Thought Experiment 01

Why this essay? It has been an exceptionally busy week, meeting with numerous business, community, civic, and local government leaders as we prepare our Bioregion Destination Management Plan. More on that soon. (If you’ve written and haven’t received a reply, I’m not ignoring you!) This essay, though, is about an interview with an AI researcher that triggered a thought experiment. The essay is highly speculative, but backed by rigor and research. I’d love to hear your thoughts.

First the interview itself, hosted by Steven Bartlett, who produces the Diary of a CEO Podcast.1 Despite its length (2 hours), it’s been viewed 3.5m times in under a week (as of this writing), so it’s obviously hitting a nerve. When it first came across my radar, I didn’t pay much attention to it on account of the typical clickbait title and fear mongering description. But when a colleague whose opinion I respect shared it directly (thanks MK!), I thought I’d better at least watch the introduction. I ended up watching the whole thing and made extensive notes.

The interview is with Daniel Kokotajlo, a former OpenAI researcher and a prominent AI forecaster.2 He’s the founder of the AI Futures Project and the lead author of ‘AI 2027,’ a widely-read scenario mapping the trajectory of artificial intelligence. His follow-up, ‘AI 2040: Plan A,’ sets out how the world could still navigate superintelligence safely.3

In the interview, he explains:

• What he saw inside OpenAI that made him walk away

• Why the people building AI privately believe it’s coming even sooner than the public is being told

• What happens if AI becomes powerful enough that humans can no longer control it, and why he puts the odds of catastrophe as high as 70%

• Why almost every job could be automated, and what that means for the next generation

• The plan he believes could still lead to abundance and a future worth living in.

What he entirely misses in this interview, like most AI forecasters, is:

• The coming Decade of Dramatic Disruption that will make the conversation of ‘how many jobs AI and robotics will displace’ entirely irrelevant. I’ve written about why it’s naive to ignore the DDD here.

• The difference between Retail AI (chatbots) and Wholesale AI (surveillance), which I’ve written about here. All of Daniel’s forecasting focuses narrowly on Retail AI.

• The Gartner Hype Cycle and its relevance to AI, which I’ve written about here. Considering that we’re likely in the early days of a massive AI market correction, it seemed odd to me that he didn’t at least mention this.4 The oversight, intentional or not, reminded me of the Upton Sinclair quote, “It is difficult to get an individual to understand something when their salary depends upon their not understanding it.”

Should you watch the full interview?

If you’re remotely interested in some of the concerns being tracked by AI forecasters, I’d recommend that you make time available to watch. It certainly is worthwhile, especially if you keep the caveats above in mind.

While it’s not a prerequisite for the rest of this essay, watching it first may provide much-needed context. If you really don’t have the time, watch from the 30 to the 60-minute mark. That half-hour provides the necessary context for the thought experiment that follows.

At about the 50-minute mark, Daniel says the following, referring to the major Big Tech companies:5

They’re focusing on automating their own research so that they can do everything that they’re doing faster. And they want to get to very high levels of general intelligence, and then deploy that out into the economy. So by the time AI comes for all these different jobs they will have had fully autonomous AI research happening for months maybe years. That means that the AIs will be vastly superhuman at AI research and probably also vastly superhuman at lots of other things.

Earlier in the conversation, at about the 30-minute mark, the conversation moved to Synaptic Pruning & Strengthening, which I’ll explain in more detail later in this essay. It was these two snippets of the conversation that led to the following thought experiment, which rests on five pillars. I’ll first describe the pillars and then describe where this could go, when we take into account the future of human coordination post the Decade of Dramatic Disruption. Instead of including dozens of footnotes, I’ve provided an extensive reference section below the essay. Here’s an overview of the five pillars (tapping on each link should zoot you directly to the relevant section, but I’m still figuring out Substack’s idiosyncrasies, so bear with me):

1. Infrastructure Mania and What Survives

2. Non-Monetary Lifeboats During Dramatic Disruptions

3. Pre-Monetary Coordination

4. AntiSocial and ProSocial AI

5. Residue From AI Bubble

Let’s dive in with each of the five pillars and then the Summary (link in case you want to cut to the chase).

Across all previous significant asset bubbles of the recent past, there’s a pattern that emerges. It happened with the construction of canals in the US and UK (1790s), railroads (1870s), and fiber (1996–2001). The pattern is that speculative capital overbuilds infrastructure that turns out to be useful only long after a period when investors are wiped out. The point is that the physical asset that remains becomes the backbone of an economy the speculators and investors never quite envisioned.

In the late 1990s, just as my tech career started, telecoms companies laid over 80 million miles of fiber across continents and under oceans. Roughly 85% of it remained “dark” (unused) until late 2005. Dark fiber was derided as a waste, but by the mid-2000s, it provided cheap capacity for broadband, cloud computing, and video streaming, which we all take for granted now.

The relevance to today is that AI infrastructure built during this current mania will survive the coming crash in degraded but functional form, just as railroads, canals, and fiber did. The valuable questions worth asking are who controls it after the (inevitable) market correction, and what coordination logic will it serve.

Historical periods of economic disruption show us another pattern: societies or communities that are willing to experiment with non-monetary or alternative monetary systems at the peak of the disruption generally fare better than those who don’t run such experiments.

The longest running example is the Swiss WIR, which has issued a currency not backed by Swiss francs since 1934. The biggest lesson from this experiment is that turnover in WIR is countercyclical. In other words, companies use it more during a recession.

The relevance to today is that communities (or bioregions) that are most primed to introduce alternative monetary systems prior to an economic correction are likely to navigate the otherwise inevitable signs of poverty unprepared communities will face (think food queues during the Great Depression).

In our valley, I’m particularly excited by the role an innocent game called Spirits of the Realms can play to provide that priming, without the complexities of attempting to introduce a new monetary system during periods of relative stability.6

To repeat the claim: communities with a pre-existing non-monetary coordination substrate — which could include mutual credit, reciprocity networks, community currencies, or smartphone games — show measurable countercyclical resilience during monetary crises. In short, if you have a bioregional focus, I would seriously consider introducing the Spirits of the Realms game into your community. Reach out if you’d like to know more before I manage to write up the results of the experiment we’re running here.

Research into the early history of our valley has got me increasingly interested in the lineage of John Amos Comenius (1592-1670).7 He was a Moravian philosopher, pedagogue and theologian who is considered the father of modern education. He lived during a pivotal period in history, straddling the transition from the end of Feudalism to the birth of what came to be known as Modernity. He witnessed significant changes in political, economic, and cultural landscapes, not unlike what we’ll be navigating as we get deeper into the DDD.

His particular contribution was Pansophism, a philosophical term that refers to universal knowledge or wisdom. The concept encompasses the idea of a comprehensive and all-encompassing understanding of the world, covering a wide range of disciplines and knowledge domains. The term is derived from the Greek words “pan,” meaning all, and “sophia,” meaning wisdom. Comenius envisioned a system of education that would provide individuals with a broad and interconnected understanding of various fields of knowledge, aiming for a holistic and universal wisdom. Zachary Stein has extensively explored this approach through numerous interviews and his 2019 book, Education in a Time Between Worlds.8

Of specific interest to me appears to be a bifurcation in Comenius’ lineage that happened sometime between 1620 (The Battle of White Mountain in which the Catholics defeated the Bohemian Protestant movement, forcing the suppression of The Unitas Fratrum which Comenius helped establish) and 1720 (the establishment of a settlement called Herrnhut at Berthelsdorf, Saxony one hundred years after The Unitas Fratrum was exiled).

• One line appears to have been carried south through Moravian missionaries (that’s the version of Comenius’ teaching that took root in our valley).

• The other line appears to be carried north and is extensively documented in the 2017 book by Lene Rachel Andersen, The Nordic Secret: A European story of beauty and freedom.9

The fascinating parallel is that both lineages entered non-monetary economies. In the north it was feudal settlements and in the south it was indigenous tribes.

In our valley, Georg Schmidt, who trained at Herrnhut, arrived at the Cape on 9 July 1737 and settled at Baviaanskloof (our valley) on 23 April 1738, establishing a teaching station among the Chainoqua Khoi. His entire approach focussed on literacy instruction in Dutch, the establishment of vegetable gardens, a water furrow to assist with irrigation, daily lessons under a pear tree, and a work-for-supplies exchange. By the end of 1738 he had 28 voluntary students. The Khoi economy he entered was non-monetary. Schmidt didn’t set out to establish a business. What he built was a coordination system: teach people to read, grow food, share labor, and organize time. I can find no record of any form of currency changing hands until much later when the British arrived. The British governor of the Cape Colony passed the Caledon Code (or Hottentot Proclamation) in 1809. It was a law that forced the indigenous Khoikhoi to have a fixed home. It also required them to carry a pass when moving around. In 1826, British currency was made the sole legal tender, formalizing the British pound sterling as the Cape’s official money.

Before the British arrived, the Moravians — in partnership with the Khoi and San tribes — had already established our valley as the second largest market town outside of Cape Town. From all the records I’ve found, Cape Town was a thriving market economy from around 1652, when Jan van Riebeeck established the Dutch East India Company (VOC) settlement and introduced Dutch guilder and various international trading coins. Money only appears in our valley’s historical records from about 1817, with the formalization of land ownership. Stated differently, between 1738 and 1817, a period of 79 years, our valley grew from nothing to become the second largest settlement outside Cape Town without a single cent changing hands. I find that a fascinating accomplishment, and it appears to trace all the way back to the teachings of John Amos Comenius (1592-1670).10

The relevance to today is that communities (or bioregions) have an historical precedent of a thriving market economy based on Contributionism rather than Exploitation right here in our valley.11

In an earlier essay, I discussed the difference between Wholesale and Retail AI:

How to Approach AI as a Threshold Guide

·

Jun 25

Why this essay? My claim is that in order to fully understand AI, the longer arc of cognitive evolution also needs to be considered. This essay presents source material, structural arguments, and key evidence across four themes relevant to AI within the context of late-stage civilization. I guarantee it’s an entirely different angle to any AI-related co…

In that essay, I said the following:

What you and I loosely refer to as ‘AI’ is only the retail face of an industry whose wholesale customer is the surveillance-commercial-military-intelligence apparatus. The retail product (chatbot, image generator, coding assistant and the like) and the wholesale infrastructure (behavioral prediction, military intelligence, and autonomous targeting) are different access tiers to the same tool.

I now want to make a further distinction between AntiSocial AI and ProSocial AI

AntiSocial AI extracts value from the people it interacts with. It concentrates capability in a small number of firms, treats users as data sources and attention as inventory, runs in centralized cloud infrastructure that depends on continuous fiat throughput, and optimizes for engagement and monetization.

ProSocial AI increases the coordination capacity of the community it serves. It runs on hardware the community can access without permission, treats users as participants whose knowledge shapes the system, operates under community governance, and optimizes for the health of a bounded place.

The first extends the logic of +M into the cognitive layer. The second is a candidate substrate for +N.12

Where this becomes particularly interesting is when we refer back to the interview that kicked off this thought experiment, specifically the mention of Synaptic Pruning & Strengthening of Neural Networks at about the 30-minute mark.

Without getting too bogged down in the detail, neural networks — in the biological sense — are the brain’s connective architecture: roughly 86 billion neurons, each forming thousands of synaptic connections to other neurons, producing a web of something like 100 trillion synapses. In a neural network, the intelligence lives in the connections between neurons and in the relative strength of those connections. Intelligence isn’t somehow stored in the neurons themselves.

Synaptic Pruning is the process by which the brain eliminates synapses that are weak, redundant, or unused. A human brain is born massively overconnected. An infant has far more synaptic connections than an adult. The developmental arc doesn’t build more connections over time. Instead, development relies on selective elimination: the brain sculpts itself by cutting away what it doesn’t need.

Synaptic Strengthening is the complementary process. Connections that fire repeatedly grow stronger. The shorthand is Hebb’s rule (1949): “neurons that fire together wire together.”13 The formal mechanism is called long-term potentiation (LTP). When a synapse is activated frequently, the receiving neuron becomes more sensitive to the signal, the connection is physically reinforced (more neurotransmitter receptors are inserted into the postsynaptic membrane, the dendritic spine itself enlarges), and the pathway becomes easier to activate next time.

That’s what happens in biology, and a similar process happens in technology (although I’m being careful not to make too many sweeping analogies because there are vast differences in how the two actually work.)

In the technological sense, Reinforcement Learning from Human Feedback (RLHF) could be compared to the biological process of Synaptic Pruning & Strengthening.14 Model pruning (a literal technique in AI, where redundant or low-contribution parameters are removed to make networks smaller and faster) is analogous to synaptic pruning. However, the biological process is bounded, embodied, and aligned with the organism’s conditions of existence. The AI process is unbounded, disembodied, and aligned with the institutional incentives of the companies running it. Hence, AntiSocial AI.

This section is already getting a little long and at risk of becoming too technical, so let me wrap up this section with a bold claim:15

Every ProSocial use of AI, however small, strengthens the synaptic weights the model has learned around coordination, reciprocity, stewardship, and commons governance, and weakens the weights it has learned around extraction, engagement capture, and monetization. Communities that put AI to work on their own coordination are, in aggregate, training the substrate on which the next form of human coordination will run.

Now we can move onto the final Pillar before I lay out the actual thought experiment we’ve been building towards.

In the asset bubbles we explored in Pillar 1, we saw that the asset class left behind after investors have lost their investment are inherently valuable some time later: canals, railroads, and fiber proved immensely useful when the time was right.

There is a slight challenge with AI in that the asset left behind after the bubble bursts (data centers, servers, and computer chips) depreciate significantly faster than previous asset classes. Stated differently, AI compute depreciates in ~3–5 years vs. decades for rails, canals, and fiber.

That is, until you consider the value of the model themselves rather than the technological equipment.

The value the AI boom has created isn’t the chips or the data centers. Instead, it’s the models themselves. The model is what remains after years of training, testing, pruning back the weak connections, and strengthening the useful ones, until what’s left is a compressed, working understanding of language, images, ecosystems, or logic. The chips may well wear out in a few years, and the data centers will become stranded assets, but the models will keep working, and can be copied for the cost of a download.

When the AI crash comes, the companies that built the models will be judged on whether they can continue generating profit at the scale their investors need. Many will fail that test, but the models themselves won’t disappear. They will sit in open repositories, on hard drives, in forks maintained by hobbyists and researchers, waiting for someone with a use for them. My bold claim is that bioregional communities could well be that someone. What Wall Street writes off as a failed bet, a valley or a watershed can pick up almost for free and use to coordinate itself through the Decade of Dramatic Disruption.

As we know, we are in the late stages of the Cycle of Globalization, which will likely decisively end when the AI Bubble pops. When that happens (it hasn’t yet, but it appears to be close), we’ll start seeing systemic stress signals that confirm we’re well into the Decade of Dramatic Disruption, or the Great Depression of the 2030s. This is when we’ll see signs of current monetary system poverty similar to what was witnessed during the Great Depression of the 1930s.

What if, by the time the AI Bubble bursts, the AIs have completed sufficient Synaptic Pruning & Strengthening so that all that remains are ProSocial models, which appear worthless and wasteful (just like fiber was in the early 2000s) to the Business-as-Usual world?

These models can then be deployed, at very low cost, specifically in service of Bioregionalism and the next iteration of human coordination in the TIMN model, this time without an extractive monetary system. What will emerge are nodes of coherence representing places where the next form of human coordination happens.

• The same thing happened when cathedrals appeared across Europe after the Thirty and Eighty Years Wars after the fall of the Byzantine Empire. The Peace of Westphalia finally brought peace to mainland Europe, closing a calamitous period of European history that killed approximately eight million people. Cathedrals created “islands of sanity” and the peace treaty created the framework for modem international relations. The concepts of state sovereignty, mediation between nations, and diplomacy all find their origins in the text of this treaty written more than three hundred and fifty years ago.16

• The same thing happened when cities and stock exchanges started forming nodes of coherence as the Market form took shape.

• The thought experiment sees bioregions as nodes of coherence as the +M form of coordination reaches its inevitable conclusion.

Is this just a pipe dream?

The answer is it depends on what those of us who have read this far do with the thought experiment.

That’s all for this week.

Next week I’ll start unpacking how we’re thinking about Transformative Tourism and how we’re pitching it to national government as a strategy that can be rolled out across the country. That was meant to happen this week, but I’m afraid things are simply moving too quickly!

Until then, remember to love the ones you’re with, and frame on!

Michael 💚

References are organized alphabetically within each pillar, then cross-pillar sources listed separately. Epistemic tags are used as follows:

• DF - Documented Fact

• AI-inf - AI Inferred: Triangulating three or more DFs using AI to assess patterns

Where a source was not read in full text (consulted via abstract, publisher summary, or authoritative secondary account), this is noted.

Ahamed, Liaquat. 1873: The Rothschilds, the First Great Depression, and the Making of the Modern World. New York: Penguin Press, 2026. [DF] (Consulted via Fortune essay and interview; book not read in full.)

Ahamed, Liaquat. “I Won a Pulitzer for Explaining the Great Depression. The AI Spending Boom Terrifies Me.” Fortune, 2 June 2026. [DF]

Dell’Oro Group. “Worldwide Data Center Capex Rose 57% in 2025.” Press release, 17 March 2026. [DF]

Federal Reserve Bank of New York, Liberty Street Economics. “Crisis Chronicles: Canal Mania (1793).” 13 June 2014. [DF]

Fisher, Irving. Stamp Scrip. New York: Adelphi, 1933. [DF] (Cross-listed under Pillar 2.)

Gartner, Inc. “Gartner Hype Cycle Research Methodology.” gartner.com. Accessed July 2026. [DF]

Gartner, Inc. “Hype Cycle for Artificial Intelligence, August 2025.” (Reported via secondary summaries; not directly accessed.) [DF]

KobeissiLetter, via IEEE Communications Society Technology Blog. Comparative AI capex as share of GDP infographic. 2025. [DF] (Market-analysis source; figures cross-checked against Dell’Oro and Real Investment Advice.)

Odlyzko, Andrew. “Internet Traffic Growth: Sources and Implications.” University of Minnesota, Digital Technology Center. Various papers, 2000–2003. [DF] (Odlyzko’s AT&T-era traffic research consulted via secondary summaries and his university page; individual paper titles not individually verified.)

Odlyzko, Andrew. “Collective Hallucinations and Inefficient Markets: The British Railway Mania of the 1840s.” University of Minnesota, January 2010. [DF/AI-inf]

Real Investment Advice. “Capex Spending on AI Is Masking Economic Weakness.” 2025. [DF] (Market-commentary source; GDP-share figure of ~1.2% cited with caveat on competing estimates.)

White, Richard. Railroaded: The Transcontinentals and the Making of Modern America. New York: W.W. Norton, 2011. ISBN 978-0-393-06126-0. [DF]

Willis, Carol. Form Follows Finance: Skyscrapers and Skylines in New York and Chicago. New York: Princeton Architectural Press, 1995. [DF] (Cited via secondary summaries; not read in full.)

Balakrishnan, Sidhya, Roberta Costa, Johannes Haushofer, and Fábio Waltenberg. “Welfare Effects of a Permanent Unconditional Cash Transfer Program: Evidence from Maricá, Brazil.” NBER Working Paper No. 33089, October 2024. [DF] (Consulted via JFI release and abstract; full text not read. The “9% household-income increase” figure attributed to this paper elsewhere is NOT confirmed in the release.)

Dini, Paolo, and Laura Sartori. Various LSE working papers on Sardex, 2015–2017. [DF/AI-inf] (Consulted via secondary summaries and ResearchGate abstracts.)

Fisher, Irving. Stamp Scrip. New York: Adelphi, 1933. [DF]

Gaddy, Clifford G., and Barry W. Ickes. Russia’s Virtual Economy. Washington, D.C.: Brookings Institution Press, 2002. [AI-inf] (Cited as competing explanation for Russian barter; not read in full.)

Gómez, Georgina M. Argentina’s Parallel Currency: The Economy of the Poor. London: Pickering & Chatto, 2009. [DF]

Gómez, Georgina M. “What Was the Deal for the Participants of the Argentine Local Currency Systems, the Redes de Trueque?” Environment and Planning A 42(7): 1669–1685, 2010. DOI: 10.1068/a42309. [DF]

Gómez, Georgina M., and A. H. J. Helmsing. “Selective Spatial Closure and Local Economic Development: What Do We Learn from the Argentine Local Currency Systems?” World Development 36(11): 2489–2511, 2008. DOI: 10.1016/j.worlddev.2007.11.015. [DF]

Guriev, Sergei, and Barry W. Ickes. “Barter in Russia.” In Paul Seabright, ed., The Vanishing Rouble: Barter Networks and Non-Monetary Transactions in Post-Soviet Societies. Cambridge: Cambridge University Press, 2000. [DF] (Cited via Woodruff and secondary summaries.)

Guriev, Sergei, and Dmitry Kvassov. “Barter for Price Discrimination.” International Journal of Industrial Organization22(3): 329–350, 2004. [AI-inf] (Cited as competing explanation.)

Kourachanis, Nikos. “Social Change and the Greek Welfare State Crisis (2010–2020).” Journal of Social Change (Walden University), 2015. [AI-inf]

Littera, Giuseppe, Laura Sartori, Paolo Dini, and Panayotis Antoniadis. “From an Idea to a Scalable Working Model: Merging Economic Benefits with Social Values in Sardex.” International Journal of Community Currency Research 21: 6–21, 2017. [DF]

Mattsson, Carolina E. S., Teodoro Criscione, and William O. Ruddick. “Sarafu Community Inclusion Currency 2020–2021.” Scientific Data 9: 426, 2022. DOI: 10.1038/s41597-022-01539-4. [DF]

Onken, Werner. “The Wörgl Experiment with Depreciating Money.” 1997. (Exact publication venue to be confirmed; widely cited in complementary-currency literature.) [DF] (Not read in full.)

Ruddick, William O. Grassroots Economics: Reflection and Practice. 2025. [DF] (In project knowledge.)

Sartori, Laura, and Paolo Dini. “From Complementary Currency to Institution: A Micro-Macro Study of the Sardex Mutual Credit System.” Stato e Mercato 107: 273–304, 2016. [DF/AI-inf]

Stodder, James, and Bernard Lietaer. “The Macro-Stability of Swiss WIR-Bank Credits: Balance, Velocity, and Leverage.” Comparative Economic Studies 58(4): 570–605, 2016. DOI: 10.1057/s41294-016-0001-5. [DF]

Woodruff, David M. Money Unmade: Barter and the Fate of Russian Capitalism. Ithaca: Cornell University Press, 1999/2000. DOI: 10.7591/9781501711466. [DF] (Consulted via publisher summary and secondary accounts; not read in full.)

Atwood, Craig D. Community of the Cross: Moravian Piety in Colonial Bethlehem. University Park: Penn State University Press, 2004. [AI-inf] (Cited for Moravian communal-economy model; not read in full.)

Balie, Isaac. Die Geskiedenis van Genadendal 1738–1988. 1988. [DF] (Not read; identified as priority source for the money-timing question.)

Balie, Isaac. Genadendal: Its Golden Age 1806–1870. 1992. [DF] (Not read in full; cited via TIMN Research Proposal and secondary accounts.)

Bredekamp, Henry C. “Vehettge Tikkuie, alias Moeder Lena van Genadendal (1737–1800).” Quarterly Bulletin of the South African Library 41(4), 1987. [DF]

Bredekamp, Henry C., and H. E. F. Plüddemann, eds. Angelika Flegg, trans. The Genadendal Diaries: Diaries of the Herrnhut Missionaries H. Marsveld, D. Schwinn and J. C. Kühnel, Volume I (1792–1794). UWC Institute for Historical Research, Publication Series B4, 1992/1999. ISBN 1-86808-115-X. [DF]

Bredekamp, Henry C., and Robert Ross, eds. Missions and Christianity in South African History. Johannesburg: Witwatersrand University Press, 1995. [DF] (Not read in full.)

Engel, Katherine Carté. Religion and Profit: Moravians in Early America. Philadelphia: University of Pennsylvania Press, 2009. [AI-inf] (Cited for the Moravian economic model in Bethlehem, PA; not read in full.)

Gillespie, Michele, and Robert Beachy, eds. Pious Pursuits: German Moravians in the Atlantic World. New York: Berghahn Books, 2007. [AI-inf] (Not read in full.)

Gollin, Gillian Lindt. Moravians in Two Worlds: A Study of Changing Communities. New York: Columbia University Press, 1967. [AI-inf] (Not read in full.)

Krüger, Bernhard. The Pear Tree Blossoms: A History of the Moravian Mission Stations in South Africa, 1737–1869.Genadendal: Moravian Book Depot, 1966. [DF] (Not read in full; the single most important unread source for Pillar 3. Claims attributed to it rest on South African History Online summaries, TIMN Research Proposal citations, and project knowledge.)

Schmidt, Georg. Tagebuch und Briefe (1737–1744). UWC Institute for Historical Research, 1981. [DF] (Primary source; not consulted directly.)

South African History Online. “Genadendal.” sahistory.org.za. Accessed July 2026. [DF] (Secondary encyclopedia source drawing substantially on Krüger.)

Viljoen, Russel. “Moravian Missionaries, Khoikhoi Labour and the Overberg Colonists at the End of the VOC Era, 1792–1796.” 1992. [DF] (Exact publication venue to be confirmed.)

Cornell Lab of Ornithology. “eBird Passes 2 Billion Bird Observations.” ebird.org, June 2025. [DF]

Cornell Lab of Ornithology. “Merlin Bird ID.” merlin.allaboutbirds.org. Accessed July 2026. [DF]

iNaturalist. “2025 Impact Highlights.” inaturalist.org, 2025. [DF]

iNaturalist. “Updated Computer Vision Model and Geomodel with Over 1,500 New Taxa (v2.26).” inaturalist.org/blog, October 2025. [DF]

Meta AI. “Llama 3.2: Revolutionizing Edge AI and Vision with Open, Customizable Models.” ai.meta.com, September 2024. [DF]

Meta Intelligence. “Small Language Models: Phi-4 vs Gemma 3 vs Llama 3.3 — Enterprise Edge AI [2026].” meta-intelligence.tech, 2026. [DF] (Market-analysis source.)

Pl@ntNet. “Introduction to Pl@ntNet.” docs.plantnet.org. Accessed July 2026. [DF]

Pl@ntNet. Live statistics. my.plantnet.org. Accessed July 2026. [DF]

Ronfeldt, David. Tribes, Institutions, Markets, Networks: A Framework About Societal Evolution. RAND Corporation, Paper P-7967. Santa Monica, 1996. [DF]

Ronfeldt, David. Commentary on TIMN information-technology pairings. P2P Foundation blog, 20 May 2009. [DF]

Ronfeldt, David. “Rethinking What ‘Tribes’ and ‘Networks’ Are Good For.” Substack series, various installments, 2025. [DF]

Stanford University, Human-Centered Artificial Intelligence (HAI). AI Index Report 2025. Stanford, April 2025. [DF/AI-inf]

Anderson, Benedict. Imagined Communities: Reflections on the Origin and Spread of Nationalism. London: Verso, 1983. [DF] (Cited in project knowledge, TIMN Nodes analysis.)

Bromberger, Christian. “Football as World-View and as Ritual.” French Cultural Studies 6: 293–311, 1995. [AI-inf] (Cited in TIMN Nodes analysis.)

Eliade, Mircea. The Sacred and the Profane: The Nature of Religion. New York: Harcourt, 1957. [DF] (Cited in TIMN Nodes analysis.)

Ostrom, Elinor. Governing the Commons: The Evolution of Institutions for Collective Action. Cambridge: Cambridge University Press, 1990. [DF]

Scott, Robert A. The Gothic Enterprise: A Guide to Understanding the Medieval Cathedral. Berkeley: University of California Press, 2003. [DF] (Cited in TIMN Nodes analysis.)

12

From Ronfeldt’s TIMN model. Refer to last week’s essay for further context:

TIMN in the Valley of Grace

·

Jul 12

Why this essay? Something significant shifted in our valley this week. I’m not quite sure WHY, so this essay lays out where my thinking’s at about bioregionalism as an emerging form of the next iteration of human coordination. My simple but rather bold claim is that each bioregion that can tell their story from a TIMN perspective, establishes itself as …