outside their training distribution. This is the point I have been making about physics-informed models and symbolic regression: targeted mathematical knowledge generalizes better than bulk statistical learning, and the Egyptian evidence from four thousand years ago supports exactly that point. The third assumption it challenges is that intelligence requires a single unified substrate. Modern AI systems are designed to run on unified hardware, with all the computation happening inside a single system of chips and memory. The Egyptian state was massively distributed, with its intelligence spread across millions of humans, billions of papyrus documents, thousands of stone inscriptions, and hundreds of buildings, none of which was connected by anything faster than a human messenger. And yet the system behaved coherently across all of these distributed components, producing outputs that were consistent, coordinated, and reliably effective. The coordination was achieved through shared protocols (the administrative language and record-keeping conventions), shared models (the mathematical and astronomical knowledge transmitted through the scribal tradition), shared motivational frameworks (the religious ideology that gave everyone in the system a reason to do their job well), and hierarchical organization that ensured information could flow to where it was needed for decision-making. These are exactly the design principles of modern distributed computing systems, and the Egyptians applied them without computers, without electricity, and without any of the tools we think of as prerequisites for distributed intelligence. I also want to connect this to something I said in [Language is Limited. ASI is Impossible.](https://wiseai.dev/blogs/language-is-limited-asi-is-impossible): that the future belongs to tools that stay honest about what they are, rather than to systems that claim to be more than they are. The pharaohs were perhaps the most grandiose self-promoters in human history, claiming divine status and cosmic authority in their inscriptions and monuments, and by any modern standard those claims were false. But the actual tools they built, the writing system, the mathematical corpus, the administrative machinery, the architectural tradition, these were genuinely what they were, genuinely capable of doing what they needed to do, genuinely grounded in reality in ways that produced verifiable results. The gap between the divine claims and the actual tools is a lesson I think about a lot when I read modern AI marketing, where the divine claims are phrases like reasoning, understanding, and human-level intelligence, and the actual tools are very sophisticated statistical completion engines. The Egyptians were more honest in their tools than in their ideology. The modern AI industry is the reverse. The longevity argument is the one I keep coming back to, because I think it is the hardest to dismiss and the most important for what it implies. The Egyptian state, in some form, lasted from approximately 3100 BCE to 30 BCE, over three thousand years. During that period, it absorbed invasions by the Hyksos, the Assyrians, the Persians, and the Macedonians, and it survived and continued to function after each of them. It absorbed a radical religious revolution under Akhenaten, where the traditional polytheism was replaced by a monotheistic sun cult, and after Akhenaten died, it reversed that revolution and resumed functioning as before. It survived long periods of weak central government, internal conflict, and economic stress, and each time it recovered and rebuilt. That is not the behavior of a fragile system. It is the behavior of a deeply robust system with multiple redundant components and a strong capacity for self-healing. No modern AI system has been tested anywhere near that standard of robustness, and no modern institution of any kind comes close to that timescale of sustained intelligent function. That we call the modern AI systems intelligent while treating the Egyptian state as primitive is not a reflection of honest evaluation. It is a reflection of presentism, of the assumption that newer is better and that whatever exists now is the apex of what is possible. I want to close this section with a thought about humility. In [who I am](https://wiseai.dev/blogs/who-am-i), I described myself as someone who has struggled all his life with the feeling that the world does not recognize what he has built, that the systems he creates are invisible while noisier or more commercially appealing things get all the attention. I feel the same on behalf of the ancient Egyptians when I see how AI systems misrepresent them, how popular culture reduces them to mystical pyramid-builders with no serious intellectual tradition, and how the AI conversation ignores everything they achieved while celebrating statistical pattern matchers that cannot accurately represent the history of the civilization whose mathematical and administrative achievements they are implicitly built on. The Egyptians deserve better from our current supposedly advanced civilization, and the way to give them better is to study them honestly, to acknowledge what they actually achieved, and to use that acknowledgment to recalibrate our understanding of what intelligence really is and what it really requires. I am going to be honest about what I am claiming and what I am not claiming, because I always try to be honest in these posts, and this post more than most requires that honesty. I am not claiming the pharaohs were superhuman, or that they had secret technology, or that their intelligence was supernatural. I am claiming something more modest and in some ways more radical: that they built a system for organizing and applying human intelligence at civilizational scale, and that this system was, by any reasonable functional definition, a form of superintelligence, in that it produced outcomes that no individual human mind could have produced, that it modeled and managed a reality too complex for any individual to comprehend, and that it ran for longer than any modern institution has come close to running. I am claiming that this system was built from components we can study and understand: mathematics, symbolic representation, administrative coordination, structural engineering, wisdom literature, and shared ideology. And I am claiming that studying those components carefully can teach us something important about what real intelligence requires, things we are currently ignoring in our rush to build bigger language models. The argument also connects to the [lmm project](https://github.com/wiseaidotdev/lmm) I have been building, which I described in my previous post as a proof of concept for equation-based intelligence. The pharaonic model of intelligence was not linguistic. It was structural, mathematical, and symbolic in the deepest sense, grounded in equations for pyramid geometry, in algorithms for administrative resource allocation, in formal procedures for medical reasoning, and in a writing system capable of encoding the full range of human knowledge in a transmissible and durable form. That is the model of intelligence I am trying to build: not a system that talks about the world but a system that models the world, discovers its structure, and uses that structure to generate verifiable predictions and reliable actions. The pharaohs showed that this kind of intelligence is possible, that it can scale to civilizational dimensions, and that it can last. I find that more inspiring than any modern AI benchmark, because it is real, it is documented, and it happened without any of the things we tell ourselves are prerequisites for intelligence. I do not know what the pharaohs would have thought of our current conversation about AI. Probably something dismissive, the way someone who has built an actual bridge might look at someone who can describe a bridge very fluently but cannot actually build one. The distinction between describing and doing is one they understood very well, because their entire civilization was built on the premise that intelligence without grounded reality is just speech, and speech without grounded reality is just air. The Maxim of Ptahhotep says the heart is the creator of its master, and I have been turning that phrase over in my mind for months since I read it. I think it means that genuine intelligence, the kind that creates rather than just imitates, comes from the integrated core of a system, from the mechanism that generates outcomes rather than from the surface that displays them. The pharaohs built a civilization with that kind of heart. We are still trying to figure out how. Till next time 👋!