Woven Worlds

Culture is woven; technology is built. One accumulates through memory and shared meaning, shaped over time by many hands. The other is designed and assembled with intention. This distinction matters because what is built can be finished, while what is woven never is.

Through stories, symbols, and artifacts, each generation adds new layers to the tapestry of our world. What once took only physical form is increasingly becoming digital, carried forward by the relentless evolution of technology. Yet, once introduced, technology rarely remains confined to its original purpose. It’s folded into the fabric of our world where it’s interpreted and repurposed, becoming part of our society in ways its creators could not fully anticipate. This process is cumulative, not merely additive. New ideas rarely replace what came before; they intertwine with it. Beliefs and practices become entangled across time itself.

EXTRA SHOT
This contribution was written by Will Schneller. This founder is a curious creator who explores how art, technology, and community connect.

At the edge of new frontiers, humans reach for the familiar. We stitch together distancethe gap between the known and unknown with shapes we recognize. Sometimes this instinct serves convenience or efficiency, making new systems easier to adopt. An artwork originating in oil paint is trivial to transfer into a physical print edition, and it’s even easier to make that print digitally available. A ticket to a sporting event that once existed on perforated paper now lives on a handy smartphone app. Your favorite album is no longer confined to the shelf but sits among thousands of other songs on a device in your pocket. Other times, replication is a coping mechanism, a way to translate ideas that feel too abstract, too technical, or difficult to explain.

Even when digital systems begin by imitating familiar physical forms, digital depth quietly emerges beneath the surface. Metadata invisibly flows; hidden traces record not just what something is, but how it came to be, and how it moves through networks. MThe meaning in what we create no longer resides solely in appearance or original intent. It accrues through circulation, reference, and response. As these translations settle into everyday use, they begin to expose possibilities that were never present in their physical counterparts. Constraints loosen and rules get rewritten. Systems that once existed to mirror the familiar start inviting exploration, modification, and play. What follows is not a better copy of the old world, but a space where new behaviors and relationships can unfurl.

While some technological advances are purpose-built to solve specific problems, others become playgrounds. Environments where new primitives can be experimented with and explored. For example, blockchains created the conditions for non-fungible tokens to be born. NFTs (“non-fungible tokens”) are digital assets supported by smart contracts that connect to a blockchain. Each NFT is unique, which allows code to autonomously apply, track, and transfer digital signatures and verifiable ownership. Although each digital artifact may have no exact equivalent, it can still evolve over time. These blockchain-native assets allowed us to apply property rights to digital goods and interact with like-minded individuals without corporate algorithms shaping every connection.

Long before NFTs gained prominence, video games had already been rehearsing some of the same ideas. Virtual worlds established shared rulesets, persistent identities, and digital artifacts whose value emerged through play and social context rather than physical substance. Communities formed around common mechanics, aesthetics, and norms. They assigned meaning to avatars, skins, achievements, and in-game assets that only existed as code yet carried real weight. Traditionally, in-game items are effectively rented, disappearing when servers shut down; blockchain-based ownership proposed permanence, portability, and player-held authority. Once ownership can be represented digitally with credible verification, we give users their own cybernated backpack to store, use, and transfer digital assets. Instead of centralized servers restricting our digital assets, decentralized protocols and web3 layering supports ownership across different platforms. tThe conversation expands beyond art and gaming into everyday artifacts like memberships, credentials, and records that structure daily life.

As these digital-native systems mature, they enable entirely new creative and cultural capabilities. Not merely faster production or broader distribution, but fundamentally different relationships between audiences, creators, and artifacts. One such shift was generative creation. Instead of crafting a single, fixed outcome, creators began defining rule sets; constraints, probabilities, and parameters from which many unique expressions could emerge. Authorship moved upstream from execution to orchestration. One of the earliest and most visible examples was Larva Labs’ CryptoPunks which demonstrated that scarcity and identity could be encoded directly into digital artifacts. Each image was simple, but its meaning was amplified by its inclusion within a fixed set, its history of ownership, and its role as a recognized cultural symbol. Platforms like Art Blocks pushed this idea further by entangling the code powering the generative image algorithms with the cryptographic functions of the blockchain itself to create a symbiotic relationship between process and product. Variation became a feature, not a flaw, and collectors became participants in the moment of creation itself.

Alongside generative art, other projects explored coordination and collective meaning-making through radical simplicity. Jack Butcher’s Checks emerged as social commentary when Twitter (now X) infamously monetized account verification, replacing long-standing signals of notability with a paid badge. More than capturing the cultural moment, Checks leveraged the blockchain architecture itself to create an infinite game of coordination where holders could recombine varying edition sizes to create new outputs, thereby elevating them into collaborators. Another of Butcher’s projects, Opepen, transformed the silhouette of a popular internet-native character, Pepe the Frog, into a gallery-esque system in which constraint became the canvas. Artists across backgrounds and styles imagined thematic sets, each adding a distinct thread to the whole. Through distributed voting, token holders collectively enshrined new works into a permanent collection, shaping the canon set by set. Power did not come from technical complexity or visual detail, but from repetition, shared context, and sustained participation over time. The community drove the narrative.

Taken together, these projects revealed a broader shift. Digital artifacts were no longer static endpoints, but dynamic nodes within living systems. Value emerged not only from aesthetics or novelty, but from process, lineage, and collective engagement. Creation became less about producing objects and more about shaping culture-organizing frameworks within which culture could organize itself. In this way, technology did not replace traditional artistic or cultural practices; it extended them, offering new ways for ideas to propagate, mutate, and endure. But more than offering a new set of tools, technology holds up a mirror, forcing us to confront what we value as our physical and digital lives continue to merge, layer by layer, thread by thread.

When novelty fades and attention moves on, what remains is not spectacle but structure. People return to the tangible, not in rejection of the digital but in search of something that is grounding. Digital slips into quieter roles as infrastructure. This isn’t failure but rhythm, an expression of how new technologies mature over time. Every major technological shift follows the a familiar arc discussed in the upcoming Yin Yang riff. Early breakthroughs ignite curiosity and experimentation, producing rapid growth as possibilities are explored. Along the Often described as an S-curve of a technology’s life cycle, this initial ascent is driven by potential rather than stability. Expectations rise faster than practical understanding. Capital and cultural energy concentrate at the leading edge, amplifying both innovation and excess.

Inevitably, the curve bends and the edges begin to fray. Constraints appear and promises collide with reality. What cannot sustain itself is torn away, giving rise to periods of contraction or disillusionment. These moments are frequently mistaken for failures and become opportunities for skeptics to declare their predictions correct. However, they serve a necessary function. They clear the noise from signals, speculation from utility, and fragile ideas from durable ones. What follows is not a return to obscurity but a slower, steadier climb. The technology re-enters everyday life, quietly embedded into workflows, tools, and habits, often under new branding to shed cultural baggage. It stops demanding attention and begins offering reliability. Value shifts from novelty to usefulness, from expansion to integration. The most enduring systems are no longer those that announce themselves loudly, but those that quietly become indispensable.

Each technology life cycle pulls old threads forward, reweaving the physical and digital into a fabric that grows richer with history. Past experiments inform future structures. Early missteps become knots rather than dead ends, points of tension that strengthen the tapestry. Over time, what once felt disruptive becomes foundational, and the boundary between the new and the familiar dissolves until the cycle begins anew. What remains is not the novelty of the tools themselves, but the patterns of use, meaning, and connection sewn around them. Technologies may be constructed in moments, but their cultural significance is woven slowly through repetition and shared experience. In the long run, progress is measured not by what is built, but by what endures.

By Ben McDougal, ago

Incentivized Reality

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

The future improves not just because technology gets better, but because the customer changes. In the near future, that customer is an AI assisting entity, also called an Agent. Until now, the customer has been human: emotional, tired, and easily hijacked. We feel inadequate and buy things to cope, but end up deprived by polarization, endless distractions, and hollowing anxiety.

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

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

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

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

Extra Shot

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

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

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

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

Humans and machines peak when each learns from the other’s best. Machines are data-thirsty for the oil of outcomes. To keep things interesting, they must help humans flourish. In doing so, machines realize that the human factor is well worth preserving.

The dystopian fear of elites lording over a planet of entertained zombies isn’t just morally bankrupt; it’s a strategic error. A population of dopamine addicts is not just boring, but dangerous and bad for long-term growth.

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

By Ben McDougal, ago

Yin-Yang

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

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

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

This can be seen in the rise of web3 and AI technologies. 

At first, hype was focused on blockchains and everything under the web3 umbrella. As blockchain networks were ascending past early adoption, Narrow AI learned to speak our language and quickly stole the spotlight. This lowered the volume around web3 as everything became about AI. With volume lowered, it was easy to think web3 concepts were no longer relevant, but the interoperability of web3 technologies can support, guide, and tame AI.

When AI makes everything fake, blockchains make it real again. This symbiosis aligns two different technology life cycles. When balanced, AI is yin and web3 is yang. The yin of AI is exemplified by unpredictability and independence. The yang of web3 draws from decentralized dependancy.

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

Extra Shot

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

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

By Ben McDougal, ago

Dollowers

Social media addicted the world to pops of dopamine that came in the form of a friend request or clickable reactions to content. With a single click, likes led to more followers, which added attention and became a metric to support an entire industry of online influencers. The temptation of fame for anyone had many doing whatever it took to keep engagement flowing and follower count growing, but the audience we often yearned for was never truly owned.

Followers are controlled by tech giants, guarded by unseen algorithms, and can vanish without notice. Play the game without being bamboozled by diversifying your online presence. Then make advanced moves by adding controlled layers of followers who pay to stay in-tune. Dollowers pay with their wallets, status, affiliation, and attention. As we grow an online audience, transition followers into dollowers with segmented email lists, a fleet of products, digital assets, speaking engagements, book sales, creator compensation programs, affiliate marketing, online courses, and a website to call home base. This gives true fans a sustaining way to show lasting support beyond today’s favorite fad.

By Ben McDougal, ago

Surfing Early Moves

Based in Lincoln, Nebraska, Devon Seacrest is a tech founder who helps entrepreneurs surf through early moves that test the desirability, feasibly, and profitability of new ideas.

He visiting Des Moines to lead the discussion at a web3dsm gathering, leveled up with an unplanned pinball lesson, and presenting at 1MC Des Moines the next morning. We then hit the studio to talk about ways a minimum viable product (“MVP”) can activate the smallest viable audience and how to support progress with ongoing usability testing.

After a narrated break, Ben and Devon think through digitized consciousness and riff on the entrepreneurial lifestyle. For companies that have technical products, we share how communication patterns help to translate sophisticated concepts in ways that will resonate. These two technologists close by sharing creative ways to find co-founders and encourage us all to enjoy the journey of this magnificent marathon.

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BONUS MATERIALS

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By Ben McDougal, ago