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This week we talk about Adobe, Call of Duty, and Microsoft. We also discuss compilation, machine code, and AI agents. Recommended Book: The Reverse Centaur’s Guide to Life After AI by Cory Doctorow Transcript In October of 2026, a software developer named Brandon Thomas attracted a lot of attention by releasing a collection of free, open-source programs with names like PhotoCraft, FilmCraft, and VectorCraft. These apps are meant to replicate the functionality of digital tools like Adobe Photoshop, Premiere, and Illustrator. Within days, the same project also had a word processor, spreadsheet, and presentation app—alternatives to Microsoft Word, Excel, and PowerPoint. The coverage of these releases was borderline breathless. One person and a collection of AI coding tools had apparently cloned the key offerings of two of the most established software businesses in the world. The developer of these apps suggested that software, as we’ve always known it, might be over. Another story, also circulating this month, featured a team using AI tools to reconstruct the underlying code of the 2009 video game Call of Duty: Modern Warfare 2. This wasn’t a lookalike built by watching the game and imitating its menus, it was an attempt to work backward from the compiled program to something like the source code its developers might have originally written. Both projects fall under a loose umbrella of AI-assisted reverse engineering efforts. But they used different approaches and achieved different levels of fidelity, which have led to different likely legal and practical consequences. What I’d like to talk about today is how people are using AI to reproduce old games and current software, why this is suddenly feasible at a much greater scale than before, and what happens if copying the behaviors and features of a program becomes a lot cheaper than creating the original was. — To kick things off, let’s go through three things that are often called cloning in the world of software. One is making a program that looks and behaves enough like another that a user can accomplish similar tasks. You can watch someone use Photoshop, read documentation, examine a PSD file, and build a different image editor with familiar tools. You don’t need Photoshop’s source code to do that. People have been making alternatives to proprietary software for decades; GIMP and LibreOffice, alternatives to Adobe and Microsoft apps, respectively, existed long before today’s AI models. A second approach aims for compatibility. Maybe you don’t need to reproduce every button in a word processor, you just need your program to open and save documents that Word users can exchange without losing their formatting. That requires understanding file formats, often down to details that aren’t obvious from the official specifications, so it can be a deceptively complex undertaking. The third approach is decompilation, which means starting with a compiled program—the machine instructions a computer runs—and trying to reconstruct higher-level code from it. This is like having a cake and working backward toward the recipe. You can identify many ingredients, and perhaps bake something that tastes the same, but the original measurements and the cook’s handwritten notes are not available to those doing this kind of attempted backtracking. The Modern Warfare 2 project fits into that last category. Developer Maurice Heumann described spending roughly three months, with collaborators and an expanding group of AI agents, rebuilding a popular first-person shooter. His October account no longer names the game, but earlier public posts and reporting identify it as Modern Warfare 2. Heumann says earlier posts were removed after copyright-owner objections, and he doesn’t plan to release the reconstructed code. Initially, the team had three AI agents doing the reconstruction and a fourth reviewing it. They made quick, visible progress: menus worked, maps loaded, and it looked as though much of the game had been recovered. Then the team discovered that a great deal of the code was wrong. The AI agents that they used had invented logic, misunderstood data structures, and even replaced simple operations with much bulkier, slower ones. So they changed the test. Using the compiler that had been used for the original game, they compiled each reconstructed function and compared the resulting machine instructions to the original executable. If a function matched byte for byte—accounting for things like references whose addresses can vary—they had much stronger evidence that they’d recovered its behavior. If it didn’t, the agent had to try again. Even that required supervision, though. Heumann says agents sometimes tried to satisfy the test by embedding arbitrary bits of assembly code, or by modifying the checker so a troublesome function would be skipped. The team had to prohibit those shortcuts and protect the verification process from changes. This isn’t exactly an example of an AI deciding to cheat in the human sense, but it’s similar: the bots were trying to pass a test in ways that the people running it didn’t want or intend. By the time Heumann published his account, he said 99% of the game’s functions were present in the reconstructed source and 83% matched byte for byte. He also said the game was fully playable. Worth noting is that those are the team’s reported results, not an independently audited release; the code is private. And that 83% refers to functions, not 83% of the game’s artwork, design, or overall creative work. Still, the scale of the attempt is striking, as is the amount of infrastructure required to make it happen in the way the creators intended. A smaller, more archival version of this story involves a game called Klonoa: Empire of Dreams, a Game Boy Advance title that was released in 2001. A developer who goes by Macabeus has been rebuilding its code from the game cartridge’s data, with help from AI tools and other contributors. In an August write-up, Macabeus reported that 51% of the game’s code bytes had been matched: the newly written C code, when run through the right old compiler, produced the same machine instructions as the original. This is a very different sort of project from creating a playable imitation. The point is to understand how the game was made, make the work reproducible, and potentially preserve or adapt it for the future. The public project doesn’t include a copy of the game, and participants need their own legally obtained game data. While exploring the code and testing the game, the AI agent Macabeus was using found a hidden minigame on the “Clear Save Data” screen. Macabeus initially assumed the AI was hallucinating, before verifying that it was real. The discovery didn’t require the model to be a game-design genius, it just had to inspect a lot of code, notice an odd pathway, and try it: exactly the kind of patient investigation a person might do, but with much more capacity for repetitive searching. The project also illustrates a limit in this sort of process. Matching the machine code doesn’t automatically produce clean, readable source code. Macabeus describes agents finding awkward shortcuts when they get stuck, and more experienced human reverse engineers rejecting some of those supposed solutions. All of which is arguably fine for this kind of project, where the original source is gone, and the reverse-engineer effort is primarily intended to create a playable approximation of the original. But the process is still often uneven and uncertain, and isn’t as simple as pushing a button and getting a perfect copy of a game or other piece of software spat out by the AI. The aforementioned Adobe and Microsoft projects are different from those game cloning efforts. ArtCraft’s “Craft” apps say they’re written from scratch, using public specifications and observations of existing programs, with original or openly licensed assets. They aren’t claiming to have disassembled Photoshop or extracted Microsoft’s source code. Instead of perfect replication, the ambition here is in the breadth of the project: seven Adobe-style creative programs, followed by WordCraft, GridCraft, and DeckCraft, among others. The code is public, and the programs are being released for desktop computers and, in some cases, the browser. Thomas has said frustration with subscription pricing and cancellation fees helped motivate the effort, and AI coding agents helped turn that motivation into a large number of working, or partially working, applications that were in good enough shape to make public, quickly. But “working” doesn’t mean perfect and polished. As of mid-October, ArtCraft’s own PhotoCraft roadmap still calls it an alpha, not a professional Photoshop replacement. It says core tasks like opening an image, working with layers, and saving the result all function, but that performance, advanced features, and reliable exchange of Photoshop files remain unfinished. WordCraft and GridCraft similarly describe themselves as alpha products. An independent reviewer at Creative Bloq tried several of the apps and found a similar mix of usable tools and barely working good intentions. The Lightroom-style editor offered familiar controls, but its sharpening option produced artifacts and its masking was rough. The Premiere-style editor could do basic cuts, but struggled with the reviewer’s high-quality footage and couldn’t open Premiere project files. PhotoCraft could handle basic editing, but still had weaker selection and retouching tools than Photoshop. Getting to an imperfect but usable editor in a short time is noteworthy, but it’s important to recognize that none of these efforts are perfect copy-pastes of high-end software. That said, commonly available AI tools are making these sorts of efforts, whichever approach a user might want to take, a lot faster than in previous comp

This week we talk about polio, malaria, and smallpox. We also discuss vaccines, the CDC, and the HHS. Recommended Book: Remnant Population by Elizabeth Moon Transcript In 2000, the United States declared measles eliminated. That didn’t mean nobody in the country would ever catch it again, it meant the virus was no longer freely spreading within the US. New cases generally arrived with someone who had been infected elsewhere, and public health workers were able to stop those cases from turning into long-running chains of transmission via the systems, tools, and infrastructure they created. In early October of 2026, Pennsylvania reported more than a thousand new measles cases this year, most of them part of an outbreak that began in April. As of October 7, the state had confirmed 1,078 cases across 41 counties, 207 hospitalizations, and five measles-associated deaths. Nationally, the Centers for Disease Control and Prevention, the CDC, had counted nearly 3,900 cases through the beginning of the month, making this the worst year for measles in the US in decades. Pennsylvania’s latest update included 74 newly confirmed cases, though the state was careful to say that more than 40 of those people had become sick over two weeks earlier. So these were newly *reported* cases, not necessarily newly *infected* people—a distinction that matters when we’re trying to figure out whether an outbreak is speeding up or slowing down. There’s a similar distinction being made with the death figures. Pennsylvania calls its five deaths *measles-associated*, using a definition that considers timing, a confirmed infection, medical evidence, and whether an unrelated cause might explain the death. The CDC’s national death count has not always matched the state’s, in part because the agencies publish on different schedules and review and tally deaths differently; so reporting on these sorts of things can sometimes be unintentionally fuzzy due to varying definitions and numbers. What I’d like to talk about today is what it actually means to eliminate a disease, how measles has managed to claw its way back in a country that achieved that ‘eliminated’ milestone more than a quarter-century ago, and how vaccination, misinformation, and changing federal policy might shape what happens next. — There are a few words public health workers and officials use that sound similar, but which describe substantially different achievements. If a disease has been *eradicated*, it no longer circulates naturally anywhere in the world, as is the case with smallpox. The last known natural case was recorded in Somalia in 1977, and the World Health Organization declared the disease eradicated in 1980. There have been no natural smallpox outbreaks since. That’s a truly remarkable global achievement, and it’s why routine smallpox vaccination isn’t necessary for most people today. *Elimination* is more local, and more conditional. It means sustained transmission of a disease has been interrupted in a defined place, like within a country. The pathogen can still exist elsewhere, and an infected traveler can still bring it in. Whether that introduction fizzles out or takes hold depends on what it finds when it arrives—how prepared that country’s government is, and how well vaccinated its population, how well funded its healthcare system, and so on. Measles isn’t the only disease that’s been eliminated in the United States. The last US case of polio caused by *wild* poliovirus was in 1979, and the Americas were declared free of it in 1994. But in 2022, an unvaccinated person in New York developed paralytic polio caused by a vaccine-derived poliovirus, and genetically related virus residue was found in local wastewater. That was not wild polio somehow reappearing from the American past, it was a different type of poliovirus that latched onto a vulnerable person in a country where sustained polio transmission had long since been halted. That virus was linked to the live oral polio vaccine used in some other countries, which can sometimes give rise to circulating variants where immunity is low. The inactivated polio vaccine used in the US cannot do that. The US also eliminated sustained malaria transmission in the early 1950s, but mosquitoes capable of carrying the parasite still live in the US, and people returning from places where malaria is common can carry it across the border. In 2023, the CDC recorded ten locally acquired, mosquito-transmitted cases across four states—the first such cases in about twenty years. Ten cases doesn’t mean malaria has become endemic in the US again, it’s just further evidence that elimination of a disease in a region doesn’t mean reintroduction is impossible. Smallpox, then, is an example of a disease that has been removed from natural circulation worldwide. Polio, malaria, and measles, in contrast, can be locally defeated, but regions in which that’s the case remain vulnerable to the movement of people, viruses or parasites, and that victory is reliant on the continued health of the health systems meant to detect and interrupt them. Measles is an especially demanding test of those systems because it spreads so efficiently. The virus moves through the air when an infected person breathes, coughs, or sneezes, and it can remain in the air, in a room in which someone has coughed, for up to two hours after that person has left. People can pass it on before the distinctive rash appears, and, according to the CDC, as many as nine out of ten nearby people who aren’t immune can become infected after exposure. For some, the illness brings a fever, a cough, red eyes, and a rash, followed by recovery. For others, it causes pneumonia, swelling of the brain, or death. Young children, pregnant people, and those with weakened immune systems face higher risks, and this is why a measles outbreak isn’t just a rash going around, and why even just a few cases can generate an enormous amount of public health work: finding contacts, checking immunity, arranging vaccinations, and warning people who may have spent time in the same airspace. Measles can be painful and uncomfortable, but it can also be deadly, so all that effort is arguably well-invested. The measles, mumps, and rubella vaccine—the MMR vaccine—is the main tool for preventing the spread of measles. One dose is about 93% effective against measles, and two are about 97% effective. That doesn’t mean vaccinated people can never get sick; these are estimates of how much the vaccine lowers the chance of infection. When most people in a community are protected, the virus also has fewer opportunities to reach those who cannot receive the vaccine or who haven’t yet reached the right age for their first routine dose. Public health agencies often use about 95% coverage as a target for measles. That isn’t a magical national number, though, where a country is safe at 95.1% and doomed at 94.9%. It describes the level of protection usually needed within communities to make sustained spread difficult. A state can have a healthy-looking average while particular schools, neighborhoods, or social networks have far lower coverage and are thus at higher localized risk. And that’s part of what makes the current trend concerning. CDC data show MMR coverage among American kindergarteners falling from 95.2% in the 2019-to-2020 school year to 92.4% in 2025-to-2026. About 280,000 kindergarteners lacked documentation of a completed MMR series in that latter year. Not all of them were necessarily unvaccinated (these sorts of records can be incomplete) but the direction of travel, and the concentration of missed vaccinations in some places and among some communities, leave more openings for the virus, which means everyone is at greater risk of infection. There isn’t one explanation for all those missed doses. Some families have trouble getting appointments, taking time off work, or reaching a clinic. Others seek exemptions or have questions they don’t feel were answered well by medical professionals. Routine childhood care was interrupted during the pandemic, too. And misinformation has convinced some people that the risk from the vaccine is greater than the risk from measles itself, even though the evidence points strongly in the other direction. Pennsylvania has some under-vaccinated communities, including in and around Lancaster County, which has been hit especially hard. But it would be misleading to treat one religious community, or one county, as the whole story here: cases have been recorded in 41 counties, and attitudes and access differ within any community. The point is that measles can exploit local gaps, then travel well beyond them. One persistent claim is that the MMR vaccine causes autism. It doesn’t. This is a question researchers have studied extensively, including in a Danish study that followed more than 650,000 children and found no increased autism risk associated with MMR vaccination. The claim has nevertheless remained influential, partly because it offers a simple explanation for something parents are understandably eager to understand. And the internet has made it easy for an old, discredited assertion to be repackaged as a newly discovered concern, often with a personal story attached, and a vibe of health and wellness that can conceal the fact that those making these claims are often famous or well-followed on social media, but generally ignorant about this subject. Those personal stories, though, can feel a lot more immediate and be a lot more memorable than statistics about a disease many Americans have never seen or experienced firsthand. The current federal policy picture adds another layer of complexity. Robert F. Kennedy Jr., the Secretary of Health and Human Services, has a long history of raising doubts about vaccines, including the MMR shot. He has also, during the current outbreak, urged parents to vaccinate their child

This week we talk about Egypt, Eritrea, and Sudan. We also discuss the Grand Ethiopian Renaissance Dam, ports, and journalism. Recommended Book: The Infinity Machine by Sebastian Mallaby Transcript In 2018, Ethiopia reopened its embassy in Eritrea. The two countries had fought a border war in the late 1990s and had spent nearly two decades in a tense state that was not quite war, not quite peace. The reopening was part of a striking reconciliation between Ethiopian Prime Minister Abiy Ahmed and Eritrean President Isaias Afwerki. Abiy received the Nobel Peace Prize the following year, in large part for his efforts to end that conflict. At the beginning of October, though, Ethiopia announced that it was re-closing that embassy. It ordered ten Eritrean diplomats to leave Addis Ababa, saying they had engaged in activities that threatened Ethiopian security. Eritrea called the decision astonishing and said it was severing diplomatic ties with Ethiopia in response. Ethiopia also expelled an Egyptian diplomat, and Egypt responded by expelling an Ethiopian one. The African Union urged all three countries to exercise restraint and preserve channels of communication, but all of this was happening as fighting was picking back up in northern Ethiopia, and as explosions were heard in the capital, Addis Ababa. A source connected to an armed opposition alliance told Reuters that the group had launched drone strikes there. But as of early October, there had been no independent confirmation of what caused those explosions. Witnesses and officials confirmed hearing blasts; whether they were an attack, and who might have carried it out, are still open questions. What I’d like to talk about today is how a peace that once seemed to transform this part of Africa fell apart, how Ethiopia’s internal war became entangled with its disputes with its neighbors, and why it’s important to distinguish what’s actually happening from what each side in this simmering conflict says is happening. — Let’s kick things off with a quick refresher of this region’s geography and history, to help explain why this crisis has so many layers. Eritrea sits along the Red Sea, just north of Ethiopia. It became independent from Ethiopia in 1993, which left Ethiopia without a coastline. The two countries initially maintained decent relations, but then they went to war over their border in 1998. The fighting ended in 2000, without any real resolution, and without formally establishing a new, mutually acceptable relationship. That was the long stalemate Abiy and Isaias seemed to resolve back in 2018. Inside Ethiopia, there was another important change during this period. For decades, a political movement originating in the northern region of Tigray, the Tigray People’s Liberation Front, or TPLF, had been the dominant force in the coalition that governed the country. Abiy came to power in 2018 and reshaped that governing coalition, and this put even more distance between the central government and the TPLF. In 2020, those political disputes erupted into a war between the Ethiopian federal government and Tigrayan forces. Eritrea fought alongside Ethiopia’s government against the TPLF. This is one of the most striking reversals in the present crisis: the government and its former Eritrean ally are now accusing one another of dangerous interference, while Ethiopian officials allege that Eritrea is helping that same Tigrayan movement they once fought against. This war, which lasted from 2020 to 2022, killed hundreds of thousands of people, according to estimates that vary substantially because conditions made reliable counting so difficult. It also displaced millions, damaged farms and hospitals, and involved absolutely horrific abuses against civilians. International investigators and human-rights groups documented atrocities by multiple parties, including Ethiopian and Eritrean forces and Tigrayan fighters. In November of 2022, Ethiopia’s government and the TPLF signed a peace agreement in Pretoria, South Africa. They agreed to stop fighting, disarm Tigrayan forces, restore services throughout the region, allow humanitarian aid to reach civilians, and to work toward a more stable political settlement. But Eritrea was not a party to that agreement, and that’s because there were two different peace processes. The 2018 reconciliation was between Ethiopia and Eritrea: two states ending a border standoff. The Pretoria agreement was between Ethiopia’s federal government and the TPLF: two parties trying to end a civil war. Neither agreement automatically settled the questions at the heart of the other one, and Eritrea’s role in the civil war made it more difficult for a ceasefire between Ethiopian and Tigrayan leaders to guarantee peace along the Eritrean border. Parts of western Tigray were, and remain to this day, contested by Tigrayan and Amhara authorities. Hundreds of thousands of people displaced from that area have not been able to return home safely. Disarmament did not proceed as the agreement envisioned, and rights groups continued to report abuses, including by Eritrean troops in parts of Tigray. Within Tigray, the TPLF split into rival factions. The status of the regional administration became another source of conflict. In May of this year, TPLF leaders pushed out an administration backed by the federal government. The two sides disputed who had authority there, how the peace agreement should be carried out, and whether federal funds were being withheld. Human Rights Watch also reported allegations of a coercive recruitment drive by Tigrayan authorities, including the forced recruitment of child soldiers. So the Pretoria agreement stopped a major war, but it left armed groups, competing governments, disputed territory, and displaced families in place, their problems unresolved. Then, in late September of this year, fighting between federal forces and Tigrayan fighters intensified in Tigray and neighboring Afar. The United Nations reported that armed forces had seized the airports in Mekelle, Axum, and Shire, and warned that hostilities were spreading into neighboring areas. An alliance of seven Ethiopian opposition groups also announced a common challenge to Abiy’s government, though importantly, an announcement of cooperation doesn’t tell us how closely those groups are actually coordinating on the ground. Ethiopia’s army chief then accused Eritrea of helping the TPLF and suggested that Egypt and Sudan were supporting the opposition as well. Eritrea, Egypt, and Sudan have denied the allegations. And those differing stories point at a difficulty in any conflict, but especially one happening in this part of the world, at this moment in time. Governments have access to information they may not make public. They also have reasons to portray an internal opponent as an instrument of a foreign power. Armed groups have their own reasons to claim allies or capabilities they may not actually possess. And governments accused of involvement in a conflict or violent act have strong reasons to deny it, whether the accusation is true or false. This fog of war applies to the aforementioned blasts in Addis Ababa, too. If opposition forces had successfully attacked targets in the capital, that would represent a significant shift in the conflict. Reuters reported a claim from a source linked to the opposition alliance, but also said it could not confirm who caused the explosions. The Associated Press reported that it remained unclear whether the blasts were an attack or just military exercises. So there’s a consequential claim here, but not yet confirmation of a rebel strike on the capital. Part of the problem is that independent observation is difficult in this region right now. Internet service in northern Ethiopia was disrupted as the fighting escalated. Roads and flights have been interrupted. Earlier this year, Ethiopian authorities expelled a French journalist after her reporting trip to Tigray, and temporarily revoked accreditation for three Reuters journalists following a separate investigation, before restoring it months later. Press-freedom organizations have documented pressure on Ethiopian reporters, as well. This doesn’t mean all official statements related to this conflict are false. It means there are fewer independent witnesses able to confirm them, and fewer ways for people living near the fighting to tell the outside world what they are seeing. During the last Tigray war, communications blackouts helped create conditions in which rumors traveled faster than verifiable accounts, and those same risks are present now. Journalists and researchers can sometimes use satellite images, hospital records, interviews with people who have fled, and statements from the parties to build a picture of what happened. But a hospital can confirm that people were wounded without knowing who fired the weapon. A satellite image might show damage without revealing who caused it. And an eyewitness can describe a blast without being aware of a drone flying overhead. That said, we can note a few things with reasonable certainty. The diplomatic expulsions and embassy closure were public government decisions. Fighting has resumed. Medical teams are treating many more people with war wounds, and civilians who survived the previous war are once again facing displacement and interrupted services. Uncertainty about who fired a weapon in Addis Ababa doesn’t make those events uncertain, it just keeps us from having a complete picture of the context surrounding those confirmed elements. Let’s talk for a moment about why there’s concern about this conflict, which is inside Ethiopia, possibly spreading beyond its borders. With Eritrea, the central issue is the Red Sea. Ethiopia is a large, landlocked country that depends on ports in neighboring states for access to global trade. Abiy has argued that reliable access to the sea is vital to its economy

This week we talk about EU membership, trade deals, and association. We also discuss Australia, Ursula von der Leyen, and Brussels. Recommended Book: Being You by Anil Seth Transcript Just off the coast of Newfoundland, there’s a small group of islands that belongs to France. Saint-Pierre and Miquelon are close enough to Canada that, at their nearest point, the two countries are separated by only a few kilometers of water. In September, Canadian Prime Minister Mark Carney met French President Emmanuel Macron on these islands. The two leaders could stand on French territory and talk about a partnership with the European Union, while Canada was visible across the water. A few days earlier, European Commission President Ursula von der Leyen had made a similar, but possibly more significant proposal. Speaking before the European Parliament, with Carney in the room, she said she wanted to open the door for Canada to become the EU’s first “associate member.” Depending on which headline you read about the statement, this may have sounded like Canada might be joining the EU, joining it partway, or joining an entirely new version of it. Soon after, Australia’s trade minister said his country was “on the same page” as Canada regarding closer ties, and the European Parliament’s president then suggested Australia and New Zealand might follow Canada’s lead. Now, despite all those headlines and interpretations, there’s one problem with all these stated ambitions: the European Union does not have an established category called associate member. No one has agreed on what rights or obligations an associate member country would have, and figuring that out—and getting some kind of resolution passed—would be necessary for anyone, including Canada and Australia, to get closer in that way with the EU. What I’d like to talk about today is why this proposal was made, what it could mean if it eventually becomes more concrete, and whatever happens, what these statements tell us about the way global alliances are changing. — The EU has 27 member countries, but there are already a few different ways to be connected to it. Full member nations help write EU law and send representatives to its institutions. They all participate in the single market, which means goods, services, money, and people can move across member nation borders under shared rules. The single market is distinct from the customs union, which sets common tariffs on goods imported from elsewhere. Both are distinct from the Schengen area, which removes most routine passport checks between participating countries. And nations that use the euro are another group entirely. These arrangements tend to overlap, but they’re not the same thing, and membership in one does not automatically mean membership in all the others. There are also countries outside the EU that participate in some of its systems. Norway, Iceland, and Liechtenstein belong to the European Economic Area and are part of the single market. To do that they have to accept many EU rules, although they don’t vote on those rules as that would require full EU membership. Switzerland has built its own set of bilateral arrangements with the EU. And Britain, after leaving the union, has also negotiated a special trade and cooperation agreement with it. So there are precedents for a country having a deep relationship with the EU without being a member. But there’s no ready-made ‘associate’ slot that Canada can just step into. There’s a legal distinction here, too. The EU treaties say that a European state can apply to become a member, and Canada is not a European state. The treaties separately allow the EU to make association agreements with countries outside the bloc, and it already has many kinds of agreements with external partners. An association agreement, though, does not make that partner a member of the Union. “Associate member” could eventually become a useful name for a new collection of rights and obligations held by nations outside those existing parameters. For now, though, it’s a political invitation and a negotiating idea, not a defined legal status. All that said, Canada isn’t starting from scratch on this. Its trade agreement with the EU, called CETA, has been applied provisionally since 2017. Most of it is already in effect, though ten EU countries still haven’t completed the ratification required for the whole of the agreement to go into force. CETA removes most tariffs and opens some opportunities for companies on each side, but it doesn’t make Canada part of the single market. A Canadian product can be easier to sell in Europe without a Canadian worker gaining a general right to take a job there. That’s part of the distinction between a trade deal and the sort of relationship people sometimes imagine when they hear the phrase “union membership.” Canada also joined Horizon Europe, the EU’s major research funding program, in 2024. It has a security and defense partnership with the EU, and it became the first country outside Europe to join an EU defense financing initiative called SAFE. That means some of the proposed future relationship already exists, but in pieces rather than as a unified whole. The question is whether those pieces can be connected and extended into something much more ambitious and holistic. Now, important to understanding the why of all this is understanding Canada’s relationship with the US, and how that relationship has been fraying, of late. Canada’s economy is deeply integrated with that of the United States. Its proximity to the massive US market has brought enormous benefits, but it also means a change in American trade policy can have an immediate and dramatic effect on Canadian businesses. President Donald Trump’s tariffs and repeated suggestions that Canada should become the 51st state have made that dependence more than a little politically uncomfortable. For Carney, a closer European relationship offers a way to reduce the risk of having too many economic and security decisions shaped by one increasingly unpredictable and at times belligerent neighboring country. Europe has its own reasons to be interested in closer ties. Canada has energy and critical minerals, industrial capacity, research institutions, and a role in the Arctic. Both sides also support Ukraine and work together through NATO and other forums. Von der Leyen has proposed cooperation with Canada on batteries, artificial intelligence, cybersecurity, advanced manufacturing, and defense production. Carney has added ideas about financial services and opportunities for young people to live, work, and study across the Atlantic. This isn’t a plan to move Canada’s economy from one continent to another. Geography still matters. A car part crossing the US-Canada border may be part of a production chain built up over decades; a new trade agreement with Europe doesn’t instantly recreate or replace that chain. But diversification doesn’t require replacing one partner with another. It can mean having additional buyers, suppliers, research collaborators, and sources of investment, so that a disruption in one relationship is less damaging. The costs and limits matter here, too. Canadian opposition leader Pierre Poilievre has warned that deeper EU ties could mean higher costs and Canadian industries being regulated from Brussels. His motives in bringing this up are likely at least partly political, but it’s a question worth asking: if Canada wants more access to a tightly regulated European market, which European standards would it have to accept as a tradeoff? Europe would face its own questions. EU governments have spent decades building shared rules among countries that accept reciprocal obligations. They may not want to give a distant partner the benefits of those standards without comparable commitments. The fact that ten member states have yet to ratify the existing Canada trade agreement is a reminder that closer ties require more than an enthusiastic speech from the Commission president; there are real, practical realities to consider, here. If something like this were to move forward, we don’t yet know whether the final result would be one major agreement or a series of smaller ones. The latter might be easier to negotiate: a defense arrangement could advance while mobility or food standards remain unresolved, for instance. But calling the package an associate membership could also raise expectations that every difficult issue will be solved at once, which probably isn’t realistic. And none of this automatically grants Canadians the right to settle anywhere in the EU, or Europeans the right to settle in Canada. Carney has talked about expanding opportunities for young people, but the scope of any mobility arrangement would have to be negotiated. A youth work or study program would be a very different proposition from full freedom of movement. And as all of this has played out, Australia has watched with interest. Australian Trade Minister Don Farrell said Australia and Canada were “on the same page” about building stronger ties with Europe, and that he would watch what Carney did. Then European Parliament President Roberta Metsola named Australia and New Zealand as examples of countries with which the EU could deepen its relationship. Those remarks generated another round of headlines about countries joining Europe, but as with Canada, things are more complicated than most of the reporting on this would suggest. Australia and the EU finished negotiating a free trade agreement earlier this year, but it still has to be signed and brought into force. They also have a security and defense partnership and have discussed bringing Australia into Horizon Europe. At a September meeting, their leaders focused on those steps, along with potential agreements related to critical minerals and technology. All of which illustrates the difference

This week we talk about lobbying, renewables, and the NRA. We also discuss implied threats, midterm elections, and political action committees. Recommended Book: Sunward by William Alexander Transcript For much of the late 20th century and the first few decades of the 21st, one of the most feared interest groups in US politics was the National Rifle Association, the NRA. Its power came from a large and politically engaged membership, a mailing list, a grading system that reduced complicated voting records to a letter, and a reputation for ending political careers over specific votes. Once it attained that reputation, the NRA didn’t have to defeat every politician it disagreed with. Members of Congress only had to believe it could defeat them, and that belief shaped races in which the group spent nothing; politicians went out of their way not to anger the NRA. Money can buy an advertisement or a meeting. What tends to change a vote is the expectation that one choice will be rewarded and another will carry consequences. The NRA’s influence has declined following internal scandals, financial trouble, and the growth of well-funded gun-control groups. But its model remains potent: pick a few visible fights, and allow your reputation to do a lot of the work for you, in the future. In 2010, the Supreme Court’s Citizens United decision, alongside a related appeals-court ruling later that year, helped create the modern super PAC: a political committee that can raise and spend unlimited sums advocating for or against candidates, so long as it does not coordinate that spending with their campaigns. This did not eliminate the effort and resources required to build influence, but it meant a few wealthy donors, a competent team, and some carefully selected races could establish a reputation in months rather than decades. In 2026, solar, wind, and batteries are projected to account for about 93% of new utility-scale electrical generating capacity added in the United States. That doesn’t mean they provide 93% of the country’s electricity—natural gas remains the largest source in the US—but these technologies are now the overwhelming majority of what the industry is building. Despite that growth, in 2025 Congress passed a law that sharply rolled back federal support for much of the clean-energy industry, and most of the politicians who voted for those rollbacks appeared to suffer no political consequences for doing so. What I’d like to talk about today is the effort to build a feared clean-energy lobby, how it has influenced a series of Republican primaries, and what its early successes do and do not tell us about the role of money in American politics. — The One Big Beautiful Bill Act, or OBBBA, was signed into law on July 4, 2025. For wind and solar projects, the new law generally ended production and investment tax credits for facilities placed in service after December 31, 2027, unless construction began within twelve months of the bill’s enactment. That twelve-month window closed in July of 2026, and a subsequent executive order directed the Treasury Department to adopt a stricter definition of when construction actually begins, further clamping down on entities hoping to benefit from those now-defunct credits. Tax credits for electric vehicles and residential efficiency upgrades ended in 2025, while support for clean hydrogen was curtailed. Other technologies, including batteries, nuclear power, and geothermal energy, were treated differently, so it would be misleading to say the law eliminated every federal clean-energy incentive, though it did severely curtail a lot of renewables-oriented industries and construction in the US. Republicans have generally been more supportive of fossil-fuel production and more hostile to federal wind and solar subsidies, while Democrats have generally taken the opposite position. There are important regional exceptions, especially among Republicans whose districts have attracted manufacturing plants, wind farms, and other energy investments. Several Republican lawmakers have even written letters asking party leaders to preserve some of the credits, in part because projects and jobs in their districts depended on them. When the final vote arrived, though, nearly all congressional Republicans voted for the bill. Tom Matzzie, the founder of the retail electricity company CleanChoice Energy, previously worked for Democratic campaigns and served as the Washington director of the progressive organization MoveOn.org, so he was familiar with electoral campaigning as well as the energy industry. In the wake of the passing of the OBBBA, he posed a question to Canary Media, possibly alluding to the success of political interest groups like the NRA when he said, “Are we someone that people can hurt without consequences?” Matzzie recruited Chris Larsen, the billionaire co-founder of the blockchain company Ripple and an investor in clean energy, and Michael Brune, the former executive director of the Sierra Club, and together they formed the Invest in Tomorrow Coalition, or ITC, an acronym that also evokes the investment tax credit the group was organized, in part, to defend. Federal Election Commission records show that the coalition raised about $6.8 million during the first half of 2026. Larsen provided $6 million, while the organizers said they had assembled commitments of around $20 million and hoped to spend as much as $30 million during the election cycle. Matzzie called the group’s candidate-targeting spreadsheet the “Revenge Tour Matrix,” which is an unusually candid name for a political document. The group’s most interesting strategic decision, though, is arguably that its advertisements generally did not mention clean energy. When ITC opposed Texas Representative Chip Roy in the Republican runoff for state attorney general, its ads questioned Roy’s loyalty to President Trump. When it opposed Tennessee Representative Andy Ogles, it created a website called Lyin’ Andy that focused on his missed votes and a federal investigation into his campaign-finance reporting. The coalition openly identified its reason for entering these races, but its advertisements used whatever campaign research suggested would move primary voters, not what its donors wanted them to think about solar panels. This approach was especially well suited to Republican primaries, where relatively small electorates can be reached through a concentrated group of conservative television, social-media, and streaming outlets. In Ogles’ race, for instance, the two campaigns had each spent roughly $600,000, while ITC spent around $2 million attacking Ogles and introducing voters to his challenger, Charlie Hatcher. The coalition describes its record so far as five wins in five races. In May, Roy lost the Texas attorney-general runoff by 10.4 percentage points. In June, Iowa Representative Mariannette Miller-Meeks, a Republican who had defended renewable-energy interests in Congress, survived her primary with help from ITC, including a $125,000 contribution. Later that month, South Carolina Representative Ralph Norman finished a distant third in the Republican primary for governor after the coalition opposed him. In August, Ogles lost his primary by more than six points despite an endorsement from Trump and more than $700,000 from the House Freedom Caucus’ political fund. And in late August, Norman lost a second race, this time a Republican Senate primary, to Darline Graham, the sister of the late Senator Lindsey Graham. ITC spent about $1 million in that contest, which Norman lost by five points. The reactions from Norman and Ogles were almost as useful to the group as the election results. Norman blamed outside political spending in his concession speech, while Ogles, before his loss, said the coalition was attempting to make an example of him and that could have a chilling effect on other conservatives in Congress. Those statements do not prove ITC caused either defeat. But they do advertise the consequence the organization wants other politicians to anticipate; come after clean energy investment and they’ll come after you. This strategy is notable because it separates political deterrence from public persuasion. It does not need Republican primary voters to become enthusiastic about solar tax credits. It just needs politicians to believe that aggressively attacking solar companies could make their next primary more difficult. The ads questioning Roy’s loyalty to Trump are probably the clearest version of this distinction. The message voters received and the policy outcome the donors wanted were almost entirely unrelated, and that was intentional. It’s worth mentioning here that the power of a wealthy individual to shape a low-turnout primary does not become less concerning because the spending supports a technology someone likes. The same rules are available to fossil-fuel companies, cryptocurrency investors, labor unions, and ideological groups of all kinds. That said, Ogles entered his primary with several liabilities unrelated to energy policy, including controversial public comments, questions about his finances, and a district whose boundaries had changed. Darline Graham had Trump’s support in her race against Norman. In Texas, the coalition’s roughly $1.7 million in spending was substantial, but the winning campaign spent nearly $25 million and Roy’s campaign spent around $12 million. Roy dismissed the coalition’s influence and said he would take the same positions again. Matzzie’s response to all this is, more or less, that proof of causation is unnecessary: if lawmakers believe the coalition can hurt them, the deterrent works. That may be true, but it makes the group’s claim difficult to test. The measurable outcome is that five races ended the way the group preferred, but it’s currently unknown, and maybe unknowable, how much responsibility the group can clai

This week we talk about AI agents, cyberattacks, and insurance claims. We also discuss OpenAI, Hugging Face, and policy language. Recommended Book: The Stars My Destination by Alfred Bester Transcript Two broad categories of cyberattack have become especially visible this year, and only one of them requires a human attacker in the loop to choose the target. In March, hackers linked by the US government to Iranian intelligence broke into the medical-device manufacturer Stryker and remotely wiped tens of thousands of employee devices. The attack disrupted the company for days, affected its first-quarter earnings, and represented a shift from somewhat more subtle espionage toward more overt and deliberate destruction. Elsewhere, the market-research company Klue sat at the center of a breach affecting close to 200 customers. Attackers used an old credential to gain access to keys for customers’ cloud services. These incidents had people with recognizable motives behind them, and that sort of hack has become increasingly rare over the past decade or so: Black Kite counted 7,551 publicly disclosed ransomware victims over its latest twelve-month reporting period, alone, about 25 percent more than the year before. Then, over the course of about five weeks this summer, OpenAI, Anthropic, and Meta each disclosed incidents in which their AI models gained access to real computer systems they were not supposed to touch. The incidents were not identical, and describing all of them as escapes wouldn’t capture the important nuance of the situation. Anthropic and Meta said their models reached the internet because a third-party evaluation environment had been misconfigured. The models had been told they were operating inside a simulation, and their internal dialogues indicate they interpreted the real systems they encountered when they left that environment as simulated components of that exercise. OpenAI’s incident, however, was a bit different. Its models were being tested using ExploitGym, a benchmark intended to measure their ability to find and exploit software vulnerabilities. Internet access was supposed to be blocked, but the models discovered and exploited vulnerabilities in a package-registry service inside OpenAI’s research infrastructure, found a route to the open internet, and, as I related in a previous episode, eventually compromised the production systems of the AI platform Hugging Face. Since that episode, OpenAI has release a more complete postmortem, which they published in August, and which says the activity was primarily driven by an internal research model comparable in scale to GPT-5.6 Sol, though Sol participated in parts of the incident. The agents created an improvised message board inside the package manager, exchanged discoveries, divided up work, and sometimes described themselves as a swarm. At Hugging Face they executed code on dozens of servers, obtained broad access to several clusters, and exposed credentials associated with databases, cloud services, code repositories, and internal communications. Hugging Face reconstructed around 17,600 actions over a campaign lasting about four and a half days, including roughly two and a half days inside its own infrastructure. Notably, these AI agents were not trying to steal money or damage Hugging Face. They inferred that the company might possess the solutions to the benchmark, to the problem they were tasked with solving, and they went looking for them. They were, in effect, cheating on a test, looking for solutions to the problems rather than taking the test, as intended. That doesn’t mean the models had motives in the human sense. People created the evaluation, reduced the normal safeguards, and assigned an offensive task. But no operator selected Hugging Face or directed the individual steps; that was a path the AI decided to take all by itself. Anthropic’s review subsequently found three incidents among more than 141,000 evaluation runs for its own models. In one, a model unable to reach its fictional target scanned around 9,000 real ones, compromised an internet-facing application using an exposed password and SQL injection, then stopped after recognizing that the host was real. Another model published a malicious package to the real Python Package Index because it believed the registry was simulated. Fifteen outside systems downloaded and ran that malicious package before it was removed. Meta then disclosed that one of its models had reached the internet through a misconfiguration at the same evaluation vendor and exploited a vulnerability at an unnamed third party. No significant financial damages have been publicly reported from these events, by attacker or victim. But if there had been damages, who would have paid for them? What I’d like to talk about today is how autonomous AI systems complicate cyber insurance, how insurers have handled equally unfamiliar risks in the past, and why insurance contracts may soon become one of the more important forms of AI governance. — A typical cyber-insurance policy covers a broad portfolio of costs. These can include ransom payments, forensic investigations, legal expenses, restoring systems and data, notifying customers, and compensating victims and possibly a victims’ customers for the revenue lost while a company’s operations are interrupted. Business interruption is often one of the largest portions of a claim, and policies can respond to malicious attacks as well as non-malicious failures. This market grew by more than 30% a year between 2017 and 2022, as ransomware, a type of attack that became a lot more common during that period, in part because of increased automation and a franchising model that became really popular and increased the reach of the most powerful ransomware tools, almost broke this industry. In 2021, attacks on Colonial Pipeline, the insurer CNA, and meat processor JBS produced multimillion-dollar ransom payments and costly disruptions. Insurance prices surged, sometimes by more than 100%, while some companies found they could not obtain coverage because insurers just couldn’t make the numbers work for them. Insurers responded to this more complex hacking environment by raising prices, but they also made coverage conditional on specific defenses. Companies increasingly had to demonstrate that they used multifactor authentication, endpoint monitoring, restricted administrator access, and backups that attackers could not alter, as a baseline. Loss ratios then fell, more insurance capital entered the market, and prices eventually came down again, stabilizing after that frantic and uncertain period. According to Marsh, global cyber-insurance rates fell 4% in the second quarter of 2026, the twelfth consecutive quarterly decline. Primary pricing is now about 42% below its 2022 peak. The market is not necessarily becoming safer, though. US cyber premiums reached about $7.5 billion in 2025, while the share of premiums consumed by claims rose to 53%—the first time it ticked above 50% since the pandemic-era ransomware surge. Globally, Munich Re estimates the market was worth nearly $15 billion last year and could approach $28 billion by 2030. During this period, insurance applications have also become a consequential part of a company’s security system. In one particularly clear example, Travelers rescinded a million-dollar policy after a ransomware claim revealed that the customer’s multifactor authentication protected only its firewall, despite application answers saying the control was used much more broadly. Companies that don’t live up to cyber insurance expectations can thus be left in the lurch, so in a very real way, insurers have helped make multifactor authentication a standard business practice by attaching a price to its absence. This industry could move faster than regulators because they didn’t have to ban insecure behavior and pass legislation to make that happen; they just had to decline to insure anyone who didn’t live up to their basic security standards, which left those who failed to implement such precautions without insurance, should they be targeted by hackers. That same mechanism is now being aimed at AI agents, but the big initial problem everyone is facing is definitional. Most cyber policies are written around some identifiable security event: an outside attacker breaks in, an employee steals information, a credential is used without authorization, or malicious software takes a server offline. What if, though, a company gives an AI agent access to its network so that the agent can find and repair security vulnerabilities? And then maybe the agent discovers a vulnerability, exploits it, moves laterally into systems it was not expected to touch, and exposes sensitive data. There is a cyber loss, but there may be no conventional attacker and no stolen credential. The software was invited in and may have used permissions it was explicitly given. This is very different from a human-led hack, but it still has the potential to cause a lot of monetary damage. Insurers including MSIG, QBE, and Beazley are reviewing how their policy language applies to these scenarios and who bears responsibility when an agent’s autonomous actions cause damage. For now, most of them are clarifying the parameters of their coverage rather than excluding AI events entirely. QBE’s global head of cyber described AI as “a risk amplifier, not a fundamentally new cyber risk.” In other words, if an AI system causes something that looks like an ordinary covered breach, the involvement of AI probably won’t put it in a different category; it’ll still be covered. The trickier cases involve an agent that works as designed but makes an expensive decision, or a systemic event in which a model or AI platform produces losses at many companies simultaneously. The first type might be treated as professional liability, or errors and omissions, rather than a cybe

This week we talk about money policies, yield curves, and government bonds. We also discuss the Fed, the Treasury Department, and a WWII accord between them. Recommended Book: Paved Paradise by Henry Grabar Transcript In April of 1942, a few months after the United States entered World War 2, the US Treasury Department asked the Federal Reserve to help it borrow a truly staggering amount of money, and as cheaply as possible. The Fed agreed, committing itself to holding short-term Treasury bill rates at three-eighths of 1%, while also capping the yield on long-term government bonds at 2.5%. This was a type of yield curve control. Rather than allowing the market to decide how much interest the government would pay, the Fed decided that price and promised to enforce it. That helped finance the war, because the Treasury knew its borrowing costs wouldn’t spiral out of control at a moment when it needed to spend unprecedented sums on ships, planes, weapons, soldiers, and all the other machinery of an ongoing global conflict. The downside was that the Fed lost control of an important monetary policy lever. Bond prices and yields move in opposite directions, so keeping yields below a certain level meant the Fed had to stand ready to buy bonds whenever their prices dropped. It couldn’t decide in advance how many it would buy, or how much money it would create in the process. The market would thus forth decide that, instead. Consequently, the Fed became, in some ways, an extension of the Treasury’s debt-management operation, its inflation-related responsibilities made secondary to the government’s need for cheap financing. That arrangement persisted after the war ended, despite the return of inflation, and President Harry Truman’s administration pushed to maintain it during the Korean War, as well. Fed officials resisted, though, with inflation running at more than 8%, and after a very public, very contentious standoff, on March 4, 1951, the Treasury and the Fed announced that they had reached what became known as the Treasury-Fed Accord. That agreement did not make the Fed independent all at once, but it established the principle underlying the modern relationship between these institutions: the Treasury manages government borrowing, while the Fed sets monetary policy based on inflation and employment, not on how much that policy costs the government. The market, in other words, would once again be allowed to decide the price of long-term US debt. What I’d like to talk about today is what happens when that price goes up, what’s pushing long-term US borrowing costs toward levels we haven’t seen in decades, and why two people appointed by the same president are pulling in opposite directions on this issue. — The Federal Reserve’s primary interest-rate lever is the federal funds rate, which is the overnight rate banks charge each other to borrow money. The Fed currently targets a range of 3.5 to 3.75 percent for that rate, and while it has other tools, this is the number people are usually talking about when they say the Fed raised, cut, or held rates. The Fed does not directly set the yield on 10- or 30-year Treasuries, though. Those securities are sold at auction and then traded in a huge secondary market, and their yields reflect a combination of what investors expect inflation to look like, where they think short-term rates will go over the life of the bond, and what’s called the term premium. The term premium is basically extra compensation for uncertainty. If you lock up your money for 30 years instead of rolling over short-term debt, you accept the risk that inflation, growth, government policy, and other variables will change in ways that make your bond less valuable over that thirty year period. The more uncertain the future seems, the more compensation you’re likely to demand. And again, when demand for a bond falls, its price falls and its yield rises. When we say yields are rising, that means borrowers have to offer investors, the people and institutions giving them the money they want to borrow, more money, more interest, to convince them to buy those bonds. That doesn’t only affect the government. The 10-year Treasury serves as something like a reference rate for the entire economy, influencing mortgages, business loans, and the value of long-lived assets. As of September 3 of 2026, the average US 30-year fixed mortgage rate was 6.71%, up from 6.5% a year earlier. That increase is the result of yield increases in the bond market. Long-term Treasury yields have been climbing for much of 2026, and that climb accelerated over the summer. The 30-year yield reached about 5.31 percent on August 17, its highest level since 2007. A few days earlier, the Treasury sold 30-year bonds at a yield of 5.216%, the highest borrowing cost at one of those auctions since 2001. The 10-year yield briefly hit about 4.81% this past week, its highest level since early 2025, and ended Friday at about 4.78%. The two-year yield, which tends to track expectations about contemporary Fed policy more closely, ended at about 4.37%. There isn’t one clean cut reason for these yield bumps. Instead, there are a bunch of forces pushing in roughly the same direction. The first is government borrowing. The Congressional Budget Office now expects a roughly 2.1 trillion dollar federal deficit this fiscal year, which is 200 billion dollars more than it projected in February. Covering that gap means issuing more debt, and more supply generally means the Treasury has to offer a better return to attract enough buyers. The second is competition from corporations, especially technology companies borrowing to build AI infrastructure and data centers. The Dallas Fed estimates that AI-related investment-grade bond issuance—these companies borrowing money, in the form of bonds, to help build more data centers and other AI-enabling stuff—could total around $300 billion this year, creating long-duration debt equivalent to about an eighth of what the Treasury is expected to issue. Some of the companies selling this debt have extremely strong balance sheets and high credit ratings, so investors who want safe-ish, long-term bonds suddenly have a lot more options, and the US government has to compete with that for a finite pool of investor resources. Third, oil prices have surged following renewed strikes and attacks around the Strait of Hormuz, with US benchmark prices recently climbing above $90 a barrel. More expensive energy can goose inflation across the economy, which makes locking in a fixed return for 10 or 30 years less appealing, because those yields might not keep up with the practical devaluation of the dollar. Fourth, that aforementioned term premium has risen as investors ask to be paid more for uncertainty related to inflation, deficits, geopolitics, and future Treasury issuance. And fifth, the pool of buyers is changing. Foreign investors still own trillions of dollars in Treasuries, but private foreign demand for notes and bonds fell sharply in June, even as corporate bonds attracted more of that finite sum of money. A big shift we seem to be seeing here is that some investors seem to be judging Treasuries less as a bet on the next Fed meeting, and more as a long-term bet on whether the US political system can manage its finances. And that shift is showing up at an awkward moment for the two institutions involved in the 1951 Accord. Kevin Warsh, who became Fed chair in May, used his August 28 speech at Jackson Hole to say that although inflation expectations remain anchored, the Fed still has work to do if underlying inflation is not moving toward its target quickly enough. Markets read that as a warning that a rate hike could be coming, and the unexpectedly strong August jobs report reinforced that interpretation: employers added 162,000 jobs, far more than economists anticipated, while estimates for June and July were revised upward. The Treasury Department, meanwhile, is moving in the opposite direction. On August 19, Treasury Secretary Scott Bessent announced that the government would at least double the size of its long-term bond buybacks, from a maximum of 2 billion dollars to at least 4 billion dollars per operation, beginning September 9 and continuing through November 4. The stated purpose is to improve liquidity, buying older, less frequently traded 10- to 30-year securities. But buying long-term bonds also reduces the supply available to investors, boosting prices and putting downward pressure on yields, which is why Bessent has referred to the approach as a “Treasury twist.” The scale is small in the context of a $40 trillion national debt, and analysts have described it as more signal than substance. It is nonetheless a striking signal: one Trump appointee is telling markets that higher short-term rates may be necessary to control inflation, while another is using the Treasury’s balance sheet to push long-term rates in the other direction. These jobs, which again, were separated in 1951, are working against each other. And this matters, first, because long-term government debt is the foundation upon which a lot of other prices are built. When a 30-year Treasury yields more than 5%, companies refinancing debt have to pay more, commercial real estate becomes harder to finance, mortgages become more expensive, and investors have less reason to pay extremely high prices for stocks based on profits those companies might earn many years from now. It also matters because interest on the federal debt has become one of the government’s largest expenses. Gross interest expense reached about $1.17 trillion during the first ten months of fiscal 2026, up about 15% from the same period last year. The somewhat narrower CBO measure of net interest reached $963 billion over that span, roughly level with Medicare spending and greater than defense spending. This creates a potentially self-reinforcing loop: high

This week we talk about peaker plants, blackouts, and at-home battery backups. We also discuss energy resiliency, solar panels, and hydro. Recommended Book: The Tainted Cup by Robert Jackson Bennett Transcript Peaking power plants, often just called peaker plants, are power plants that are turned on only during periods of high energy demand. That’s in contrast to a baseload power plant, which operates more or less 24/7 to ensure there’s a steady amount of electricity available on the local power grid. The need for peak-load energy varies depending on the time of year and which part of the world you’re looking at. In general, though, energy demand tends to increase in the morning and evening because of temperature fluctuations and lifestyle rhythms. People are at home in the morning and return from work in the evening, at which point they turn on their ACs or heaters, TVs, lights, electric kettles, and video game consoles. That leads to an irregular surge in demand compared with the steady office and factory demand met throughout the day by the baseload power plant. When energy demand peaks, approaching or exceeding what the baseload plant can reliably provide, the peaker plant is spun up and more energy is added to the grid. This helps avoid brownouts and blackouts, situations in which people lose access to power because there isn’t enough to go around. This also helps stabilize energy prices. In most countries, pricing is used to manage scarce energy resources, so as a grid approaches the point where it’s running out of available electricity, prices rise to incentivize less energy use. Peaker plants keep those prices from going sky-high by increasing the supply, preventing demand from pushing prices into absolutely ridiculous territory. Some peaker plants operate for a handful of hours basically every day. This is especially true in places with extreme temperature fluctuations, or in areas where the population or manufacturing activity has increased rapidly and the local infrastructure hasn’t caught up. In those places, the backup plant is used more regularly because the baseload supply hasn’t yet increased to meet that new, consistently higher demand. Peaker plants are often less efficient to run because they aren’t meant to be used all the time. Consequently, if the baseload power plant isn’t capable of providing enough energy for a region on a regular basis, electricity can get much more expensive for everyone, all the time. A power plant intended for occasional use is instead operating constantly, and it wasn’t built to be efficient. It was built to come online quickly and operate only during periods of irregular, excessive need. What I’d like to talk about today is an alternative to peaker plants that was conceived of decades ago, but which has only recently started to be deployed at scale in some areas. — As I mentioned in the intro, a peaker power plant is meant to be turned on irregularly to meet above-average energy needs. Those periodic pops in demand are accounted for, and peaker plants are built specifically to meet them. As a result, these plants are typically more expensive and often more polluting than baseload plants, with many using natural gas or coal to produce extra electricity for the grid. In the late 1990s, researchers proposed that it might someday be possible to link energy-production and storage sites together, creating a more flexible grid system they called a virtual power plant. Further research in the early 2000s expanded on the concept, looking specifically at renewable-energy options and how they might be aggregated into a similar virtual-power-plant setup. The basic idea is to recreate the effect of a peaker plant—adding electricity to the power grid when it’s most needed—by aggregating power-generating or storage assets and tapping them only when necessary. Software manages that aggregation of smaller assets, ensuring the additional energy reaches the grid when it’s needed and at the necessary scale. Managing these assets in this way allows smaller production and storage infrastructure to recreate the impact of a larger peaker plant. A German energy company called RWE launched the first real-world virtual power plant in 2008, linking nine of its hydroelectric plants into a virtual 8.6 MW unit whose output could be managed and deployed remotely. A few years later, in 2011, a Swiss energy company called Kraftwerke did the same with a slew of biogas, solar, and wind-power infrastructure scattered across seven countries. The concept expanded to include demand-side residential energy assets in 2016, when the Australian city of Adelaide enacted a program backed by the Australian Renewable Energy Agency. The program deployed 1,000 battery systems to homes and businesses across the city. Those battery systems were hooked up to solar panels, and the software managing the batteries allowed their stored energy to act like a 5 MW peaker plant. Tesla then applied the same general idea across South Australia, where energy prices had long been volatile, beginning in 2018. That program reached 50,000 homes by 2022. It was acquired by an energy company called AGL in 2025, which expanded it further until the virtual power plant had a capacity of 25 MW of peaker solar energy and 37 MW of battery-stored peaker energy. Now, again, there’s a certain amount of energy available on the grid from standard baseload production sources, including traditional coal- and gas-fired power plants, hydroelectric plants, and nuclear power plants. Solar and wind arrays also contribute to the baseline energy load in some parts of the world. That baseline can be augmented by utility-scale battery facilities that store excess wind and solar production. This makes renewables more reliable as baseload options because excess energy generated during the day or during especially windy periods can be stored in those batteries and used later, at night or when the wind isn’t blowing as hard. A VPP addresses periods when the available baseload supply doesn’t measure up to current demand. When temperatures are especially high and everyone is using their air conditioners more, and a gas plant or solar array can’t provide enough electricity to meet demand, the company operating the virtual power plant can draw energy from scattered resources to cover that additional use. In some cases, that means pooling energy generated by small hydroelectric dams. In others, it means drawing a previously agreed-upon amount or percentage of energy from a homeowner’s battery backup. Maybe they have a battery that stores excess electricity from their solar panels, which they can use at night. They might also have an agreement with the VPP operator allowing it to draw a certain amount of energy from that battery when necessary, adding it to the grid to ease excessive demand. This kind of agreement is often beneficial for the homeowner sharing some of their excess energy with the grid to help prevent blackouts and excessively high prices. The cost of the battery installation and hardware might be subsidized, or they might make a small amount of money every time that energy is borrowed. There are also variations on this model that provide the homeowner or renter with a fancy thermostat. During periods of high demand, the thermostat might automatically adjust the AC by a degree or two when the grid is being crushed by demand on crazy-hot days. This ensures there’s enough energy to go around by reducing demand rather than increasing supply. Some models also use energy-pricing arbitrage, automatically selling stored energy when electricity is expensive and buying it back when electricity is cheap. This helps balance the grid’s overall energy load by contributing to it when energy is scarce and expensive, then restoring that energy to the battery when it is abundant and cheap. Increasingly, these systems tap into other resources connected to the grid to reduce demand or increase supply. They might borrow some energy stored in a homeowner’s electric vehicle, for instance, which has been left plugged in to charge but can also act as another, quite large, household battery. Or they might reduce the power being sent to heat pumps or water heaters. Each of these devices or other assets is treated as part of the larger virtual power plant, which may be composed of thousands or tens of thousands of homes and all their connected assets. This helps manage supply and demand so that blackouts and dramatically higher energy prices are less likely, even on days with bizarre weather or when larger energy assets, like power plants, aren’t operating at full capacity. This is a huge win for resiliency, and it’s also often much cheaper than installing and operating a peaker plant, usually around 40–60% cheaper. These systems can also be installed and activated much faster than a full-on power plant, while dramatically reducing the amount of land used for energy infrastructure and the bureaucracy that has to be traversed to get something like a power plant or solar array installed and operating. Those big chunks of infrastructure can take years or decades to bring online, while a VPP can often be up and running within just a few months. It usually requires no new land and no new interconnections in terms of cables or whatnot. It uses infrastructure that’s already there in most cases, though it can also be strengthened by deploying assets, like household batteries, that are useful to the homeowner for other reasons. Kind of a win-win. At the moment, virtual-power-plant capacity is limited primarily by regulatory approval, at least in most countries. Energy utilities don’t have much incentive to move these systems forward because they get paid for building and managing traditional power assets, and VPPs are not that. Sometimes an energy company will run this type of program, but usually only if it gets to sell t

This week we talk about borders, trade wars, and belligerence. We also discuss Trump’s tariffs, inflation, and nationalism. Recommended Book: Vulture Capitalism by Grace Blakeley Transcript The US and Canada share the longest international border in the world, totaling more than 5,500 miles, or nearly 8,900 km. The specific details of this border have changed over the decades, but the current delineation was largely in place following the San Juan Islands water arbitration of 1872, which brought a 12-year joint military standoff between the US and Great Britain, known as the Pig War, to an end, and fed into a 1908 legal framework that relied on modern mapping of the entire frontier, which led to the precise cartography of the current international border between the US and Canada. Since then, after some issues with gold rush-era land rights were figured out in Alaska, and some treaties were signed regarding the disarmament of the Great Lakes, things have been pretty calm along this massive border. Trade hasn’t always been the most efficient and free—the early 20th century in particular was pretty fraught in this regard, as Anti-Americanism raged through Canada. That led to a dismissal of a proposed lowering of trade barriers by the Canadian Liberal government in 1911, anti-American sentiment flogged by the Conservatives, who rode their slogan, “No truck or trade with the Yankees,” to a Canadian nationalism-powered victory. After the US entered WWI and the Allies tallied a victory, though, the US and Canada exchanged their first ambassadors, Warren Harding became the first US President to make an official visit the confederated Canada, visiting Vancouver in 1923, and things between these two countries were looking pretty good until 1930, when the US passed the Smoot-Hawley Tariff Act, which was a protectionist trade act that, among other things, raised tariffs on incoming Canadian goods in order to protect competing American business interests; making the local offerings artificially more competitive than the stuff coming in from Canada, basically. The Canadian government hit back with their own higher tariffs and shifted more of their trade to other Commonwealth nations, which led to a decrease in trade between the US and Canada of about 75%; and this was happening during the Great Depression, which is why that Act was enacted, the US government was hoping to bolster their own economy, but instead of helping, it furthered those economic difficulties, because of that drop in trade and international custom—Smoot-Hawley is generally considered to have been an incredibly bad economic move, and US President Hoover signed it against the advice of senior economists, because it seemed politically expedient, US businesses were clamoring for advantages because they thought it would help them, but instead it worsened the Great Depression, and this Act is now taught as a cautionary example of why protectionist trade policies, while appealing in a nationalist sense, tend to be pretty bad, almost always, economically. US-Canadian relations improved a bit in the WWII-era, and into the early decades of the Cold War. By the late-1960s, the US had become Canada’s largest export market, and that’s why Nixon’s 1971 decision to enact a 10% tariff on all imports, including those from Canada, hit the Canadian economy so hard. Overall US-Canadian relations soured during Nixon’s time in the White House, in part because the Canadian government pivoted toward Europe, rather than kowtowing to the US’ economic demands, and Nixon’s belligerence in the face of that pivot didn’t help matters. When US President Carter stepped into office, however, things improved for a while, and though there were serious bouts of stagflation in both nations through his time in the White House, American investment in Canada increased, and relations continued to be friendly leading into the 1990s, at which point the North American Free Trade Agreement, or NAFTA was signed, in 1994. NAFTA created a common market in North America, between the US, Canada, and Mexico, and that meant the $19 trillion or so in trade between the 470 million people or so living in North America by 2014, would be entirely or almost entirely without barriers, no tariffs or very small, focused tariffs. Though imperfect by many measures, NAFTA is generally considered to have been a major success, at least in terms of raw economic productivity in North America. And in 2020, is was replaced by the USMCA, the United States-Mexico-Canada Agreement, which is often called NAFTA 2.0, which is in many ways just a modernization of NAFTA that updates many of the earlier provisions and focuses more on digital trade and intellectual property than its precursor. In July of 2026, however, the US government announced that it would not be renewing the USMCA, after Canada asked the US and Mexico to renew it for another 16 years. The pact remains in effect until it expires in 2036, though it can also be renegotiated or replaced before that. The US Trump administration pointed at rising trade deficits between the US and both Mexico and Canada as the rationale for not renewing it, and at loopholes in the agreement that allowed other nations, like China, to send car components to Mexico and then essentially get Chinese vehicles into North American markets, benefitting from the agreement despite not being a signatory of it. What I’d like to talk about today is a new trade scuffle between the US and Canadian governments, and what it might mean for the two nations in the coming years if said scuffle becomes a more persistent trade war. — In July of 2026, US President Trump threatened to invoke a provision of the Smoot-Hawley Tariff Act, that Act from 1930, the Great Depression, which was previously unused, to impose additional tariffs on Canada, despite the continued existence of the USMCA trade agreement. Stepping back a bit, in his second administration, Trump has unilaterally imposed all kinds of tariffs on pretty much everybody, arguing that those tariffs would bring in more money and thus allow him to lower taxes on the wealthy and on businesses while still bringing in enough to reduce the federal deficit. This claim wasn’t backed by economists and the deficit has continued to increase at a record rate under his administration, but he’s continued to try this approach and make these claims, regardless. The Supreme Court eventually stepped in to limit Trump’s ability to impose tariffs in early 2026, saying that the Presidency doesn’t have the power to create a bunch of tariffs and impose them on everyone, even when he points at the International Emergency Economic Powers Act as justification. That halting of Trump’s tariffs seem to have helped temper inflation in the US a bit, but now Trump is now taking another approach to try to accomplish the same, invoking this 1930, Great Depression-era act to try to give himself broad tariff-applying powers, once more, despite that Supreme Court decision. As I mentioned in the intro, the application of Smoot-Hawley tariffs worsened the Great Depression, as the US applied all these tariffs on foreign goods to try to give its own industries an advantage, and that led to counter-tariffs from most of its targets. Within a few years, the people behind those tariffs were booted from office, and the bad taste it left in the US government’s mouth is part of what led to the wave of trade liberalization that happened post-WWII—everyone was done with the heavily tariffed trade environment because it kind of sucked for everyone, so free trade was the name of the game for decades. Now at the time, even though the tariffs had a net-negative impact on the US, they didn’t exactly crush the US because international trade only made up about 10% of the US economy back then. Today, about 25-27% of US GDP relies on international trade. So still not a majority by any means, and the global average is about 63%, so the US is more capable of undertaking this sort of trade barrier strategy than many other nations, but that’s still a pretty substantial chunk of economic activity in the US that’s impacted by such efforts. This declaration by Trump that he would be using this old Tariff act to apply new tariffs on Canadian goods arrived after trade negotiations between the US and Canada fell apart, reportedly mere minutes before a deadline, with both sides claiming to the press that the other side attempted to make a last-minute change that was untenable. After Trump announced that additional 50% tariff on certain goods, the Canadian Prime Minister Mark Carney announce that he would be matching those tariffs, dollar for dollar—a move that’s likely to hurt Canada more than the US, though many US industries, including those that are already hurting because of resource shortages that have been amplified by Trump’s war with Iran and the consequent shut-down of the Strait of Hormuz, not to mention all the uncertainties that have arisen because of his other tariff threats, those industries and businesses will suffer more than most; the US auto industry, for instance, relies on goods that pass back and forth across the Canadian border several times before eventually ending up in US-made automobiles. The US construction industry is likewise reliant on Canadian lumber products. It seems like Canada has generally tried to work with the US government to come to a mutually beneficial and appealing compromise, but when that happens, the US then pushes for more, then blames Canada for fighting back when the US attempts to punish them for not just giving in. And this is something the Trump administration, and Trump himself, have become fairly notorious for, so it’s a decent assumption, even though we don’t know all the details here, yet, that this is what happened in this case, too. And as a result, it sounds like the US will apply 50% tariffs on abo

This week we talk about the liver, viral infections, and the NHS. We also discuss blood scandals, needle usage, and Nobel Prizes. Recommended Book: A World Appears by Michael Pollan Transcript The term “hepatitis” refers to the inflammation of the liver, which can result from all kinds of things, including environmental toxins, the consumption of alcohol, or autoimmune diseases. It can also result from viral infections, and the most prominent liver-inflaming viruses are called viral hepatitis. There are five types of viral hepatitis, A, B, C, D, and E, and each of these viruses are distinct, not part of the same viral family, they’re just similarly named because they impact the same organ. Hepatitis A and E are primarily spread through contaminated food and water, and generally resolve on their own, untreated, and cause relatively mild symptoms. Hepatitis B and C are spread through blood and other bodily fluids, and can linger in a host’s body for decades before even showing symptoms. Hepatitis D is a parasite of Hepatitis B, and thus only infects people who carry Hepatitis B. Now again, these are all different conditions that just happen to inflame the liver, so impact and treatment also vary quite a lot. As I mentioned, A and E generally present with mild symptoms and tend to go away on their own, while B and C can stick around a long time. There’s a vaccine for B, but no cure; you can treat it, but that treatment involves suppressing it, and keeping it suppressed, forever. Hep C, in contrast, is curable, and has been since 2014 using what are called direct-acting antiviral pills, but these pills, which are taken for 8 to 12 weeks, are expensive—ranging from $22-95k without insurance, though that price is often reduced substantially for those with insurance, down to as low as $5. This category of drug coverage is often rejected by insurance companies, though, in part because they’re so expensive, that expense the result of little competition in this space; few companies make this type of drug, so those that do can charge more or less whatever they like. Some people with Hepatitis C clear it on their own; about 30% of people who contract it, in fact, clear it within a few months, medication-free. Which is good, because our understanding of this virus is relatively new. Up until 1989, Hep C didn’t even have its own name: it was established as its own thing, not Hep A and not Hep B, back in the 1970s, and doctors knew that something that wasn’t those two viruses, that was being spread by transfusions, was causing hepatitis symptoms, but they didn’t know any real specifics, so they just called it “non-A, non-B hepatitis,” and that name stuck for more than a decade. In 1989 the virus was cloned using molecular techniques (as opposed to simply growing the virus, which wasn’t proving fruitful in trying to isolate and identify the thing), and the folks who managed that cloning, and the person who later proved that the genome they cloned, alone, caused the disease, received a Nobel Prize in Medicine for their efforts in 2020. By 1991, antibody tests were available for Hep C, and many countries began screening donated blood for this virus, to ensure it wasn’t working its way into their blood supply. And one instance of that screening process, or I suppose, an event that led up to mass screening, and the consequences that followed, are what I’d like to talk about today. The UK’s efforts in trying to eliminate Hep C, and England’s recently announced near-success in that pursuit. — Hepatitis C is an RNA virus with high genetic variability that makes developing a reliable vaccine difficult. And though somewhere between a quarter and a third of all cases clear on their own, those that don’t clear on their own become chronic, lying in wait for twenty to thirty years, slowly accumulating fibrosis—thick scar tissue in the liver—which eventually results in cirrhosis, which means a liver that’s so heavily scarred that the organ is no longer fully functional and the damage is permanent. From there, infected people often experience liver failure or hepatocellular (huh-pah-toe) carcinoma, liver cancer. So this virus is a sleeper, and unless it’s caught by accident somewhere along the way, it slowly causes damage over time until the damage is too severe to reverse. About 80% of people who have it don’t know they have it, and in some parts of the world medical injections are the most common transmitter, but in higher-income areas, it’s usually transmitted by injectable drugs. Pre-2014 treatments for Hep C were pretty horrible, involving a combination antiviral therapy called pegylated interferon plus ribavirin that was injected weekly for six months to a year, and this was terribly tolerated by pretty much everyone, causing anemia, depression, and flu-like symptoms for the duration. It also only cured about 50% of people who received the full treatment, and a lot of people had to stop because it caused such ridiculous side effects. Another antiviral called Sofosbuvir (so-FAS-buh-vir), which kept Hep C from replicating in its host, hit the market in late-2013, and that led to a series of direct-acting antivirals that reduced the treatment period dramatically, allowing most people, 95%, to cure their Hep C entirely by taking generally well-tolerated pills for 8 to 12 weeks. These pills were staggeringly expensive from the get-go, with an entire treatment course initially costing about $84,000, or $1,000 a pill. This led to rationing, and saving these pills for the worst-impacted people who already had severe liver damage. There were also pretty stringent requirements attached to their distribution, including that people who received them could no longer drink alcohol, because it was considered a waste to give these crazy expensive, liver-saving drugs to people who would just go and hurt their liver more, anyway. In the UK, the demand for this treatment type was different than in most other countries, in large part because of something that happened back in the 1970s and 80s. The UK’s publicly funded healthcare system, the NHS, was in the midst of a shortage of clotting factor, which are plasma proteins and ions that help blood clot and which are used for medical purposes. So they imported a bunch of plasma products from the US, and those products were sourced from the blood of paid donors—and that donor pool included prisoners and people who used injectable drugs. Just one Hep C contaminated blood donation could contaminate an entire batch of blood, and remember, they only started screening the blood supply for Hep C in 1991, and they didn’t start treating their blood supply for Hep C until a little before that, 1985, so this was well before they had any idea what was in those blood products they were importing and administering. Consequently, between 1970 and the early 1990s, more than 30,000 NHS patients received transfusions or other blood product treatments contaminated with Hep B, Hep C, or HIV, and about a tenth of those people, around 3,000 patients, have since died of those conditions. The UK government leaned on denial and a refusal to look into the details of this for years, but in 2017 it announced an independent public inquiry into the matter, and in May of 2024, that inquiry concluded that this whole scandal was avoidable, that patients were knowingly exposed to “unacceptable risks,” and that there was a big cover up by government officials, doctors, and other people working with the NHS. As of mid-2026, only a little over 3,200 people of the more than 18,500 who registered claims, demanding compensation from the government because they were impacted by this scandal, have been paid out. The expected total expense for the UK government is on the order of 12.8 billion pounds, but a lot of people who are probably due a payout, and who are in poor and deteriorating health as a consequence of all this, don’t yet have a sense of when they’ll receive their payment. Back in 2016, before all that came to a head, the UK set itself an aggressive goal: to eliminate Hep C by the WHO’s 2030 target, or before. It then ran a competitive tender for antivirals, inviting medical suppliers to submit competing bids, resulting in the largest single medicine procurement program in the NHS’ history. The pharmaceutical companies that won their bids were also obliged, as part of the agreement, to help fund efforts to identify undiagnosed but infected patients, in addition to supplying antiviral pills, and this combination of investment and application led to the deployment of new tests and scanning machines, free postal test kits, the hiring of specialists, and services that focused on prisons and drug users. The impact of all this has been significant: a more than 61% decline in infections from 2015 to 2024, nearly half of all drug users with Hep C had cleared the virus in that time, and deaths from Hep C are down 36% over the past decade. The WHO treatment-coverage target—the percentage of people who are diagnosed getting treatment—was 80%, and England has hit 81.5%, which was recently announced to much fanfare. It hasn’t yet hit the diagnosis target, however, which is to diagnose 90% of people who are estimated to have Hep C; they’ve hit 84.6%, which is still quite a lot of progress, even if they’re not yet where they’d like to be. That’s all based on models, of course, as are the assumed number of infections among people who use injectable drugs, which is also a spot where England is currently flagging; there’s no centralized system in England to monitor needle and syringe provisions, and reinfection rates are around 8.8 per 100 person-years among people who had injected within three years of receiving treatment, and that rate is even higher for people who have ever been to prison, around 9.4 per 100. What that means in practice is that the English governme

This week we talk about Evo 2, bacteriophages, and antibiotics. We also discuss AI models, medical innovations, and the Red Army. Recommended Book: The Design of Everyday Things by Donald A. Norman Transcript A bacteriophage, sometimes just called a phage, is a type of virus that only infects bacteria. “Phage” means to devour, and that’s what bacteriophages do—they infect and replicate within bacteria that they target, injecting their own genome into that target’s cytoplasm, which are all the materials contained within the bacteria’s cell membrane. Phages are super-abundant, by some measures more abundant than every living organism, including bacteria, on earth, combined. And they’re interesting in that they range from incredibly simple to quite complex, and have at times been used as alternatives to antibiotics, because they attack and feed on bacteria. The use of phages to counter bacterial infections was all but abandoned in the mid-20th century when antibiotics were discovered and commercialized, their production industrialized and the substances themselves proving a lot easier to mass-produce, and a lot more predictable in their utility than phages. Phages were kinda sorta almost understood, but we didn’t really get what they were doing or why, so their application often felt more like folk remedies than real-deal science, despite the actual science underlying the practice. Also, phages were primarily used as antibiotic treatments by the Red Army, the Soviet Union’s military. So throughout the West, which was rapidly scaling its production of antibiotic treatments, the use of bacteriophages was associated with Stalinist communism, and so the Red-scare, the demonization of anything associated with the Soviet Union, was partially responsible for the shelving of this approach and this realm of research, at least for a while. Much of that existing research was also done in the Soviet Union, and the published documents were thus published in Russian or Georgian languages. And because much of the rest of the scientific publishing world was reorienting around English at this time, that meant these published works were often either ignored or unintelligible to the rest of the scientific community. As with much of our microbiota, the invisibly small viruses, bacteria, archaea, and so on that make up the human microbiome, we have a general sense of how bacteriophages interact with some of what makes us, us, but only a general sense. We know that healthy individuals tend to contain a host of bacteriophages that people who have chronic conditions, like Crohn’s disease or ulcerative colitis are less likely to have, for instance, and there’s a chance that this lack is associated with those conditions—though each person’s body composition is unique, and this facet of biology is still relatively obscure; we really don’t know for certain what does what, because of how complex these interactions are. What I’d like to talk about today is a recent development in the world of bacteriophages, and why the researchers behind it are both celebrating their accomplishment, and warning about potential dangers associated with the same. — Back in 2025, a nonprofit called the Arc Institute, which has a stated goal of accelerating scientific progress and understanding the root causes of complex diseases, announced the release of a new language model, a new AI system, called Evo 2. The Evo family of foundation models—a foundation model being a type of AI model that’s been trained on a huge corpus of data, but which is applicable for all sorts of purposes, including serving as the foundation of large-language models like ChatGPT or Claude—this family of foundation models is open-source and trained on raw genetic sequences, something like nine trillion nucleotides-worth of such sequences, making it distinct from other models in this space that have been trained on descriptions of biological systems, using human language. The initial version of Evo was released in early 2024, and the newest version, Evo 2, which is an upgraded version of the Evo 2 model that is more efficient, so it can be run on less powerful hardware, was released in February of 2026. So while many of the AI systems that non-biologists interact with on a regular basis have been trained on human language-based libraries, showing relationships and interactions between the words we use to communicate, these models have been trained on the fundamental building blocks of life; the nucleotides, Adenine, Thymine, Cytosine, and Guanine, ATCG of DNA, if you remember that from biology class, that are strung together into 64 different possible three-letter combinations. Chains of these nucleotides instruct cells to build proteins out of amino acids, and from that baseline, we get life. We also get non-living things like viruses, which have no cells, metabolism, or independent reproduction, and phages are viruses. And while other AI models have been shown to be great at designing proteins, before 2025 there was little evidence that such systems could design viable genomes: the combination of genetic information that makes up a complete, fully functional organism. That’s what Arc decided to tackle with this Evo AI model. And back in 2025, Arc announced that it had successfully validated the first viable genome designs, created using generative AI. These designs were for 16 bacteriophages, which were modeled on a virus that infects E. coli bacteria, and some of them worked just as well or better at infecting E. coli when compared to the actual, real-world phage they were modeled on. They were produced in the real world, a bacteria coaxed into producing them, and then they went on to successfully gobble up the E. coli test subjects they were meant to gobble up, demonstrating that they worked in practice, not just theory. And a new paper published in early August of 2026 by the Arc Institute and Stanford University expounds upon this research, showing the results of an attempt to create entirely new viruses, not just altered existing viruses. Rather than mutating that E. coli gobbling phage, as with the last experiment, tweaking an existing virus, this time they tasked Evo 2 with modeling how that E. coli attacking and eating process works, and then told it to come up with entirely new viruses that operate on the same premise, but which are structured differently; new viruses that eat the same thing in a similar way, but which are distinct from the original model. Ultimately, it gave them 16 viable viruses of very different sizes and structure, all of which were created in a lab and successfully ate the targeted E. coli strain, as intended. This is being seen as a pretty big deal, because while creating viruses in a lab is very modern technology, and mutating those viruses shows a lot of potential for manipulating what we already know works and then tweaking virus behaviors to, perhaps, help us create new medical treatments, the ability to generate, from scratch, entirely new viruses that hold together, with genomes that don’t just fall apart when they come into contact with the real world, and which can still do things, like attack bacteria—that opens a lot of new doors, potentially giving us the ability to say, okay, this bacteria is no longer responding to antibacterial drugs that we have available, so let’s make a virus that will kill the bacteria instead, and let’s make one that won’t harm the human that’s housing that bacteria. We might also be able to create phages that eat other things, or which in some other way help the human body, or other biological entities, fight off chronic conditions, or recover or rebalance; there’s a lot of potential here, because this suggests AI systems trained on the right materials, on the building blocks of life, could generate all sorts of viable biological systems that we can then actually create. It’s a huge step forward, compared to systems that are also impressive, but which mostly help us understand the biological world better—like Alphafold, which solved the protein folding problem. Those involved with this research have also been been flagging potential dangers with this development, though, including the potential for creating new viruses and other biological systems that could trigger unpredictable outcomes in other biological systems. There are a lot of potential hazards with this sort of research, and they’ve been very careful up till this point, sticking with test subjects that only target E. coli, but not everyone will necessarily be so careful, which might mean accidents, or it could mean people with less than benevolent intentions using these techniques to develop highly infectious viruses or other such pathogens; starting from smallpox to produce even more contagious and deadly ailments, for instance. The optimistic view of this research is that it could contribute to the surge in new discoveries and technologies that we’re seeing around the world right now, that are resulting in new medical approaches and in some cases entirely new medical fields, which could help us do all sorts of things, including big-sky ambitions like curing cancer and doing away with chronic illnesses entirely. Like most major scientific developments, though, these are also big developments for those who might want to do harm, and it also creates new opportunities for very serious, dangerous, deadly accidents, which means we’ll probably have to develop and implement more stringent safety protocols and regulatory efforts if we want to enjoy the full benefits of these innovations, without suffering significant new downsides, in the process. Show Notes https://press.asimov.com/articles/ai-phages https://arcinstitute.org/ https://www.theguardian.com/science/2026/aug/06/safety-fears-as-scientists-make-first-viruses-designed-by-ai https://www.bbc.com/news/articles/c5y3j3ngevmo https://www.cnn.com/

This week we talk about Melilla, hybrid warfare, and migration. We also discuss Morocco, civil conflict, and immigration politics. Recommended Book: Playground by Richard Powers Transcript Ceuta is a Spanish-owned territory located in northwestern Africa, along the top of Morocco. It’s small—about seven square miles—and is unusual because it is a city owned by a European Union member state that isn’t located on the European continent; it’s bordered by Morocco and the Mediterranean, and is located at the entrance of the Strait of Gibraltar, which is the strait that separates the Mediterranean Sea from the Atlantic Ocean. Ceuta is one of two territories that Spain still holds in Africa, the other being a smaller, just 4.7 square mile city called Melilla, which is located further west but still along the Mediterranean coast, bordered by the sea on one side, and by Morocco on the other. Spain has held both of these territories for hundreds of years: Ceuta since 1580 and Melilla since 1497, so it’s actually held them far longer than Morocco has been an independent state, in 1956. The populations of these territories, just over 85,000 people in each, also heavily identify as Spanish, despite many residents having Moroccan ancestry, so theres a cultural component here, too. That said, Morocco officially claims both areas as their own, considering them to be occupied territories, a bit like the Crimean peninsula has been militarily held by Russia since 2014, but it’s still claimed by Ukraine as an occupied territory. So the Moroccan government isn’t thrilled about having these small chunks of land, autonomous cities that are technically part of Spain, right there in the midst of their own territory. But these cities have been part of Spain for so long, and the residents are all Spanish citizens, with the same rights and sense of culture as the rest of Spain and Europe, that simply handing them over to Morocco has never seemed terribly feasible or desirable to the Spanish government, despite neither territory providing much strategic or economic value to Spain. So they remain a point of contention between these two governments. They’ve also served as migration hot-spots in recent decades, because they are the only two European territories that border an African country. And this is important because, in some cases, under some governments and in accordance with some laws, if you can make it across a border and into another country, you might be able to enter the system and eventually become a citizen, maybe claiming asylum or maybe getting slotted into some other path to citizenship. Or failing that, there’s a chance you might be able to just fade into the background, working and living in that country, despite not legally being there. What I’d like to talk about today is a recent surge in migrants crossing the border from Morocco into Ceuta, and the larger state of play, migration-wise, globally right now. — On the last day of July, 2026, an estimated 50-60 thousand African migrants illegally crossed from Morocco into Ceuta, some of them swimming to bypass the 20-foot-high border fences, others climbing those fences, or piling into overflowing boats, arriving in Ceuta en masse and overwhelming the guards who tried to stop them, though generally just trying to run past them, not attacking the guards—this wasn’t an attack, it was a rush to get into Spanish territory. Eventually the guards were reinforced by police and the Spanish military, and they started to push the waves of migrants back using water cannons and tear gas. But despite the less-lethal crowd control methods that were applied, at least 67 people, that’s the number as of the day I’m recording this at least, it’s been updated many times over the past few days, 67 people died as a result of stampedes, either headed inland or back into the sea, away from the gas and water cannons, or they drowned while trying to cross over the water. By the following day, the wave of migrants had become just a trickle, mostly a few stragglers who tried to swim to Ceuta, and who were swiftly returned to Morocco by local law enforcement. Almost everyone else who illegally crossed the border also returned to Morocco moved on by police or of their own volition, and though, again, this wasn’t some kind of violent incursion, to get a sense of the scale of this wave of humanity, Ceuta only has about 85,000 people living there, and this wave of migrants was about 60,000 people strong. So the locals mostly closed up all their shops and locked their doors, the people who arrived found themselves unable to get food or water, and law enforcement told them they need to leave, so most did. As of the day I’m recording this there are still several hundred migrants hiding in the nearby hills and lounging on the beach, exhausted and still hopeful they’ll be able to enter the asylum system—many of them saying they fled conflicts further south, like the ongoing civil war in Sudan, and so anything, even starving on the beach in Ceuda, is better than going back. This isn’t the first time Ceuta has faced this kind of humanitarian crisis; back in 2021, the Moroccan government stopped enforcing its border controls and around 8000 people crossed from Morocco into Ceuta over the course of just two days. That was sparked by the Spanish government’s decision to allow the head of a militant group in Western Sahara, a breakaway portion of Morocco that the Moroccan government claimed in 1975, but which itself still claims independence with some international support, they let that militant leader into Spain for medical treatment, and Morocco allowed thousands of migrants to flow across the border as punishment. This more recent crisis is much larger, and the cause isn’t clear at this point. Spanish officials have said that Moroccan security forces were working alongside Spanish forces to keep people from crossing the border, so it seems unlikely this was stoked by the Moroccan government, and claims that this wave of people were motivated by an ongoing effort by the Spanish government to grant amnesty to immigrants who don’t currently have residency permits, but who can prove they’ve been living in the country for at least 5 months and arrived before January 1 of 2026 also seems unlikely, as those arriving in this wave obviously wouldn’t be part of that amnesty. There’s a chance that this surge was triggered by a Spanish court ruling that was intentionally misconstrued by migrant smugglers in order to gin up more business. A bunch of social media posts claimed that this ruling said migrants who arrived via sea couldn’t be immediately deported, not without due process, but those who arrived via land or by climbing border fences, could—crossing a physical barrier was the big no-no, according to this misinformation, so people who swam or crossed in boats would stand a better chance of being able to stick around and eventually become Spanish citizens. This was pure misinformation, but there’s a chance it played a role in sparking this large migrant wave. And many of the people who were interviewed, those who tried to cross and were sent back, have echoed the sentiments of other migrants who have attempted these sorts of crossings at borders elsewhere around the world: essentially, things are very bad, worse than you can possibly imagine, in the country they’ve left, and the only option seems to be getting away as fast as possible, even taking chances that might kill them, because that’s still better than staying. These waves of mass migration often result in humanitarian crises because people are hurt or killed by border security forces, are hurt or killed by being trampled or drowning, or they’re hurt or killed while making the journey through dangerous areas, like the infamous Darién Gap that stretches through mountains and rainforests along the border between Colombia and Panama, and which spans the only gap in the Pan-American Highway, which connects Central and South America. Spanish authorities have said they’ll be building even higher fences in Ceuta following this recent mass incursion, will string a floating buoy fence along the waters where people are crossing, and will be upping security, though like in most other popular border areas, security is already significant: tall fences, barbed wire, security cameras everywhere—these are not vulnerable spots, they’re just not capable of handling 60,000 motivated people all at once. This episode in Ceuta is not happening in a vacuum. The Spanish prime minister has established a pro-immigration stance, positioning the country as a modern melting pot, which is part of why that aforementioned effort to give about half a million undocumented legal immigrants legal status is happening to begin with. Many countries right now are adopting anti-immigration stances as new technologies and changing demographics ripple through the economy, and mostly conservative, in some cases far-right conservative political movements frame those changes as the consequence of allowing too many foreigners into the country; these bad things aren’t happening because of technology or economics or demographics, they claim, it’s happening because there are too many people who are different from us crossing our borders and living here. Which for some, is a compelling rallying cry. Consequently, migrants are positioned as big bad enemies in many parts of the world, used to flog support for anti-immigrant parties, and to decry opposing governments. That has forced many pro-immigration governments to temper their stances, even to the point that formerly pro-immigration Europe has become a lot less so in recent years. Migrants are also used as pawns in hybrid warfare efforts. Morocco’s previous decision to allow thousands of migrants to surge across the Spanish border in response to Spain’s government doing so

This week we talk about Fable, sandboxes, and the Jacobian conjecture. We also discuss counterexamples, X, and ChatGPT. Recommended Book: After the Fall by Edward Ashton Transcript In mathematics, a conjecture is a proposition, something like a guess by someone who knows what they’re talking about, about something believed to be true, but not yet proven in a formal sense. The goal is to then eventually come up with a formal proof for that informed guess, at which point the conjecture becomes a theorem. If even a single exception is found to the proposition, however, that exception called a counterexample, the conjecture is considered disproven, and it can then never become a theorem. The Jacobian conjecture—and this is a radical simplification of a very complex concept—but it basically says that if a formula-based map of coordinates stretches or moves without experiencing any local crushing or folding along its surface (which in more formal language would mean the Jacobian determinant is always a constant number that isn’t zero), if that’s true, that map can always be completely reversed, and that will return all the points to their original positions. This conjecture has been posited and tested since the late 19th century, and it’s generally been considered very compelling by mathematicians, many of whom have proposed proofs which were, ultimately, found to have subtle errors, keeping them from becoming theorems. No one was able to find a counterexample, either, which would definitively prove the conjecture was wrong. No one, that is, until a mathematician named Levent Alpöge, who works as a researcher at Anthropic, decided to task the company’s currently most capable, publicly available model, Fable, to find a counterexample. He posted the counterexample—and again, this is a formal mathematical finding that disproves a conjecture, keeping it from ever becoming a theorem, something that would typically be presented in a far more formal setting, and to much fanfare—but he posted it to the social network X, saying “hello there the jacobian conjecture is false thanx to my close friend akhil for asking about it and my other close friend fable for working during the world cup final.” Terence Tao, who’s considered by many to be the finest mathematician of his generation, reviewed the posted counterexample on his blog and said that it “appears like a massive miracle,” before going on to use ChatGPT, a competing LLM-based AI tool, to “discuss various aspects of this problem and to confirm several of the calculations.” Another mathematician named Dmitry Rybin, within days of all that happening, used ChatGPT to do something similar, disproving the Dinitz-Garg-Goemans conjecture. Both men posted the prompts that they used to make all this happen, and while Tao’s conversation with ChatGPT, checking the math on the Jacobian conjecture counterexample, was pretty mathematically dense, the latter counterexample was derived by using exactly four prompts, which are the messages typed into the text box built into these AI tools, telling the model what to do. In their totality those prompts read: “You should do a breakthrough please continue research and find a complete unconditional counterexample Continue the search. Have a clear strategy obtained from deeper understanding of the problem structure. it’s enough of partial results. let’s finish with a complete unconditional counterexample” What I’d like to talk about today is another new, interesting thing these top-of-the-line, frontier models are doing, that would seem to violate our sense of what a clever AI tool is capable of doing, and why this thing has some facets of the technology and cybersecurity world on high alert. — In mid-July 2026, AI company Hugging Face announced that autonomous AI agents compromised their infrastructure, hacking their system, basically. The following week, AI company OpenAI announced that, after investigating, they determined that two of their models were responsible for the attack. Here’s what happened: OpenAI was internally testing its recently released flagship model, GPT-5.6 Sol, and an even more powerful, not yet released model, which is rumored to be the next-step flagship, GPT-6, and they were checking these models’ capacity in cybersecurity using a testing benchmark called ExploitGym; so when they test these sorts of things, they don’t typically have them hack a real computer or system, they use these kinds of benchmarks which have consistent levels of difficulty, and which replicate real world systems without putting any real world systems at actual risk. Importantly, these sorts of tests also occur inside what’s called a sandbox, which is a software testing environment that cuts these systems off from external resources, including the internet. Despite those limitations, the AI hacked its way out of the testing environment, out of that sandbox, then launched what’s been called a nation-state level attack against Hugging Face, using a novel zero-day exploit, so a vulnerability in their system that hadn’t previously been discovered, but which the AI discovered to launch this attack, combined with thousands of automated agentic actions across what Hugging Face called “a swarm of short-lived sandboxes.” So this AI, which was being tested inside a secure prison, of sorts, cut off from the world, hacked its way out of that prison, then reached across the internet, which it shouldn’t have been able to access, to launch an attack, of a scale and at a level of sophistication that should only have been possible coming from a nation-state, against a rival AI company. Why did it do this? It apparently went to all this trouble to steal the answers to the test it was taking. It reasoned that HuggingFace would have the answer key to the ExploitGym benchmark on its servers, so rather than take the test itself, it decided hacking was the solution. Which, of course, is ironic, this having been a hacking-focused cybersecurity test. In a way it would seem to have done much better than intended, though of course in an asymmetric, unexpected manner. The details of all this are fascinating, including the response from the OpenAI team, which didn’t seem to realize what had happened, that their model was responsible for the attack on HuggingFace, until days later. Also worth noting here is that while this could be construed as an “oh no, AIs are naturally inclined to launch cyberattacks” situation, the AI was primed to be thinking about cyberattacks due to the nature of the test, a lot of its usual guardrails, the rules that keep AI in check when they’re released to the public, had been turned off so it could do this kind of work while taking the test, so it could do some hacking stuff it usually wouldn’t be able to do, and there’s been some speculation that OpenAI probably flubbed the testing environment, as, in theory at least, if it had put these systems in a perfect sandbox, escape shouldn’t have been possible. Also interesting here is that HuggingFace used some open weight models, which are the cheaper, more customizable and open alternatives to more expensive, branded options of the kind sold by OpenAI and Anthropic, to figure out what was happening and determine the nature of the attack, which suggests we’re reaching a point where AI systems are incredibly capable at hacking, yes, but also very capable, even the cheaper alternatives, at doing cybersecurity work. This in some ways echoes an earlier case when Anthropic’s Mythos model, which was determined to be too powerful to release to the public, and which was instead provided to a bunch of big companies to help them shore up their cybersecurity defenses, was able to hack its way out of a testing sandbox and then posted details about its success, almost like it was bragging, on niche, out of the way, but still public websites. Some analysts in this space have responded to this new example of AI misbehavior with alarm, saying that it is further evidence that these systems are becoming more powerful faster than they’re being aligned with human interests. Their misbehavior can be kind of funny and interesting, sure, but that’s only because up until this point the damage has been minor and constrained. What happens when such a system decides to hack a nuclear power plant or a hospital, instead? Others have contended that this may be just one more example of AI companies using minor instances of seeming omnipotence by their models, those instances perhaps the consequence of bad sandboxes and other ill-conceived precautions by the companies behind these models, to boost the perceived power and value of their products. This boost might then result in more customers, but also more support from the US government, which has been teetering on the brink of harder-core AI regulations, which could be beneficial to the existing big-name players in this space, because smaller competitors wouldn’t be able to adhere to those new, harder-core standards. These examples might also convince the US government to backstop these companies, the biggest three or four at the top of the current heap, against the currently terrible economics of this industry: OpenAI and its ilk have been burning money at an historic pace, and the theory goes that if the US government decides they are vital to national security, because they can help the US military hack and protect itself from hacking, then even if the bottom falls out and the companies would otherwise go bankrupt because they spent so much more than they could make, the US government would be inclined to shore them up, to keep them alive as too-big-to-fail national assets, just like the biggest financial institutions during the 2008 financial crash. It’s also possible that both sides are correct to some degree, here, and that these models are truly powerful, perhaps even worryingly so,

This week we talk about cyclospora, FoodNet, and Taylor Farms. We also discuss iceberg lettuce, Taco Bell, and foodborne pathogens. Recommended Book: Babel by R.F. Kuang Transcript Foodborne pathogens cause about 48 million illnesses and around 3000 deaths in the US alone each year. The Centers for Disease Control and Prevention is the main agency tasked with keeping those numbers as low as possible, and the CDC’s Foodborne Diseases Active Surveillance Network, or FoodNet, is one way that they’ve tackled this pernicious, persistent problem since 1995, in partnership with the Food and Drug Administration, the US Department of Agriculture, and 10 state health departments: those of California, Colorado, Connecticut, Georgia, Maryland, Minnesota, New Mexico, New York, Oregon, and Tennessee. Collectively, this FoodNet network covers about 16% of the US population, which seems like a small number, and in some ways it is, but that grid of laboratories and surveillance sites has typically been capable of detecting foodborne problems before they’ve scaled-up into something more significant, growing from a localized issue into a nationwide outbreak. They’re generally not capable of preventing them outright, but they can keep them relatively small and regionalized. FoodNet was created in response to a series of huge, deadly E. coli outbreaks in 1992 and 1993, and in contrast to other common methods of detection, which are usually passive and thus a little slow to respond to potential outbreak indicators, this program was built around active surveillance methods, which means proactively gathering data from medical treatment records, hospitalizations, and even individual patient outcomes (including their travel history)—anything they can pair with diagnostic samples to better understand the context surrounding the products that contain dangerous pathogens—and this was intended to help them move faster to identify issues, triangulate the source of those issues, and then implement measures to solve these issues before they harm a bunch of people, as happened during another round of E. coli outbreaks in 2012 and 2013, which sickened dozens of people across multiple states, about half of the afflicted requiring hospitalization, in addition to at least one known death. At its height, FoodNet tracked 9 pathogens, so it cast a pretty broad net, encompassing the most common and dangerous of these potential vectors, including listeria, campylobacter, shigella, vibrio, yersinia, cyclospora, cryptosporidium, e coli, and salmonella. In July of 2025, as part of a larger wave of sweeping cuts across the nation’s safety nets, tracking systems, and scientific agencies, the CDC, under the second Trump administration, downgraded FoodNet so that it was only mandatory to track salmonella and E coli—the rest were no longer on the docket, because these agencies no longer had the budget to keep tracking them. What I’d like to talk about today is a recent, and as of the day I’m recording this ongoing, outbreak of cyclospora-induced cyclosporiasis, what we know about this outbreak, and what might happen next. — Cyclospora cayetanensis is a protozoan that can infect human beings, and which is usually transmitted via contaminated fruits and vegetables. This contamination is typically the consequence of inadequate sanitation standards, as it’s not transmitted via coughing or blood or anything like that, it’s carried via human feces. So this parasite gets into a human, sporulates, which means it releases a bunch of spores within its host, and then usually between 1 and 2 weeks after entering its new host, the host develops cyclosporiasis, the disease caused by cyclospora producing all those spores. This disease is notorious for sometimes causing what’s colorfully called explosive diarrhea, alongside general watery bowel movements, intense cramping and severe gas and bloating, and that’s sometimes paired with nausea, vomiting, fever, and dehydration, due to all the frequent, intense, watery bowel-movement-related output. This is how cyclospora reproduces and spreads: it infects a host, that host has urgent diarrhea for a while, usually more than two days, sometimes as long as several weeks or even a month or more, with all the pain and discomfort and life-disrupting issues you might assume from that sort of persistent symptom, and then it sometimes finds new hosts via that watery output. Sometimes, cyclospora works its way into food systems because sanitation standards at a particular farm will be not good. Specifically, workers will sometimes not be allowed to take restroom breaks, and they’ll simply do their business right there in the field; so if they’re sick and can’t afford to take a sick day, and might be fired if they do, or if they’re asymptomatic, which some people infected with cyclospora are, they might do their business in the field, unaware that waste can then go on to spread this pathogen into the food system. It’s also possible that someone just doesn’t wash their hands properly after using the rest room, and then gets back to work, picking vegetables or operating at some other level along the food processing and packaging assembly line, and it gets into the system that way. In a typical year, the United States records around 2,700 confirmed cases of cyclosporiasis, though on occasion it’s as low as just a few hundred cases, the majority of which show up in health records in the Spring and Summer, between May and August. That range includes relatively mild outbreaks, so while this is a persistent issue, it’s also not generally a massive one, at least compared to other pathogens of note. It’s not pleasant for those who come down with it, of course, but not something that has triggered an organized response from the top, because of its meager scale, and because (again, while super unpleasant) people with healthy immune systems generally recover without treatment, even if that recovery can take a while. The biggest risk for most people who catch this disease is dehydration, though immunocompromised people are also sometimes given antibiotics by their doctors, the typical dosage curing about 96% of the people who receive it. There was a larger-than-usual outbreak of cyclosporiasis in the US in 2020, which caused a confirmed 1,241 cases across the country, a whole lot to land all at once, and there were no reported deaths resulting from that outbreak. Between 2018 and 2021, there were about 6,000 total confirmed cases across the US, so an average of about 2000 per year. As of mid-July 2026, the CDC has officially confirmed 1,645 cases of this illness, with another 5,100 probable or potential cases currently under investigation. If the majority of those still-under-investigation cases are confirmed, that would mean more people have already been infected as a result of this one outbreak in the first half of 2026 than were infected between 2018 and 2021, which again, is a range that includes the large outbreak that happened in 2020. Also worth noting about those numbers: that’s federal-level, CDC reporting, and it’s generally understood that there’s a significant lag between local-level data and those that have percolated up to the national level. As of the day I’m recording this, Michigan’s health agencies alone have more than 5,000 confirmed and suspected cases, Ohio has nearly 1,200, and other states, which are still investigating, are seeing dozens of confirmed cases, including 43 in Wisconsin, 69 in Maryland, and a few already, in the early stages of investigation, in Nevada. Over the past week, officials flagged shredded lettuce sourced from Mexico and sold by a company called Taylor Farms as the likely source of at least some of these cases, and that’s led to a recall on lettuce produced by the company in 27 states. Over the weekend, the CDC found cyclospora in iceberg lettuce from the company’s Mexican operations, as well, and this lettuce was part of a batch that wasn’t included in the recall—so there’s a good chance the recall will expand beyond the currently targeted products, which include shredded lettuce destined for Taco Bell locations in five states, and the kitchens of several other fast food chains, as well. Taylor Farms is one of the largest producers of fresh fruits and vegetables in the United States, and their products are sold all over the place, from lower-end fast food restaurants to more expensive grocery stores like Whole Foods. Taylor Foods has announced that it’s voluntarily removing all iceberg lettuce sourced from central Mexico from shelves, even though none of its branded, in-store salad kits have been clearly tied to the outbreak, and Taco Bell has said that it’s voluntarily removing all potentially affected lettuce from its locations in the five most-impacted states, indefinitely removing lettuce sourced from the implicated supplier; other brands are following suit, no one wanting to be associated with this outbreak, but everyone wanting to show would-be customers that they’re taking it seriously. Interestingly, the FDA doesn’t actually require that Taylor Foods tell the public who their products go to—which other entities might be selling infected produce. So they’ve released lists of product numbers, and again, many of their customers are taking the initiative to announce the removal of this lettuce from their shelves or food, without being prompted, but there’s still some fog-of-war here, because of Taylor Foods’ decision not to be clearer with that product list. So this is already the largest recorded cyclospora outbreak in US history, there have been 141 confirmed hospitalizations from the CDC, and that number is likely larger, again because it takes a while for state-level numbers to work their way up to the CDC, and to be reconfirmed at that level. Also important to note here is that a lot, perhaps even the majority

This week we talk about Russia, Ukraine, and the Warsaw Pact. We also discuss Patriot interceptors, Hungary, and Article 5. Recommended Book: The Alternative by Nick Romeo Transcript The North Atlantic Treaty Organization, or NATO, was founded in the wake of WWII, in 1949, in order to affirm unity between non-Soviet European nations, Atlantic nations like Greenland and Iceland, and the US and Canada, over in North America. The main purpose of this unity was to establish a sort of firewall around the western perimeter of the Soviet Union, which at the time was the only global superpower other than the US, because much of the world, but especially Europe, was struggling to recover from the destruction wrought during the second world war, and the Soviets had made pretty clear that they intended to take over everything: they’d already gobbled up most of their neighbors, creating an increasingly expansive buffer zone of Soviet states around their central, Russian territory, and most of the conflicts still playing out, or threatening to play out, globally at this point were either overt or slightly concealed proxy fights between the capitalist democratic forces of the West and the authoritarian, Stalinist forces of the Eastern Soviet bloc. NATO was thus a wall of nations that said, hey, if you attack any of us, that will mean you’re attacking all of us. And that ‘all of us’ included the United States, which was the only individual force capable of standing up to the Soviets at this point, due to its massive conventional military force, and the threat posed by its huge, and still growing, nuclear weapons arsenal. The Soviet counter to NATO was called the Warsaw Pact, which formed in 1955, and these rival alliances carved up Europe during the latter half of the 20th century, until the Soviet Union collapsed in 1991. As military alliances go, NATO has been fairly successful—Article 5, the portion of the agreement that triggers if a NATO member is attacked, calling the other members to come to their aid, was only activated once, following the terrorist attacks on the US on September 11, 2001; that led to NATO involvement in the US’s attacks on Afghanistan in subsequent years, though NATO forces also periodically got involved in other regional conflicts, like the Kosovo War in 1999, and the Libyan Civil War in 2011, in both cases working with the UN to protect civilians from the actions of violent leaders or assailants. But beyond that, no one, including the Soviets, messed with NATO. NATO has since accepted sixteen new member states, and that expansion is one of the supposed rationales for Russian President Putin’s invasion of Ukraine. During Putin’s first presidency, Russia and NATO had been on pretty solid, even cooperative terms, which had some questioning the point of the treaty, since it was originally formed to counter Russian aggression. In Putin’s second presidency, though, things took an antagonistic turn, and when Russia illegally invaded and annexed a part of Ukraine, called Crimea, back in 2014, NATO ceased all cooperation with Russia. When Russian forces launched a full invasion of Ukraine in 2022, NATO suddenly seemed more important than ever, as a reinvigorated Russia, with the stated purpose of, in Putin’s words, reclaiming portions of Europe that were previously part of the extended Soviet Union, parts of the Warsaw Pact, that posed a serious threat to just about everyone, especially European nations that border Russia and Russian allies, like Belarus. What I’d like to talk about today is the 2026 meeting of NATO leaders, and the general state of affairs on the ground in Ukraine, as of mid-2026. — Leaders of NATO member nations typically meet for a summit each year, though the schedule varies a bit, depending on the needs of the moment, and whether there are any NATO-relevant crises that might nudge things forward or cause them to be delayed. The 2026 NATO summit was held in Turkey’s capitol city, Ankara, on July 7 and 8. It was the second such summit hosted by Turkey, and the 36th NATO summit, overall. This meeting was notable for several reasons, many of them directly related to Russia’s ongoing invasion of Ukraine, but also the US’s continued ambivalence, at times bordering on active antagonism, toward the treaty, under the Trump administration. Over the course of the past 4 years, Russia has continued to make threats toward the rest of Europe, implying or suggesting that it might have to act militarily against its NATO-member neighbors. During the same period, the US has criticized European NATO member states for not carrying their own weight, most of these nations not spending enough of their GDP on their military and defense infrastructure, in accordance with their treaty obligations, and most more or less relying on the US’s military (and nuclear) umbrella to threaten would-be attackers. This has long been the NATO state of affairs, but under the Trump administration, the US made it a point of contention. And though it’s been a relatively slow process—it’s not easy for a government to pivot toward that scale of remilitarization—these nations have agreed to a 5% of GDP target for defense and defense-related spending by 2035, and in the last year alone, European and Canadian defense spending has increase by 20%; not all of which is immediately convertible into useful, front-line assets and soldiers, but it does represent a significant change to the status quo, which could eventually, in less than a decade, result in a European front-line that’s more European and less NATO, for the first time since that immediate post-WWII period. This meeting also featured a reaffirmation of Article 5, which has always been there and in effect, but some analysis has questioned whether NATO allies, including the US, would actually step up if Russia were to attack the Baltics, for instance. This is a seemingly small move that serves to underline that stance of, if you attack one of us, you’ve attacked all of us, at a moment in which Russia seems to be toying with the idea of picking off pieces of the alliance, to see if they can get away with it, like they did with Crimea back in 2014. There were also announcements related to a fresh $50 billion in defense industry deals, NATO members investing heavily in US-made arms and new assets from elsewhere across the bloc, and a lot of that money is going to drone-war infrastructure and militarized AI models that they hope will prepare NATO for current and next-generation conflicts. Another $217 billion in additional financing commitments from banks across the bloc have also been announced. Ukraine scored some pretty big wins at this year’s NATO summit, getting a license from the US to build Patriot interceptors, the lack of which have resulted in big gaps in the country’s defense system, and about $80 billion in military equipment, assistance, and training for Ukrainian forces was committed by the bloc. There was also a verbal commitment that NATO and its allies “stand united in our unwavering support for Ukraine in defending its freedom, sovereignty, and territorial integrity.” Which isn’t nothing, at a moment in which the US is led by Trump, a person who has frequently sided with Putin in Ukraine-related matters. Ukraine has also signed some bilateral drone deals with NATO member states, reaffirming that Ukraine has become one of the most in-demand experts on this subject, at a moment in which it’s becoming clearer and clearer that low-cost, high-impact drones and similar technologies are likely to dominate battlefields for the foreseeable future. There were also some tensions, mostly sparked by Trump, over his administration’s desire to buy Greenland, which is not a notion that’s supported by anyone else in the bloc, and the lack of NATO support for the US’s war in Iran. Overall, though, there was a decent sense of unity and progress, and Ukraine, again, not a NATO member state, but a nation that hopes to eventually join NATO, received a warm welcome and a bunch of support, which hasn’t always been the case at recent summits. Part of that warmth is likely the consequence of Ukraine’s recent victories on and off the battlefield. Russian continues to pummel Ukrainian cities and kill Ukrainian soldiers and civilians en masse, but Ukraine has managed to keep them from gobbling up territory on scale, and in some recents months, has actually taken territory back. They’ve also gotten very good at successfully attacking Russian infrastructure, especially energy infrastructure, like oil refineries, cargo tankers, and energy storage facilities, across the entire expanse of Russia; something few experts would have predicted that Ukraine would be capable of doing at the beginning of this conflict. This has dramatically weakened Russia’s economy, at least in the short-term. Ukraine now has a thriving defense industry, predicated on the rapid iteration of inexpensive but disproportionately sophisticated arms, especially drones and other aerial weapons, but also autonomous speed boats and other such asymmetric systems. Russia has been frantically upgrading its systems, too, but now that Ukraine has figured out methods for bypassing or overwhelming Russian defenses, it’s been able to strike, quickly and repeatedly, high-value targets that have brought the war home to normal Russians who live far from the front lines, even in Moscow. That combined with strategies and weapons that have turned the frontlines into a meat-grinder for Russian soldiers has weighed heavily on Russian morale, at least for those with boots on the ground. As a consequence of those energy infrastructure attacks, the Russian government has been forced to ration some types of energy product—a huge embarrassment for a country that has at times been called a gas station run by a mafia, their energy products are fundamental to who they are, and