Let's Know Things

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.
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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: higher yields increase the cost of servicing the debt, higher interest costs expand the deficit, larger deficits require more borrowing, and more borrowing can put further upward pressure on yields.
Economists use the term fiscal dominance to describe the point at which government financing needs start to constrain monetary policy, pushing the central bank to keep rates lower than it otherwise would, or to buy government debt, even if doing so undermines its effort to control inflation.
The US is not necessarily at that point, but this is exactly the kind of pressure the 1951 Accord was meant to prevent.
As with everything government money-related, there’s also a global dimension to this shift.
For decades, Japanese banks, insurers, pension funds, and other institutions bought foreign bonds in part because yields at home were so low. On September 1, though, Japan’s 10-year government bond yield touched 3% for the first time since 1996.
Japan’s government has more debt relative to the size of its economy than any other wealthy country, and it assumed a 3% long-term rate when calculating debt-service costs for its current budget. Rising above that level would strain its finances, but those higher yields also give Japanese investors more reason to keep their money at home.
That doesn’t mean Japanese institutions will dump all their Treasuries. Currency-hedging costs and the specific needs of different investors complicate that calculation. But when a major source of relatively steady demand becomes more price-sensitive, the marginal buyer of US debt has to be paid more to invest.
Finally, the Treasury market itself has become somewhat more fragile.
The amount of debt in circulation has grown far faster than the balance sheets of the dealers that traditionally absorb buying and selling. Hedge funds have filled some of that gap using highly leveraged strategies, including something called the cash-futures basis trade.
Fed researchers estimate that these positions reached about $830 billion by September 2025, representing 35% of hedge funds’ long Treasury exposure. These trades can provide useful liquidity when markets are calm, but because they rely on enormous amounts of borrowed money to capture tiny price differences, they can also unwind pretty quickly when volatility spikes.
That sort of unwind contributed to the Treasury-market seizure in March of 2020, and a different leveraged hedge-fund strategy added to turbulence in April of 2025.
The assets treated as the world’s safest and most liquid can still become difficult to sell when everyone needs cash at the same time, in other words.
The next few weeks should partially clarify what’s actually driving this unusual market.
The expanded Treasury buybacks begin the day after this episode goes live, September 9. Producer-price inflation data arrives on September 10, consumer-price data on September 11, and the Fed meets on September 15 and 16. The Bank of Japan follows on September 17 and 18, when it may increase its policy rate from 1% to around 1.25%.
If the Fed hikes and long-term yields fall, that could indicate investors view the move as credible inflation-fighting: short-term borrowing becomes more expensive, but the term premium shrinks because the distant future seems less inflationary.
If the Fed holds after a soft inflation report and short-term yields fall while the 30-year barely moves, that would suggest the long end is being driven by deficits, debt supply, oil prices, corporate competition, and global demand more than Fed policy.
And if the buybacks begin but long-term yields continue to climb, that would demonstrate the limits of debt-management policy in a market this large. The Treasury could respond by issuing more short-term and less long-term debt, reducing immediate borrowing costs, though that would also mean refinancing more frequently and taking on the risk that rates remain high.
It could also draw down some of the around $950 billion in its account at the Fed to fund larger buybacks, but that cash also serves as a buffer against the debt ceiling, which the government is currently expected to reach sometime in 2027. Spending the buffer now would mean rebuilding it later, and rebuilding it would require issuing even more debt.
Back in 1951, the Treasury and the Fed reached an agreement that the central bank should not be required to make government borrowing cheap, and that the price of long-term debt should be allowed to reflect what the market believed that debt was worth.
Right now, the market is rendering its verdict, and that verdict is that lending the United States money for 30 years has become substantially more expensive. Now we wait to see what Washington decides to do about it.
Show Notes
https://www.federalreservehistory.org/essays/treasury-fed-accord
https://www.brookings.edu/articles/what-is-the-treasury-fed-accord-of-1951-and-why-is-it-important/
https://www.federalreserve.gov/data/three-factor-nominal-term-structure-model.htm
https://www.freddiemac.com/pmms
https://www.cbo.gov/publication/61983
https://fiscaldata.treasury.gov/datasets/interest-expense-on-the-public-debt-outstanding/interest-expense-on-the-public-debt-outstanding
https://fiscaldata.treasury.gov/datasets/debt-to-the-penny/debt-to-the-penny
https://www.dallasfed.org/research/economics/2026/0210-searls-aifinancing
https://home.treasury.gov/news/press-releases/sb0606
https://home.treasury.gov/news/press-releases/sb0607
https://www.federalreserve.gov/newsevents/speech/warsh20260828a.htm
https://www.bls.gov/news.release/empsit.htm
https://apnews.com/article/1af16359af43eb8abc66445465f633c8
https://apnews.com/article/775d7cf741349c7c8e689c0beb57f074
https://apnews.com/article/a27a8d3651ff810b25c610d3e1b6259d
https://www.federalreserve.gov/econres/notes/feds-notes/decomposing-hedge-funds-u-s-treasury-exposures-20260622.html
https://www.imf.org/en/publications/fandd/issues/2026/03/safeguarding-the-treasury-market-jeremy-stein
https://www.investing.com/news/economy-news/japans-benchmark-bond-yield-rises-to-3-for-first-time-in-30-years-4883532
https://www.boj.or.jp/en/mopo/mpmsche_minu/index.htm
https://bipartisanpolicy.org/article/when-will-we-reach-the-debt-limit-again/
https://home.treasury.gov/policy-issues/financing-the-government/quarterly-refunding/most-recent-quarterly-refunding-documents/
https://www.federalreserve.gov/monetarypolicy/fomccalendars.htm
https://www.bls.gov/schedule/2026/09_sched.htm
https://www.axios.com/newsletters/axios-markets-a975877a-ddce-4ea0-a735-4b460d37af90.html
https://www.ft.com/content/c96c25c1-b27c-4c08-a2ba-21821b39dd78
https://www.axios.com/2026/08/19/rates-treasury-borrowing-bessent


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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.
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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 the hardware and is paid to manage the software that keeps everything running smoothly. Household batteries and similar assets otherwise represent competition, so utilities are less inclined to allow these systems to move forward or even be legally installed without a fight.
That said, the major players in the VPP space right now are Sunrun, Tesla, Renew Home, Uplight, Next Kraftwerke, and sonnen. The latter is the largest VPP operator in Europe and has recently been expanding into the US, especially in Utah.
Most VPP deployment in the US is happening in California, Texas, Florida, and Puerto Rico. These systems are also being deployed across South Australia, Germany, and China, where the first gigawatt-scale residential VPP, which aggregates air conditioners and water heaters across millions of households, has been launched.
This category of energy technology has rolled out more slowly than originally anticipated. When the early models were deployed in Europe, their outcomes were considered broadly beneficial, but expansion was hindered by regulations—paperwork, basically—and pushback from existing utilities that didn’t want the competition.
VPPs were also bundled with other renewable-energy infrastructure and consequently faced substantial opposition in the US, in particular, during both Trump administrations. Those administrations pulled support for renewables across the board and, in some cases, actively tried to kill these industries to make even more room for oil and gas companies.
In 2025 and so far in 2026, though, the blazing-fast deployment of data centers has brought VPPs back into the conversation. Data centers require a silly amount of energy to run, and power grids in the areas where they’re being built have been strained as a consequence, dramatically increasing energy prices.
VPPs won’t solve that problem, but they could ease it in several ways. They can temper energy use and make more electricity available during periods of peak demand without requiring the construction of expensive power plants that might not come online for years or even a decade.
They could also reframe the use of VPPs so that they’re no longer seen primarily as environmental efforts, but as economically viable means of addressing data-center-created energy shortfalls. That could lead to more VPP build-outs because these systems would no longer be such obvious targets for anti-renewable-energy legislation and politics.
Show Notes
https://en.wikipedia.org/wiki/Peaking_power_plant
https://en.wikipedia.org/wiki/Virtual_power_plant
https://www.sciencedirect.com/science/article/pii/S2211467X2400097X
https://www.theguardian.com/environment/2016/aug/05/adelaide-charges-ahead-with-worlds-largest-virtual-power-plant
https://www.nrg.com/insights/energy-education/understanding-virtual-power-plants--a-guide-to-vpps.html
https://techcrunch.com/2026/08/19/home-batteries-are-suddenly-cheap-and-everywhere-heres-why/
https://pv-magazine-usa.com/2026/08/13/tesla-unveils-zero-down-powerwall-lease-program-with-retail-electric-plan-in-texas-touts-global-vpp-potential/
https://www.energy-storage.news/base-power-launches-100mw-vpp-programme-in-texas/
https://www.ess-news.com/2026/02/12/texas-lands-its-first-battery-only-virtual-power-plant/
https://nuwattenergy.com/en/virtual-power-plants-2026
https://www.ess-news.com/2026/06/25/sunrun-tesla-renew-home-announce-plans-for-16-8-gw-virtual-power-plant-program/
https://www.sciencedirect.com/science/article/pii/S2352484725003865
https://www.cleanenergywire.org/news/start-next-kraftwerkes-renewable-virtual-power-plant-stabilises-grid
https://www.energy.gov/edf/virtual-power-plants-projects
https://www.woodmac.com/press-releases/virtual-power-plant-capacity-expands-13.7-year-over-year-to-reach-37.5-gw
https://www.utilitydive.com/news/in-2026-virtual-power-plants-must-scale-or-risk-being-left-behind/810321/
https://ieefa.org/resources/case-virtual-power-plants
https://uplight.com/blog/virtual-power-plants-are-powering-the-grid-of-the-future-and-uplight-is-leading-the-way/
https://sepapower.org/knowledge/vpp-and-supporting-der-policy-developments-q1-2026/
https://www.energymining.sa.gov.au/consumers/solar-and-batteries/south-australias-virtual-power-plant
https://whatisavpp.com/research/topics/enpal-flexa/
https://www.canarymedia.com/articles/virtual-power-plants/rooftop-solar-industry-trump-budget-law
https://foleyhoag.com/news-and-insights/blogs/energy-and-climate-counsel/2026/july/virtual-power-plants-the-distributed-energy-revolution-has-arrived/
https://ieefa.org/resources/case-virtual-power-plants
https://sepapower.org/knowledge/vpp-and-supporting-der-policy-developments-q1-2026/
https://www.cesa.org/resource-library/resource/puerto-rico-virtual-power-plant/
https://www.energy.gov/edf/virtual-power-plants-projects
https://www.energymining.sa.gov.au/consumers/solar-and-batteries/south-australias-virtual-power-plant
https://www.ess-news.com/2025/01/16/china-launches-work-on-its-first-gw-scale-residential-virtual-power-plant/
https://www.ferc.gov/ferc-order-no-2222-explainer-facilitating-participation-electricity-markets-distributed-energy
https://www.utilitydive.com/news/in-2026-virtual-power-plants-must-scale-or-risk-being-left-behind/810321/


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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 about $20 billion worth of Canadian goods coming into the US, including things like honey, seeds, and agricultural products, and some types of furniture, clothing, and fabric.
About 72% of all Canadian exports went to the US in 2025, and many of those exports, the ones to which this new tariff will be applied, will now be more expensive, because these costs are almost always passed on to the end-consumer, not just eaten by the business, which in some cases wouldn’t be able to afford to eat those higher costs and stay in business. This is part of why these sorts of tariffs often increase inflation rates.
Both sides of this conflict have publicly committed to not back down, and there’s political hay to be made in sticking with that sentiment; the US is not terribly popular in Canada, or in many allied countries, right now, due to the antagonistic stance the Trump administration has taken toward those relations, so the Canadian government might actually benefit from taking a hard line against the US, here. Likewise, Trump’s supporters might rally around his bullying of a neighboring nation, especially if the administration can successfully frame this as an effort to reduce the deficit or support US businesses, protecting them from foreign competitors are are unfairly competing.
There’s still a fair bit of fog of war on all of this, and we’ll know a lot more within the next few weeks, both in terms of the details of what happened, and in terms of what’s likely to happen next. Right now, though, it would seem that we could be headed for a new trade war between two of the world’s most deeply intertwined wealthy economies, and that could lead to a lot of global economic disruptions as some of that trade is rerouted, and as inflation continues to spiral.
Show Notes
https://apnews.com/article/trump-tariffs-canada-us-trade-war-293908564c7a381ea58a61db6e9a8517
https://apnews.com/article/canada-us-trade-tariffs-trump-857ef76b20a766e370d70176135b678e
https://apnews.com/article/canada-us-trade-war-trump-carney-tariffs-4d18583fe52134ca8550652ad9772d2c
https://www.nytimes.com/2026/08/22/business/economy-trade-war-us-canada.html
https://www.axios.com/2026/02/20/trump-tariffs-supreme-court-illegal
https://access.heinonline.com/HOL/LandingPage
https://en.wikipedia.org/wiki/North_American_Free_Trade_Agreement
doi.org/10.1017%2FS0022050700019549
https://en.wikipedia.org/wiki/Smoot%E2%80%93Hawley_Tariff_Act
https://en.wikipedia.org/wiki/Canada%E2%80%93United_States_trade_relations
https://www.axios.com/2026/08/22/us-canada-tariffs-trade-trump-carney
https://www.npr.org/2026/08/22/nx-s1-5941584/us-canada-tariffs
https://apnews.com/article/canada-us-trade-tariffs-trump-857ef76b20a766e370d70176135b678e
https://www.bbc.com/news/articles/cvgvyy4x2mvo
https://www.nytimes.com/2026/08/22/world/canada/carney-trump-canada-tariffs.html


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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 government overall has done a pretty astounding and effective job at negotiating their relationships with pharma companies and getting detection on track at that scale, but on more ground-level issues that are, interestingly, a lot cheaper to implement, but at times more politically complicated because of public sentiment about drug use and drug users, they’re doing a lot less well—and important to note here is that these outcomes vary a bit across the four programs being run across the UK. Scotland and Wales are doing relatively better and worse in some regards compared to England, for instance.
Also worth noting here that while England is broadly doing a great job with Hep C diagnosis and treatment, they aren’t the first to achieve those WHO-set goals: Egypt reached Gold tier status according to the WHO’s Hep C guidelines in October of 2023, at that point having diagnosed 87% of people who have the virus, and treating 93% of those who were diagnosed. They managed to cut incidence of the virus by 97% in just 8 years, leaning on a system of high-yield testing—they tested more than 60 million people during those 8 years—alongside a production scheme that included local manufacturing of antivirals, making them more available and affordable.
All of which are generally good signs about where Hep C testing and treatment is going, at least in these regions. And it paints a optimistic picture for other countries that might want to replicate some of what’s working within their own borders.
Show Notes
https://www.bbc.com/news/articles/c75gk620r22o
https://en.wikipedia.org/wiki/Infected_blood_scandal_in_the_United_Kingdom
https://en.wikipedia.org/wiki/Hepatitis_C
https://en.wikipedia.org/wiki/Viral_hepatitis
https://en.wikipedia.org/wiki/Hepatitis_B
https://www.healthline.com/health/hepatitis-c/treatment-costs
https://www.who.int/news-room/fact-sheets/detail/hepatitis-c
https://publichealthscotland.scot/publications/surveillance-of-hepatitis-c-in-scotland/surveillance-of-hepatitis-c-in-scotland-progress-on-elimination-of-hepatitis-c-as-a-major-public-health-concern-2025-update/
https://www.emro.who.int/media/news/egypt-becomes-the-first-country-to-achieve-who-validation-on-the-path-to-elimination-of-hepatitis-c.html
https://www.gov.uk/government/publications/hepatitis-c-in-england-and-the-uk/hepatitis-c-in-england-2025
https://www.england.nhs.uk/2026/08/100000-people-receive-treatment-to-cure-deadly-hep-c-virus-on-nhs-in-just-ten-years/
https://www.hepctrust.org.uk/blog/2019/04/hepatitis-c-trust-welcomes-elimination-deal-hepatitis-c-and-calls-government-backed/
https://commonslibrary.parliament.uk/research-briefings/cbp-10099/
https://www.who.int/teams/global-hiv-hepatitis-and-stis-programmes/hepatitis/reports/global-hepatitis-report-2026


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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/2026/08/06/health/ai-viruses-bacteriophages
https://www.abc.net.au/news/2026-08-07/ai-models-design-viruses-not-found-in-nature-for-first-time/107007854
https://www.wired.com/story/scientists-used-ai-to-create-16-new-viruses/
https://www.science.org/doi/10.1126/science.aec2657
https://en.wikipedia.org/wiki/Bacteriophage
https://en.wikipedia.org/wiki/Evo_(AI)
https://www.nytimes.com/2026/08/06/science/ai-viruses-bacteria-arc.html


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