Born to Etiquette

Dan Brown is a magician—not of ideas, but of illusion. His novels are crafted with the same dexterity as a stage magician’s tricks, directing the audience’s gaze where he wants it, not where truth lies. And yet, like any great illusionist, his success tells us far more about the audience than it does about him. The Da Vinci Code, Angels & Demons, and Inferno are not literary masterpieces, nor do they aspire to be. They are consumable, disposable, engineered for maximal propulsion rather than for introspection. And yet, they sell by the millions. Why? Because Brown, perhaps unwittingly, has tapped into a deeper truth: humanity, for all its intelligence and historical depth, craves the illusion of discovery more than discovery itself. We want to dance in chains—to be led through labyrinths that promise revelation but, in the end, only reinforce the patterns we already believe.

Fig. 31 I got my hands on every recording by Hendrix, Joni Mitchell, CSN, etc (foundations). Thou shalt inherit the kingdom (yellow node). And so why would Bankman-Fried’s FTX go about rescuing other artists failing to keep up with the Hendrixes? Why worry about the fate of the music industry if some unknown joe somewhere in their parents basement may encounter an unknown-unknown that blows them out? Indeed, why did he take on such responsibility? - Great question by interviewer. The tonal inflections and overuse of ecosystem (a node in our layer 1) as well as clichêd variant of one of our output layers nodes (unknown) tells us something: our neural network digests everything and is coherenet. It’s based on our neural anatomy!

At the core of Brown’s appeal is his mastery of simulated knowledge. His prose is functional, his characters wooden, but his greatest trick is making the reader feel as if they are learning. He weaves history, art, and conspiracy into a seamless, rapid-fire experience, much like a fast-food chain selling the illusion of nutrition. A reader of The Da Vinci Code does not walk away with a deeper understanding of Renaissance art, Gnostic traditions, or the history of the Catholic Church. They walk away with the feeling that they know these things, the exhilaration of movement rather than the weight of real intellectual engagement. Brown compresses genuine mysteries into formulaic suspense, feeding the same pleasure centers that conspiracy theories do: the thrill of the hidden unveiled, the comfort of a pattern discerned in the fog of history.

This is not to say that Brown’s success is undeserved. He is a craftsman of momentum, a virtuoso of structure. He understands, better than most so-called literary authors, the neural pathways that make a page turn. The short, clipped chapters, the relentless cliffhangers, the illusion of erudition—all combine to create a form of literature that is less about storytelling and more about algorithmic engagement. Brown’s books are dopamine loops, tapping into the limbic system’s hunger for resolution. And in a world dominated by infinite scrolls and social media algorithms, his books feel like literature designed for an age of fragmented attention.

But what does this tell us about humanity? That we long for knowledge, but not for its burdens. That we seek meaning, but not at the cost of effort. Brown’s popularity is a referendum on our era’s relationship with history: a yearning for depth, but an unwillingness to wade into it. This is why his works do not invite a second reading. Once the illusion is complete, there is no magic left. True literature—Dostoevsky, Borges, Shakespeare—is built on layers, on cadences that reveal deeper truths with every return. But Brown’s novels function like a rollercoaster ride: exhilarating in the moment, but utterly exhausted once the ride is over. They exist only in the act of consumption.

Yet, within this, there is a paradox. If Brown is a salesman of narrative snake oil, what does it say that millions willingly buy it? Perhaps deception is not a defect of human cognition but a feature. The evolutionary Red Queen Hypothesis suggests that survival is a constant race, that to stagnate is to perish. In this light, Brown’s work is not a cheap trick but a deeply human necessity. His novels simulate learning in the same way that myths once did, offering not truth but coherence, not complexity but rhythm. They provide a sense of mastery over a chaotic world, even if that mastery is illusory. And perhaps that is enough.

For all his flaws, Brown is an artist of his time. He is not a poet, not a prophet, not a literary architect—but he is a cartographer of desire. He maps the pathways of our yearning for secrets, for knowledge without labor, for the illusion of agency in a world that often strips it away. In this sense, Brown is not an anomaly but an inevitability. The real mystery is not why he writes as he does, but why we continue to crave it. Perhaps, in the end, we do not want to break free from our chains. Perhaps we simply want a better dance.

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import numpy as np
import matplotlib.pyplot as plt
import networkx as nx

# Define the neural network fractal
def define_layers():
    return {
        'Probability': ['Probability', 'Earth', "Biology", 'Loss', 'Trial', 'Error', ],  # 95/5
        'Deception': ['Deception'],  # 80/20
        'Strategy': ['Strategy', 'Faith'], # 51/49 
        'Knowledge': ['Knowledge', 'Kusoma', 'Hope'],  # 20/80 
        'Certainty': ["Absurdity", 'Uncertainty',  'Victory', 'Certainty', 'Love']  # 5/95
    }

# Assign colors to nodes
def assign_colors():
    color_map = {
        'yellow': ['Deception'],  
        'paleturquoise': ['Error', 'Faith', 'Hope', 'Love'],  
        'lightgreen': ['Trial', 'Kusoma', 'Certainty', 'Victory', 'Uncertainty'],  
        'lightsalmon': [
            "Loss", 'Biology', 'Strategy',  
            'Knowledge', "Absurdity"
        ],
    }
    return {node: color for color, nodes in color_map.items() for node in nodes}

# Calculate positions for nodes
def calculate_positions(layer, x_offset):
    y_positions = np.linspace(-len(layer) / 2, len(layer) / 2, len(layer))
    return [(x_offset, y) for y in y_positions]

# Create and visualize the neural network graph
def visualize_nn():
    layers = define_layers()
    colors = assign_colors()
    G = nx.DiGraph()
    pos = {}
    node_colors = []

    # Add nodes and assign positions
    for i, (layer_name, nodes) in enumerate(layers.items()):
        positions = calculate_positions(nodes, x_offset=i * 2)
        for node, position in zip(nodes, positions):
            G.add_node(node, layer=layer_name)
            pos[node] = position
            node_colors.append(colors.get(node, 'lightgray'))   

    # Add edges (automated for consecutive layers)
    layer_names = list(layers.keys())
    for i in range(len(layer_names) - 1):
        source_layer, target_layer = layer_names[i], layer_names[i + 1]
        for source in layers[source_layer]:
            for target in layers[target_layer]:
                G.add_edge(source, target)

    # Draw the graph
    plt.figure(figsize=(12, 8))
    nx.draw(
        G, pos, with_labels=True, node_color=node_colors, edge_color='gray',
        node_size=3000, font_size=9, connectionstyle="arc3,rad=0.2"
    )
    plt.title("Dan Brown: The Snake Oil of Narrative", fontsize=15)
    plt.show()

# Run the visualization
visualize_nn()

Fig. 32 Glenn Gould and Leonard Bernstein famously disagreed over the tempo and interpretation of Brahms’ First Piano Concerto during a 1962 New York Philharmonic concert, where Bernstein, conducting, publicly distanced himself from Gould’s significantly slower-paced interpretation before the performance began, expressing his disagreement with the unconventional approach while still allowing Gould to perform it as planned; this event is considered one of the most controversial moments in classical music history.