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The all-American EV startup is cutting costs to survive.

America’s most interesting electric-vehicle company is about to have the defining year of its life.
On Wednesday, the company reported that it lost $1.58 billion in the fourth quarter of last year, bringing its net annual losses to $5.4 billion. It announced that it is laying off about 10% of its salaried employees, but — at the same time — promised that it has a plan to achieve a small profit by the end of this year.
Rivian does not seem to be in trouble — not quite yet, at least. But the earnings made clear what electric-vehicle observers have known for a long time: Either the company will emerge from this year poised to be a winner in the EV transition, or it will find itself up against the wall.
That’s partially because Rivian has a stomach-turning number of corporate milestones coming up. Over the next 11 months, it plans to unveil an entirely new line of vehicles, shut down its factory for several weeks for cost-saving upgrades, break ground on a new $5 billion facility in Georgia, and — most importantly — turn a profit for the first time. It also expects to manufacture and deliver roughly another 60,000 vehicles to customers.
Any one of these goals would be difficult to achieve in any environment. But Rivian is going to have to execute all of them during a time defined by “economic and geopolitical uncertainties” and especially high interest rates, its CEO R.J. Scaringe told investors on Wednesday. Since 2021, Rivian’s once robust stockpile of cash has been cut in half to about $7 billion; at its current burn rate, the company will run out of money in a little more than two years.
Although Rivian’s situation is dire, it’s not experiencing anything out of the ordinary. As I’ve written before, the electric truck maker is crossing what commentators sometimes call “the EV valley of death.” This is the challenging point in a company’s life cycle where it has developed a product and scaled it up to production — thereby raising its operating expenses to eye-watering levels — but where its revenue has not yet increased too.
During this vulnerable period, a company essentially burns through its cash on hand in the hope that more customers and serious revenue will soon show up. If those customers don’t arrive, then it either needs to raise more cash … or it runs out of money and goes bankrupt.
It’s a frightening time, but once a company crosses the valley of death, it can reach an idyll. Not so long ago, Tesla found itself in something like Rivian’s position as it prepared to launch the Model 3. Seven years later, it is the most valuable automaker in the world.
Once Rivian’s revenue exceeds its costs, its problems will get easier, or at least more straightforward: Instead of fighting for its survival and watching its cash reserves dwindle, Scaringe will be able to make more strategic trade-offs. Should the company cut costs to expand its profit margin and reward investors, or should it pass the savings along to customers in the form of lower prices, thus growing its market share? Scaringe can’t make these types of decisions until his firm is safely out of the valley.
Claire McDonough, Rivian’s chief financial officer and a former J.P. Morgan director, has a plan for crossing that canyon — an aptly if strangely named “bridge to profitability” that it will attempt to build this year. Rivian’s survival, she said, will depend above all on cutting the unit costs of producing its vehicles, including by using fewer materials to make every car. Other savings will come from making more vehicles faster. That’s what makes the shutdown plan, though it might seem extreme, worth it; McDonough said those improvements alone will get the company about 80% of the way to profitability.
Another 15% will come from marketing more “software-enabled products” to Rivian drivers and by selling air-pollution credits to other carmakers, whose vehicles are not as climate-friendly. This is a tried-and-true technique; Tesla first turned a profit in 2021 by selling regulatory credits needed to comply with federal and California state-level rules to other, dirtier automakers. But that same year, Tesla also debuted an entirely new vehicle: the Model Y crossover, which quickly became its top seller in the United States. Tesla, in other words, finally started to make money by cutting costs, finding new revenue sources, and releasing new products.
New products, however, are becoming a weak point for Rivian. The company says that high interest rates will keep demand for its vehicles flat this year. It expects to make about 60,000 of them, about 20,000 fewer than what it had once anticipated. The Rivian R1S, a three-row S.U.V., has become the company’s flagship; it is selling better and is cheaper to manufacture than Rivian’s pickup, the R1T. It also costs at least $75,000, or nearly $600 a month to lease. The highest-tier models can cost $99,000. Turns out, it’s difficult to sell a lot of $70,000 trucks when even the cheapest new-car loans hover around 6%.
Rivian once had a first-to-market advantage in the electric three-row SUV market, but that may be fizzling out, too. Kia is now selling its own all-electric three-row SUV, the EV9, for $18,000 less than the R1S; in fact, the Kia EV9’s most expensive trim costs $76,000, which is only slightly more than the cheapest R1S. The Kia SUV can also charge faster than the Rivian under ideal conditions. It remains an open question how many rich suburbanites are still interested in buying Rivians, especially now that the Tesla Cybertruck and Ford F-150 Lightning are competing directly with Rivian’s pickup truck.
The company’s hopes, in other words, rest on its next product line: the R2, which it will launch on March 7. We know almost nothing about the R2 line, except that it will probably include an SUV, that it will go on sale in 2026, and that it will fall somewhere in the $45,000 to $55,000 price range. (The median new car transaction in the United States now costs $48,200.) Last year, Scaringe told me that the R2’s timing was perfect because it would fit “beautifully with what we see as this big shift” in the American EV market. In today’s market, he said, “a lot of people ask themselves, Am I gonna get an electric car? Well maybe the next one.” He better hope they’ll start buying that next one in 2026.
Even if they do, Rivian may still have to confront the problem that Tesla has changed the EV market before Rivian could get there. When the first Tesla Model 3s were delivered in 2017, the sedan was instantly one of the best EVs on the market — because it was one of the only EVs on the market. Now every automaker in the world has plans to compete at the Model 3’s price point.
Rivian’s fortunes don’t rest entirely on American consumers; it also sells vans to commercial fleet operators, as well as delivery trucks to Amazon. (Amazon owns about 17% of Rivian.) But that business can be lumpy. Rivian’s vehicle growth slowed down last quarter, for instance, almost entirely because of a near pause in sales to Amazon, which sets up fewer new vehicles in the fourth quarter. If Amazon is willing to bail out Rivian, in other words, it’s not yet clear in the data.
None of this is to say that the company’s outlook is dire. Rivian was always going to find itself at a moment like this, when its expenses exceeded its revenue by such a large amount. The automaker already has devoted fans, and many people — myself included — are interested in the R2 as a potential first EV purchase.
And the company has shown that it can make strides in a single year. Twelve months ago, I had never seen a Rivian on the road before; today, one is regularly parked on my block. The company rocketed from a standing start to become the No. 5 best-selling electric car brand in America last year. What the company has done so far is impressive. But now it must prove that it can be great.
Editor's note: This story has been updated to correctly reflect Rivian's cash burn rate.
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Wildfires in France and Spain — and a dire El Niño forecast — point to another era of public attention on disaster.
Wildfires and the Return of Climate Politics
Enormous wildfires are still burning in France and Spain. “We're facing a completely unprecedented fire,” French President Emmanuel Macron said on Monday, comparing the situation to World War II. The main fire in Gironde, a southwestern department along the Atlantic coast, have consumed more than 100,000 acres and forced roughly 200,000 people to evacuate.
There’s little sign the fires are under control in either country. In France, the blazes created a pyrocumulonimbus cloud — a towering, thundering “fire storm” that sometimes forms in the western United States but is not often observed in western Europe. Some fires have come within several miles of Bordeaux, the country’s sixth-largest metropolitan area and a longtime center of the wine industry. In Spain, enormous wildfires near Madrid, Ávila, and Toledo have killed one and displaced roughly another 79,000 people.
Firefighters are working fast, in part because a heatwave is forecast for the continent later this week. But of course it is hot — it is high summer in the Northern Hemisphere, and we are having a particularly hot year. 2026 now looks likely to be the world’s second-warmest year ever, and it has a better than one-third chance of being the warmest.
In the near term, expect more climate-addled disasters. The Pacific Ocean has slipped into its El Niño phase, which will likely spin off more extreme storms, droughts, heat waves, and wildfires. Recent modeling suggests it could be the most intense El Niño ever measured. Writing for his newsletter “The Climate Brink,” the climate researcher (and Heatmap contributor) Zeke Hausfather recently warned: “It looks like this year’s El Niño is not only very likely to be the strongest event since reliable records began — it may end up the strongest by a truly mind-blowing margin.”
How do we know this next El Niño will be bad? The most intense El Niño on record occurred from late 2015 to 2016, when sea surface temperatures in a benchmark region of the Pacific Ocean were 2.75 degrees Celsius warmer than normal. (That’s nearly 5 degrees Fahrenheit.) Those searing sea temperatures released huge amounts of heat into the atmosphere and eventually made 2016 the warmest year ever recorded. Today, a decade later, 2016 remains the fourth warmest year on record, coming in only under 2024, 2023, and 2025, per NOAA data.
But as Zeke writes, the middle 80% of modeled outcomes for this year’s El Niño are already projected to match or exceed that 2016 anomaly. The median forecast for this year’s event, in other words, would shatter the previous record. “The models are forecasting something outside the envelope of anything we have ever observed,” he writes. The National Weather Service agrees that there is an 81% chance of an event forming “that would rank among the largest El Niño events in the historical record going back to 1950,” and it says odds are better than 97% that the anomaly will stick around through spring 2027.
Scientists and activists once hoped that when global warming’s effects became unignorable, the public would take action. But disasters haven’t produced durable climate concern, and public attention has dissipated with every news cycle — and become ever more pessimistic. There are moments, however, when successive extremes can keep climate change more prominently in the public conversation. The years that followed the last mega-El Niño in 2016 made up one such period. If we are headed for another now, then experts should be ready with ideas not only for slowing and reversing the growth of heat-trapping emissions, but also for adapting our societies and infrastructure for our warming world. It’s clear we are going to need them.
This will be a big week for understanding the U.S. energy economy’s most important trend. A handful of tech companies driving the artificial intelligence boom — namely, Microsoft, Meta and Amazon — will report their quarterly earnings on Wednesday and Thursday. These companies are behind some of the country’s largest AI data center projects and therefore some of its most sizable planned power plants — clean and otherwise.
Last week, when Alphabet boosted its capital expenditure for this year by another $15 billion, the market rebelled and sent its shares tumbling. If investors’ interest in financing mega-scale data center projects is waning, then it could affect the electricity economy for years to come. In any case, we’ll know more soon. Rivian will also report its earnings this week.
Can AI help emergency managers make faster decisions when every second counts?
Meteorologists had nothing polite to say about Tropical Storm Bertha. The “weak, disorganized, and lopsided” system made initial landfall in Louisiana last week as a “hot, sheared mess,” one that forecasters doubted would reach Texas with much oomph at all. Still, the Galveston County Consolidated Drainage District — the local flood mitigation and drainage management entity for the state’s most flood-prone county — had stood at the ready, posting updates on the storm’s progress to its Facebook feed in the lead-up.
There had been action behind the scenes, too. Since this spring, the county has relied on a new “AI-powered flood warning solution” pilot program to help local administrators identify the gaps in their understanding of the county’s flood risk and monitor rising water levels in real time. In a crisis, a chatbot could even advise them on when to issue an evacuation order.
“Imagine you’re an operator and you have to tell people to leave their homes because of floods coming in,” Todd Barr, the CEO of Axonis Decision Intelligence, which has partnered with the smart water-level sensor company Simplicity Integration in Texas’ Galveston County, told me. Axonis provides AI-assisted decision-making tools to clients in a number of time-sensitive industries, and in every case, “You want a paper trail of the data you used to make the decision — the reasoning and the model you used — and our platform does all of that,” Barr went on.
Issuing evacuation notices is a famously thorny business, and one that has resulted in high-profile and high-casualty failures, including in the Paradise, California, and Maui wildfires. Particularly noteworthy were the 2025 Kerr County floods that killed more than 100 people in Texas’ Hill Country after local officials took 90 minutes to send phone alerts once they became aware of the rising river.
In many cases, particularly in more rural counties, the teams making the evacuation decisions are small and lack sufficient training not only on when to make such a call, but even on how to word it. “The people who are put in the position of issuing the messages are doing 20 other things at the same time,” Jeannette Sutton, a researcher at the University at Albany’s Emergency and Risk Communication Message Testing Lab, told me when I reported on evacuation notices after the Los Angeles fires.
As for Galveston, “100%” of the buildings on the densely populated island are at flood risk, with modeling suggesting a worst-case-scenario hurricane could produce 26 feet of storm surge. Much of the city’s stormwater infrastructure additionally predates modern climate-change-intensified rainfall probabilities, with the district in the midst of a $54 million drainage project aimed at mitigating future flooding by building a pump station and enlarging sewer lines.
As part of the region’s ongoing resiliency work, the Galveston County Consolidated Drainage District installed seven of Simplicity’s water-level sensors —the county’s first — at locations on the mainland. (There are no sensors currently on Galveston Island proper.) Simplicity’s Axonis-powered system, SI-Ai, also pulls in data from NOAA, the U.S. Geological Survey, and Houston’s Harris County to present residents of the entire region with a live flood-risk dashboard, complete with intuitive green-yellow-red indicators to evaluate their neighborhood hazard level in real time. Operators also have their own proprietary dashboard where they can monitor sensors and are prompted to ask questions to interpret readings and open “investigations” if something appears amiss.

“If I’m the municipality, I can say, ‘Okay, here’s what the forecast is looking like and what is potentially going to happen,” Alison Reese, the COO and co-founder of Simplicity, explained to me. “Then I could ask a question like, ‘Hey, what other locations in this watershed are at high risk for flash flooding?’”
That’s where Axonis, the artificial intelligence company, comes in. “Today you would have to be like, ‘Alright! Get the weather report, quick! What’s happening? What are the sensors saying? Okay Bill, now what’s the upstream sensor saying?’” Barr said, acting out the frantic scenario of trying to source data from multiple streams at once. “All of that is what we’re automating.” (Galveston’s Office of Emergency Management is “not the POC for the flood sensor operations,” a representative told me; the drainage district oversees the Axonis-Simplicity partnership, and did not return a request for an interview. The mayor of League City, a city 35-minutes north of Galveston that is also managed by the district, has publicly criticized the SI-Ai program as a separate sensor network that duplicates the work of the Harris County Flood Control District.)
Working from the assumption that emergency managers have to parse reams of data in short periods of time — flash floods can rise as much as 10 feet in an hour — Axonis provides what is essentially a chatbot for authorities to query potential decisions ranging from road closures to evacuation notices, based on feedback from the sensors. It stops short, however, of having a dialogue box that pops up to tell operators, EVACUATE THIS NEIGHBORHOOD NOW.
When Barr demoed the program to me, he had the tool configured to create a credit risk review memo for a would-be banking client. (Axonis also has customers in the banking and defense sectors.) The dashboard essentially functioned the same as it would for Galveston County, though, and his investigation returned the kind of simplified, emoji-studded one-sheet that users of large language model-powered AI interfaces would immediately recognize. In this case, the tool identified a “🔴Risk Alert CANDIDATE” — Barr said that would be a particular sensor, in the case of Galveston — and followed it with a summary and bullet-pointed sections breaking down “⚠️Credit Risk Indicators” and “💧Liquidity Position.” (In a screenshot of an example flood report for Simplicity, shared with me, those sections were replaced by “📍Site Location” and “💧Water Level — Last 72 Hours.” I wondered what else was possible: “🌊Historic hydraulic risk”? “💀Vulnerable Populations”? )

The system then takes operators through a four-step decision-making model based on the OODA Loop, a common workflow in military contexts that involves justifying actions through evidence-based observations. “We always keep a human in the loop on these things, at least today in 2026 — though who knows in two or three years,” Barr said. He clarified in a later conversation with me, though, that “Axonis and [AI] tools should never tell you to evacuate now. It should tell you the information you need to make that decision.”
That was a point Barr stressed numerous times during our conversation: That Axonis’ chatbot is intended as a brainstorming tool or sounding board, and one that keeps a careful paper trail, “cryptographically sealing” any eventual decisions for review and attestation later. I likened it to a police body camera, and Barr didn’t dispute the similarities. “It’s an accountability tool,” he told me.
Of course, that means the burden of decision-making still falls on potentially fallible humans. I worried in particular that by sharing the responsibility with AI, human operators might get lazy or fail to properly question a decision the program might be leading them toward, particularly in an instance of hallucinated data. To the latter point, Barr told me that this is part of what Axonis is designed to address. “You can’t just take the sensor data and throw it into Claude and be like, ‘Alright, go make a decision for me.’ You need to set guard rails,” he said.
As to the former point, Barr told me the chat includes a disclaimer reminding its users that AI can make mistakes, and that the company trains its customers on how LLM technology works. “At the end of the day, it’s a tool, not a decider,” he said, although he allowed that it might be used to automatically trigger warning lights, sirens, or barriers, such as closing a flooded roadway.
I also posed the concern about complacency to Ali Mostafavi, a professor who supervises the UrbanResilience.AL Lab at Texas A&M, which researches, among other things, how artificial intelligence might be utilized in emergency contexts. Mostafavi agreed that there is always a risk in cognitive outsourcing, but that there is a “counter-argument that is also valid — that without these technologies, we have seen what can happen. We had the catastrophic floods last year in Kerr County, and if a similar technology had existed back then, an automated system could have identified the flash flood, and many young children would be alive today.”
Still, Barr told me he isn’t aware of Axonis advising in an actual evacuation order yet. While it is operational, the predictive model remains untested against its highest-stakes use case: the extremes of a climate-changed world, where formerly unthinkable outcomes may be one storm away.
“The more we can stress-test these technologies in real operational settings and use that feedback loop to improve the technologies, the better,” Mostafavi said. “But that’s easier said than done, because to have a technology implemented in an operational setting it should already be stress-tested, right?”
Bertha, though, was not that reckoning; the gusty squalls blew through Galveston last week without even disturbing the dinner reservations at the marina. But although it was already back to 90 and sunny by Monday morning on the Texas Gulf, the drainage in Galveston County, as in many places around the country, remains outdated and easily overwhelmed. One day, inevitably, the water will come. Hopefully when it does, someone or something will be watching.
The large renewables developer changes tack “in response to federal energy objectives.”
Trump’s solar freeze is now so tough that at least one renewable energy developer has asked his administration to turn their permitting application into a data center and gas-fired power plant instead.
Renew Development HoldCo – an LLC created by Clearway Energy Group – wrote the Bureau of Land Management in April asking if they could amend their 2021 application to build the Amber solar project, a 500-megawatt solar project in the Nevada desert that would require building on federal land. Their requested change? “[T]o formally remove the proposed solar facility and replace it with the development of a proposed data center and natural gas facility,” according to a copy of the letter I obtained.
“This amendment is the result of a shift in our internal development priorities and an updated assessment of project timing, in order to better align with the goals of our Administration,” reads the letter, which is dated April 3 and signed by Clearway’s chief development officer John Woody. “The data center concept is in exploratory early stages and as such has a longer and more flexible development horizon, and we believe its schedule will better align with the Bureau’s current workload and staffing plans.”
Now, this swap is somewhat shocking but shouldn’t exactly be a surprise. Companies with federal energy leases are struggling to get their renewable projects permitted by a hostile Trump administration. We’ve already seen some offshore wind developers ditch their leases in favor of payouts and commitments to build more fossil infrastructure. Clearway Energy Group is owned by Global Infrastructure Partners and TotalEnergies, the latter of which struck such a deal in March.
But this does appear to represent an aberration for Clearway, one of the nation’s largest operators of renewable energy projects and whose marketing materials primarily focus on “clean energy.” Nearly all of the company’s portfolio is carbon-free power or energy storage generation sans a handful of “flexible generation” energy projects in California, according to an online map of their project pipeline. The company did not disclose in the documents I reviewed if the gas plant itself would power the data center, provide power to the wider grid, or both.
Candidly, I’ve been watching like a hawk to see if Trump’s chokehold on solar and wind permits would lead to more gas infrastructure and data centers on federal property instead. And companies are getting data center permits when they ask to swap out their solar farm for AI infrastructure. On Friday, I reported that a joint venture involving renewables developer Arevon and energy trader Bill Perkins got permission from BLM to switch an environmental permit tied to a solar farm for one allowing a new data center. Environmentalists plan to legally challenge BLM’s determination as they say it’s a test case for the future of federal land policy.
It’s unclear if Clearway would be the one to build and construct this hypothetical data center and power plant. I for one can’t find any evidence of Clearway developing data centers before. My best guess is that if they do move forward with this, it would look like the joint venture I covered on Friday, where Arevon distanced itself from the actual day-to-day operations of the development and a new firm specializing in data centers came in. But that’s just a hunch and there’s a saying about assumptions.
Nevertheless, Clearway is clearly handling the permitting side. Attached to the Clearway letter was an application also sent to BLM for constructing utility and telecommunications facilities on federal lands, a document technically known as an SF299. The application states Clearway considered using solar energy for the data center as well as using private land, but their alternative designs weren’t selected because they had “higher environmental and stakeholder conflicts.”
Also, in a section of the document requesting Clearway provide a “statement of need for the project,” the developer said it was submitting this proposal “in response to federal energy objectives” and specifically cited Trump’s Day 1 executive order which the company said “encourage[d] development of reliable energy projects on federal lands.”
I reached out to Clearway asking for more information on the letter and application. In response, the company claimed the solar project wasn’t being killed – it simply was moved to private land. They also declined to comment on the data center and gas project. Instead, I was provided a statement attributable to an unnamed spokesperson that “while we do not comment on any individual application while it moves through federal approval processes, we are pleased to be advancing more than 4 GW of solar and battery resources in Nevada on private and public lands and expect those projects to deliver tremendous economic benefits to the communities where they’re built.”
“Clearway values its strong working partnership with the BLM, its Southern Nevada office, and also with state and local interests in Nevada. Across all of these relationships, we continuously assess how best to develop and deliver infrastructure that meets needs and aligns with local and national policies and goals.”