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Spoiler: None of them feels great.

“Delete, delete, delete,” Elon Musk reportedly told his biographer, Walter Isaacson, describing his approach to management. “Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn't delete enough.”
Musk has taken his own advice: He is slicing to the bone. Earlier this week, he dismissed the head of Tesla’s Supercharger network, Rebecca Tinucci, as well as her more than 500-person team. As of today, Tesla has only a barebones crew, at best, tasked with maintaining and expanding its high-speed car charging network. It has already pulled out of a planned expansion in New York City.
Musk also laid off what remained of the company’s policy and new vehicle teams. These severe cuts follow layoffs announced in March, when Musk dismissed about 10% of Tesla’s employees. According to Electrek, the two events may be related: Musk asked Tinucci to make deeper cuts in her team in April, she pushed back, and he fired her to set an example. The company has cut more than 14,000 employees worldwide since the beginning of the year.
The news is — and there is no way of sugarcoating this — either sort of stupid, bad, or very bad for the electric vehicle transition. Here are three ways of looking at it:
Over the past year, every other major automaker in the United States has switched to Tesla’s charging plug, the North American Charging Standard, or NACS. They have struck deals that will let them use much of Tesla’s existing Supercharger network; Ford is in the process of mailing its drivers a free NACs adapter plug. These agreements were meant to give consumers more certainty about the EV transition: No matter what car they bought, they would be able to use most of Tesla’s superior charging network.
Now, that certainty is gone. Which chargers will work in the future? How much more will the Tesla network expand? And what will happen to those deals with automakers now that the Supercharger team is gone? The employees laid off this week included those who worked closely with other companies.
At least publicly, Ford is keeping its cool. “Our plans for our customers do not change,” Marty Günsberg, communications director for Ford’s electric vehicle division, told Heatmap. And yet contractors and others with business in front of Tesla's charging team were left completely in the dark Tuesday, their emails bouncing back from addresses that no longer existed, according to E&E News. No other equivalent charging network exists in the U.S., meaning there's no other easy place for them to go.
Musk, for his part, has intimated that the company will begin to look into wireless charging. Although wireless charging may make slightly more sense for self-driving cars — the car could drive itself into a given spot, et voilà! — it is a puzzling decision from a man who has said the only real constraints are those imposed by the laws of physics. More than half of current and prospective EV owners say that they worry about charger availability and convenience, yet wireless charging is slower and less efficient than wired charging, meaning it will require more charging spots and each vehicle will have to stay there longer.
So again we must ask, why? The answer may lie in the animal spirits of the market — and Elon’s dependence on the market for his personal wealth. Tesla’s stock has more or less held steady since the cuts. As my colleague Matthew Zeitlin wrote, Musk has spun the layoffs as part of a corporate turn away from selling electric vehicles, chargers, and home batteries and toward achieving artificial intelligence and autonomous driving.
That is partly because Musk must keep justifying — or, if we really want to be blunt, propping up — Tesla’s astronomical share price, which itself is premised on the idea that Tesla is a technology company, not a car company. In order to do that, he must continually steer his sometimes-profitable company toward the buzziest, most hyped-up phenomenon in the economy. Never mind his actually existing EV charger business; that can’t justify the fantasy of the share price. He needs to find something new.
One of the more useful ways of understanding Elon Musk is that he seeks to create and control private infrastructure. SpaceX creates privatized access to rocket launches. Starlink allows for privatized access to the global, satellite-provided internet. The Hyperloop — to the degree that it existed at all — sought to create a privatized and individualized form of mass transit. (Musk, fittingly, hates public transit.) Even Musk’s purchase of Twitter, now rechristened X, reflected a desire to enclose the public sphere.
And for the past year, you could understand Tesla in the same light. Sure, Tesla was an electric vehicle company. But it was rapidly becoming an infrastructure company. Through its deals with other automakers, it was cementing itself as the premier provider of electric vehicle charging in the United States. It was also the part of the company that elicited the least suspicion from Tesla’s many critics. Drivers might not always be able to rely on a third-party charger, but a Tesla Supercharger? It worked.
It hasn’t always been this way. For years, the Supercharger network seemed like Tesla’s key competitive advantage, its Warren Buffett-style moat. If you wanted access to America’s most famous and reliable fast-charging network, you had to buy a Tesla. But starting with Ford a year ago, Musk struck deals with other automakers allowing their cars to use some of its charger network. At the same time, Tesla also bowed to federal pressure and standardized its NACS charger with SAE International. That helped it win more than $17 million in grants from the Bipartisan Infrastructure Law to build even more chargers.
Why pull back now? None of the options is very encouraging. The most hopeful answer is Tesla-specific: Maybe demand for the automaker’s vehicles is sinking so quickly that Musk is, in essence, reaching for things he can throw overboard. Tesla has historically relied on Chinese consumers to buoy its sales, but it has hemorrhaged market share in China as the country’s home-grown automakers have come out with newer and often superior EVs. But things there took a turn for the better earlier this week as Musk won approval (albeit conditional) to use Tesla’s so-called Full Self-Driving software on Chinese roads. And even if a sales slump were the explanation, why also ditch the team working on new vehicles at Tesla?
The other possibilities are bleaker. BloombergNEF has ballparked that Tesla’s charging business could generate $740 million in annual profits by 2030. But that relies on Musk’s estimate that the Supercharging business has a 10% margin. If that margin has since shrunk — or if its chargers just aren’t getting used as much as Tesla once anticipated — then further investment right now might not make sense.
That’s a problem, though, as most prospective buyers say that there need to be even more public chargers before they would consider buying an EV. If the economics don’t justify a further investment in chargers, however, even with all that apparently pent up demand, then the country is in a pickle. In that case, Musk’s decision looks self-defeating, a panicky and downturn-averse reaction that will ultimately undercut the market for Tesla’s cars.
About the only bright spot here is that Musk has surrendered hundreds of the most talented charging employees to the market. Tesla excelled at using a mix of policy and engineering prowess to integrate their chargers into local utilities’ systems and rate structures; other automakers can now snap up the people with those skills.
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The data center boom is everywhere you look in U.S. economic and emissions data.
This is an edition of Heatmap Daily, an evening review of the day’s news written by our executive editor. Sign up for it here.
It isn’t exactly a new thought, but I’ve been struck recently by how many trends in America’s economic and environmental data are fundamentally about the data center boom and the return of electricity demand:
First, the Energy Information Administration reported this week that U.S. emissions grew by more than 2% last year, driven by surging electricity demand and an increase in coal-fired generation.What caused that higher power demand? New factories and data centers — as well as record summertime cooling demand.
Second, many of the new factories driving that higher power demand are themselves producing goods that are … let’s say … data center-adjacent. There are the enormous new semiconductor fabs, of course. But Ford and General Motors have also set up new production lines (or repurposed old ones) to manufacture grid-scale batteries to meet power demand.
Third, take a look at the recent U.S. spending on private non-residential construction — in other words, everything American companies are building that is not houses, condos, or apartments.
The construction industry’s spent almost $60 billion on data centers over the past year, which is more than it spent on all other office buildings combined (and more than it spent building warehouses, too). Just a handful of categories — data centers, power plants, electricity infrastructure, and certain kinds of electronics manufacturing — now make up a third of all U.S. private non-residential construction investment. They’ve never made up such a large share of construction spending since data collection began in 2014.
As The New York Times recently noted, the American economy is unusually dependent on the American stock market right now — and the stock market is unusually dependent on artificial intelligence. This week, investors started to balk at the enormous spending hyperscalers are planning to keep building out the AI boom; Alphabet’s shares dropped 8% this week after it boosted its planned 2026 capital expenditure and signaled 2027 will be even bigger. If the data center boom started to slow down in earnest, then more than just that budget will change.
Speaking of which, my colleague Emily Pontecorvo wrote earlier this week about how many businesses are struggling to even estimate their carbon emissions from artificial intelligence. The carbon accounting startup Watershed recently unveiled a new formula to help companies get a sense of their AI-related emissions.
But even that formula is still limited by the amount of data hyperscalers publish — and they don’t publish that much. Google, for instance, is the only AI company that has (laudably) provided estimates of its emissions on a per-prompt basis. Yet no company has published its per-token emissions, or how emissions sync up with particular models or regions.
So Emily asked Google: Why aren’t you — or any other model provider — disclosing this kind of data yet?
The tech company didn’t get back to us until after we’d published Emily’s story. But its response was interesting enough that I wanted to quote some of it here.
The problem is “industry consensus,” Cooper Elsworth, a Google spokesperson, told us. “There is currently very little consensus on how to comprehensively and fairly measure the serving environmental impact of generative AI (such as text generation),” he wrote. “Without standardized, ‘apples-to-apples’ frameworks, it is difficult to compare different providers accurately.”
That’s partly because energy use — and emissions data — can vary from site to site and depend on “custom-built hardware, software compilers, and advanced inference techniques.” And he claimed Google doesn’t always have the measurement hardware in place to provide such specific estimates: “Providing precise, repeatable data requires highly advanced measurement infrastructure,” he said. “For example, software-based energy monitoring tools often suffer from sampling biases. For our study, we had to step away from top-down averages and directly measure actual energy at the physical power supply unit (PSU) level across our deployed fleet. Not all providers have the telemetry or data sets required to benchmark their operations at this level of granularity.”
Read Emily’s story to understand the other reasons why estimating — or even “guesstimating” — AI-related carbon emissions is so challenging.
A conversation with Emma Uridge of the Kansas Health Institute.
This week’s conversation is with Emma Uridge, analyst with the Kansas Health Institute. Uridge spent copious hours analyzing state and local laws on data center development to best understand how policymakers are responding to the potential environmental public health impacts of large AI infrastructure, including power and water. The report, which came out this week, also goes in depth into those health impacts. I reached out to her to discuss what she sees as must-watch territory for our readers on this emerging policy arena.
Our conversation was lightly edited for clarity.
What is actually being done on policy when it comes to data centers — beyond moratoria of course?
So first I’d like to just talk about the point of moratoria. It’s helpful to talk about how these policies emerge in the first place. One area where moratoria are helpful is when a data center is proposed but the county has no approach for how they’d like to potentially regulate them. That’s temporary, most of the time. It lets local governments conduct research on the various impacts and also negotiate community benefits, ones that can mitigate any potential negative impacts — like Lancaster Pennsylvania, which instituted a community benefit agreement that maximized the potential benefits of development while mitigating what large data centers can do. That agreement looked at capping municipal water use at 20,000 gallons per day and requiring 100% clean energy. It had financial penalties for non-compliance. The company also committed $20 million to their local economic development and clean energy fund. There are ways to negotiate with developers.
We also see amendments to existing zoning. Data center proposals are increasingly popping up in rural areas, many of which are unzoned, so there’s no way a county can negotiate unless there’s a moratorium in place.
Other policy solutions include different performance standards or requiring on-site renewable energy, like what Jefferson County, Missouri, looked at. Also setback requirements, mandatory noise buffers, ending by-right zoning.
Where are local governments getting ideas for regulating data centers?
A lot of the technical information comes from developers. That can in cases be seen as a biased source of information. I wouldn’t say there’s a dedicated group providing assistance to local governments when a project is proposed — which is a similar story to wind industry development, where we have only a handful of consultants who provide technical advice. It can be really helpful to get a multi-disciplinary approach to hearing information. It can be helpful to have the utility commission, public health folks, those in academia, as well as the developer.
As of right now, especially in rural areas, local governments have a hard task of balancing pushback while getting the most accurate, evidence-based, neutral information to make decisions. That balance can be contentious.
What is the federal government doing on data center policy? How is the Trump administration approaching it?
A few things there. In the early days, the drive was for AI expansion and to be competitive with foreign adversaries. Now due to the amount of public pushback in red and blue localities and a more cautious approach.
I’m not seeing a lot of actual policy movement at this time.
I know the EPA is looking at the chemicals used in cooling data centers because when that water is cycled through the system, some of it is discharged into the water system, so they’re looking at the Toxic Substances and Control Act for monitoring that.
How much of an impact does this minimal federal role have on industry behavior?
Y’know, this isn’t specific to data centers. This is true for all kinds of large-scale development: there’s a need to require some sort of federal monitoring and regulation.
That’s where I see an emerging role for public health. At the federal level, there could be policy movement towards requiring some sort of environmental monitoring at data centers to make sure they’re operating responsibility. Looking at specific water use relative to water availability and what happens when there’s a time of severe, persistent drought. With air quality too — we’ve seen areas where the grid isn’t as reliable so their diesel generators are kicking on more and affecting air quality for residents.
We’re just not seeing all of that right now. We need corporate disclosure.
What do you see as the most important public health impacts from data center development?
It varies by localities. The most discussed obviously is water usage. One thing I’d note about my conversations with folks enthusiastic around emerging tech is, there are still questions that need to be asked about the capacity of localities to support a data center. Like a small town in Kansas may only be using 40% of their water for their utility needs. If a data center came online, how much of that water goes to the data center?
One area underexplored within the public health discipline is energy poverty and energy security. The ability of a household to meet the needs of everything energy provides in our lives. It’s known we have an aging electric grid but we’re not talking enough about large-scale blackouts when the grid is not sufficient to support some of these new data centers.
Plus more of the week’s big development fights.
1. Laramie County, Wyoming — Meta is fighting the fine it received in the Cheyenne data center water pollution controversy, and the conflict between the tech giant and the city’s small board of public utilities is continuing to spill out into the public.
2. Niagara County, New York — This county just rejected a solar project’s highway work permits in a show of retaliation against the state’s Office of Renewable Energy Siting.
3. Barron County, Wisconsin — The anti-solar protest is the new campaign stop in deep red Wisconsin.
4. Chesapeake, Virginia — A large battery storage project on the Virginia coastline is on the rocks amidst rampant local opposition.
5. Lewis County, West Virginia — West Virginia is now a key battleground in the fight over transmission, as a line spanning all of West Virginia and Maryland — and cutting through Data Center Alley in Virginia — causes compounding consternation.