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Donald Trump Watches SpaceX Launch Its Sixth Test Flight Of Starship Spacecraft
Elon Musk speaks with President Donald Trump as they watch a SpaceX launch (Brandon Bell/Getty Images)

SpaceX and Tesla are sounding very similar these days

Elon Musk’s AI rocket company has a lot in common with his AI vehicle company.

Rani Molla

Yesterday, Elon Musk announced that his space company, SpaceX, was acquiring his AI company, xAI. The vision for the newly merged company, expected to go public this year, sounds a lot like Musk’s other public company, Tesla. That resemblance may be more than rhetorical: Bloomberg previously reported that SpaceX had explored a merger with Tesla.

And at a high level, Tesla and the newly combined SpaceX-xAI appear to be pursuing the same strategy, just in different environments, a convergence that makes a future merger at least conceivable.

Grand mission, unlikely goals

Neither company presents itself as selling a product so much as advancing humanity to a place where people will have more than they could ever want or need. Tesla’s stated goal is to accelerate the transition to sustainable energy and, more recently, to build general purpose autonomy and humanoid robots in order to create what it calls “sustainable abundance.” SpaceX-xAI’s pitch is even grander: scaling intelligence, harnessing the sun’s energy, and extending human consciousness “to the stars.”

In both cases, the mission language is so expansive that trifling things like quarterly reports, cars, and even satellites can seem almost beside the point.

Both companies share a willingness to state goals that sound implausible — and that’s largely the point. Tesla openly talks about fully autonomous vehicles that generate revenue while you sleep and AI humanoid robots that will do nothing less than “eliminate poverty.” SpaceX-xAI talks about million-satellite constellations, terawatts of space-based compute cooled by the vacuum of space, and tapping more of the sun’s energy than human civilization currently uses. (Note that serious thinkers don’t actually think any of this can happen.)

Improbability is framed as evidence of seriousness. If the goal sounds reasonable, it probably isn’t ambitious enough.

Vertical integration and scale as strategy

For both Tesla and SpaceX-xAI, scale isn’t the payoff; it’s the mechanism. Vertical integration is how it gets there.

Tesla’s push to make affordable EVs forced it to pull batteries, software, chips, manufacturing equipment, and sales in-house. Unlike other autonomous vehicle efforts, Tesla isn’t relying on partnerships. Each added layer reduces reliance on suppliers and unlocks more production. Of course, now Tesla is capable of building way more vehicles than it’s been able to reduce price points enough to sell. (Tesla car deliveries fell for the second year in a row in 2025.)

SpaceX-xAI applies the same logic at a different altitude. Building global internet access drove it to build reusable rockets with a high launch cadence. Now, scaling AI compute is pushing integration even further: rockets, satellites, power generation, connectivity, and AI models designed as a single system. Ambition at this size becomes a forcing function, driving advances that wouldn’t emerge at smaller scales.

The argument is the same in both cases: when goals are big enough, markets can’t move fast enough. To build at Musk-speed, his companies have to own the whole production chain.

Physics first, economics later

Traditional business logic plays a surprisingly small role in both narratives. Instead, everything is reduced to first principles: energy density, mass, watts per ton, launch cadence, learning curves.

The assumption is that once the physics works, the economics will fall into place. Cheap batteries unlock cheap cars. Cheap launch unlocks satellites. Cheap power and compute unlock better AI. Profitability is treated less as a goal than an inevitability.

Meanwhile, skepticism is framed less as a warning sign than as a failure of imagination.

Beyond their narrative similarities, SpaceX and Tesla already have the same CEO as well as numerous business relationships.

SpaceX pays Tesla for “commercial, licensing and support agreements,” while Tesla pays SpaceX for Musk’s use of its jet, for example. The companies collaborate and have shared employees and resources.

As the two businesses pursue similar ends, it’s likely those relationships could grow stronger.

Or, it’s possible they make it official. After all, Elon Musk loves dealmaking, and he clearly has bankers on speed dial. Before Musk’s SpaceX merged with xAI, xAI merged with X. Years ago, he merged Tesla with SolarCity. When he decided he wanted Twitter, he bought it.

Joining Tesla and SpaceX almost seems like a natural progression of Musk’s consolidation.

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White House releases AI legislative framework

The White House has released its policy wish list for AI legislation — and what it wants excluded.

Still, the odds of any actual AI regulation getting passed in Congress right now are very slim.

The “National Policy Framework” for AI lays out seven issues that the Trump administration wants to see reflected in any congressional action around AI.

The items listed in the framework include:

  • Child safety protections, age verification, and parental controls for AI.

  • Data center projects voluntarily pay their own way when it comes to power, but incentives should still be encouraged.

  • Copyright laws should allow for training models on copyrighted works, while protecting individuals’ voice and likeness.

  • Free speech should be defended for AI systems, preventing the government from pressuring companies to ban or alter content based on partisan agendas.

  • A light touch to regulation to encourage innovation, and no federal agency to regulate AI.

  • American workers vulnerable to AI job replacement should be retrained and supported.

  • Federal AI rules should preempt any state AI legislation to prevent a patchwork of laws that companies would hate.

The policy list is the latest in a series of proposals from the AI-friendly Trump administration.

The items listed in the framework include:

  • Child safety protections, age verification, and parental controls for AI.

  • Data center projects voluntarily pay their own way when it comes to power, but incentives should still be encouraged.

  • Copyright laws should allow for training models on copyrighted works, while protecting individuals’ voice and likeness.

  • Free speech should be defended for AI systems, preventing the government from pressuring companies to ban or alter content based on partisan agendas.

  • A light touch to regulation to encourage innovation, and no federal agency to regulate AI.

  • American workers vulnerable to AI job replacement should be retrained and supported.

  • Federal AI rules should preempt any state AI legislation to prevent a patchwork of laws that companies would hate.

The policy list is the latest in a series of proposals from the AI-friendly Trump administration.

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WSJ: OpenAI rolling everything into one desktop “superapp”

OpenAI is trying to eliminate distractions and focus on building AI that helps with enterprise productivity tasks like coding and organizing spreadsheets.

As part of that effort, the startup is consolidating some of its side quests into one superapp, according to a report from The Wall Street Journal.

The plan is to merge ChatGPT, Codex, and the Atlas browser together, as it seeks to focus its efforts as it competes with Anthropic and Google for lucrative enterprise customers.

OpenAI Head of Apps Fidji Simo told staffers in an internal memo that “we realized we were spreading our efforts across too many apps and stacks, and that we need to simplify our efforts. That fragmentation has been slowing us down and making it harder to hit the quality bar we want,” per the report.

The plan is to merge ChatGPT, Codex, and the Atlas browser together, as it seeks to focus its efforts as it competes with Anthropic and Google for lucrative enterprise customers.

OpenAI Head of Apps Fidji Simo told staffers in an internal memo that “we realized we were spreading our efforts across too many apps and stacks, and that we need to simplify our efforts. That fragmentation has been slowing us down and making it harder to hit the quality bar we want,” per the report.

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