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Tesla’s Elon Musk details Model Y manufacturing improvements, insight on design
Tesla CEO Elon Musk recently revealed improvements the all-electric car maker has made to its production process for the Model Y crossover SUV. In an interview on Ride the Lightning podcast, hosted by Ryan McCaffrey, Musk discussed lessons learned from Tesla’s prior transition from the Model S to the Model X as applicable to the Model Y, as well as decisions made from the vehicle’s outgrowth of the Model 3. He additionally provided some insight on the design decisions behind the Model 3, which also carry over to the Model Y’s design.
Musk and McCaffrey’s discussion about the Model Y production process began with the question, “What are the biggest lessons learned from the Model 3 program that you’re applying to the Model Y?” However, Musk indicated that a more relative learning comparison came from Tesla’s design of the Model X and its departure from the Model S.
“The Model X ended up being a radical departure from the S…with the Model Y, we wanted to avoid the technology bandwagon we had with the X. It should have been easy going from S to X, but instead, it was hell because of so many new technologies…It would be too risky to the company to do that with the Y,” Musk explained.
I'm celebrating episode 200 of Ride the Lightning, my weekly @Tesla podcast, in THE BEST way possible: a 1-hour interview with @elonmusk himself! 🥳 I can't wait to share our conversation with all of you! It airs this Sunday, June 2 @ 9am ET/6am PT on major podcast services. 🚗⚡️ pic.twitter.com/V0nFrU03Ir
— Ryan McCaffrey (@DMC_Ryan) May 30, 2019
The Model Y crossover needed to address the flexibility expected of vehicles in its class such as cargo capacity, seating for 6 or 7 people, and more ride height than a sedan. Tesla addressed these features while also keeping in mind the effect on battery range a larger vehicle might have, according to Musk.
“We tried to make the car as similar to the [Model 3] as possible except in the case where a change was necessary to achieve SUV functionality…[all] while still having a low drag coefficient and not increasing the frontal area too much,” he detailed. Overall, Musk concluded that CdA (automobile drag coefficient) and mass of the Model Y only affect 8-10% of the battery range when compared to the Model 3.
The design of Tesla’s Model Y and lessons learned from Model 3 production also led to some manufacturing improvements for the electric crossover. Musk detailed how the Model Y underbody was switched to aluminum casting instead of stamped steel and aluminum pieces, which greatly simplifies the moving parts involved in making the vehicle.
This change effectively means that initially, using two castings to make the structure will take the process from 70 parts to 4 (castings plus joiners), and once the “big” casting machine comes into operation, the process will have brought the process from 70 parts to 1 (casting only). Using casting over stamping reduces the weight of the Model Y, improves MHB (heat produced), lowers cost due to the smaller number of parts necessary, and significantly drops capital expenditure on robots.
As for the manufacturing location of the Model Y, Musk said the decision was not quite final, but the default place was Tesla’s factory in Fremont, California, with the runner-up being Gigafactory 1 in Sparks, Nevada. Producing the Model Y in Fremont would be the fastest way to bring the crossover SUV into production, according to Musk. “One choice isn’t natural over other,” he said. Freemont is producing the Model 3 and the two vehicles share 75% of their components, but Gigafactory 1’s location has a lower cost of living, meaning an overall better value for Tesla.
The similarities between the Model Y and Model 3 being what they are, Musk also discussed with McCaffrey some of the design decisions that initially went into creating the Model 3. In response to the question, “What’s the toughest design decision you had to make on Model 3?”, the CEO cited two primary factors that went into the midsize sedan’s creation: the touchscreen and the nose design.
Reducing the number of screens from two in the Model S to one in the Model 3 came with some pushback, Musk explained. However, he felt that owners would prefer an open view of the road, and everything needed while driving could be fit onto one screen.
This background brought up community rumors about a heads-up display (HUD) being included in Tesla’s vehicles. On the subject, Musk set the record straight – there was never any plan to include a HUD, nor will one be added in the future. He simply doesn’t like them, and the move to self-driving makes them pointless. “We discussed it, but I’ve tried various heads up displays and found they were annoying,” he said. “We felt the car would increasingly go to self-driving…As things are approaching autonomy, why project things you don’t even care about on the screen?”
Something that customers do care about, though, is the look of their car. Musk detailed the difficulties in making an attractive design for the Model 3, which wasn’t easy thanks to the lack of a front grill on the vehicle. “You don’t want to have the nose to look like Voldemort…You’ve got to get some character or it does not look good.”
Also mentioned was the decision to reduce the width of the Model 3 to 185 cm over the 195 cm of the Model S to help sell more cars in Japan. The country’s parking machines only accept cars up to 195.4 cm wide, which leaves very little wiggle room in the manufacturing process to meet. The change to 185 cm meant that any Tesla Model 3 could fit in any parking garage in Japan.
The Model Y is set to begin production in 2020, and reservations are currently open on Tesla’s website.
Listen to McCaffrey’s full Ride the Lightning podcast interview here.
Elon Musk
Tesla isn’t joking about building Optimus at an industrial scale: Here we go
Tesla’s Optimus factory in Texas targets 10 million robots yearly, with 5.2 million square feet under construction.
Tesla’s Q1 2026 Update Letter, released today, confirms that first generation Optimus production lines are now well underway at its Fremont, California factory, with a pilot line targeting one million robots per year to start. Of bigger note is a shared aerial image of a large piece of land adjacent to Gigafactory Texas, that Tesla has prominently labeled “Optimus factory site preparation.”
Permit documents show Tesla is seeking to add over 5.2 million square feet of new building space to the Giga Texas North Campus by the end of 2026, at an estimated construction investment of $5 billion to $10 billion. The longer term production target for that facility is 10 million Optimus units per year. Giga Texas already sits on 2,500 acres with over 10 million square feet of existing factory floor, and the North Campus expansion is being built to support multiple projects, including the dedicated Optimus factory, the Terafab chip fabrication facility (a joint Tesla/SpaceX/xAI venture), a Cybercab test track, road infrastructure, and supporting facilities.
Credit: TESLA
Texas makes strategic sense beyond the existing infrastructure. The state’s tax structure, lower labor costs relative to California, and the proximity to Tesla’s AI training cluster Cortex 1 and 2, both located at Giga Texas and now totaling over 230,000 H100 equivalent GPUs, means the Optimus software stack and the factory producing the hardware will share the same campus. Tesla’s Q1 report also confirmed completion of the AI5 chip tape out in April, the inference processor designed specifically to power Optimus units in the field.
As Teslarati reported, the Texas facility is intended to house Optimus V4 production at full scale. Musk told the World Economic Forum in January that Tesla plans to sell Optimus to the public by end of 2027 at a price between $20,000 and $30,000, stating, “I think everyone on earth is going to have one and want one.” He has previously pegged long term demand for general purpose humanoid robots at over 20 billion units globally, citing both consumer and industrial use cases.
Tesla (NASDAQ: TSLA) reported its earnings for the first quarter of 2026 on Wednesday afternoon. Here’s what the company reported compared to what Wall Street analysts expected.
The earnings results come after Tesla reported a miss on vehicle deliveries for the first quarter, delivering 358,023 vehicles and building 408,386 cars during the three-month span.
As Tesla transitions more toward AI and sees itself as less of a car company, expectations for deliveries will begin to become less of a central point in the consensus of how the quarter is perceived.
Nevertheless, Tesla is leaning on its strong foundation as a car company to carry forward its AI ambitions. The first quarter is a good ground layer for the rest of the year.
Tesla Q1 2026 Earnings Results
Tesla’s Earnings Results are as follows:
- Non-GAAP EPS – $0.41 Reported vs. $0.36 Expected
- Revenues – $22.387 billion vs. $22.35 billion Expected
- Free Cash Flow – $1.444 billion
- Profit – $4.72 billion
Tesla beat analyst expectations, so it will be interesting to see how the stock responds. IN the past, we’ve seen Tesla beat analyst expectations considerably, followed by a sharp drop in stock price.
On the same token, we’ve seen Tesla miss and the stock price go up the following trading session.
Tesla will hold its Q1 2026 Earnings Call in about 90 minutes at 5:30 p.m. on the East Coast. Remarks will be made by CEO Elon Musk and other executives, who will shed some light on the investor questions that we covered earlier this week.
You can stream it below. Additionally, we will be doing our Live Blog on X and Facebook.
Q1 2026 Earnings Call at 4:30pm CT https://t.co/pkYIaGJ32y
— Tesla (@Tesla) April 22, 2026
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SpaceX is following in Tesla’s footsteps in a way nobody expected
In the span of just months in early 2026, SpaceX has transformed itself into one of the world’s most ambitious AI companies. The catalyst: its February acquisition of xAI.
When Elon Musk founded Tesla in 2003, it was a plucky electric car startup betting everything on lithium-ion batteries and a niche luxury Roadster.
Two decades later, Tesla is far more than a car company. Its valuation increasingly hinges on Full Self-Driving software, the Optimus humanoid robot, the Robotaxi program, and the Dojo supercomputer cluster purpose-built for AI training.
Musk has repeatedly described Tesla as an AI and robotics company that happens to sell vehicles. The cars, in this view, are merely the first scalable platform for real-world AI.
Now, SpaceX is tracing an eerily similar path, only faster and in a direction almost no one anticipated. Founded in 2002 to make spaceflight routine and eventually multiplanetary, SpaceX spent its first two decades perfecting reusable rockets, landing Falcon 9 boosters, and building the Starlink megaconstellation.
Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry
It was an engineering and manufacturing powerhouse, not a software play. Yet, in the span of just months in early 2026, SpaceX has transformed itself into one of the world’s most ambitious AI companies. The catalyst: its February acquisition of xAI.
The xAI deal, announced on February 2, was structured as an all-stock transaction that valued the combined entity at roughly $1.25 trillion—SpaceX at $1 trillion and xAI at $250 billion. In a memo to employees, Musk framed the merger as the creation of “the most ambitious, vertically-integrated innovation engine on (and off) Earth.”
The new SpaceX now owns Grok, the large language model family that powers the chatbot of the same name, along with xAI’s massive training infrastructure. More importantly, it has a declared mission to move AI compute off-planet.
Earth-based data centers are hitting hard limits on power, cooling, and land. Musk’s solution is orbital data centers, or constellations of solar-powered satellites that act as supercomputers in the sky.
SpaceX has already asked regulators for permission to launch up to one million such satellites. Starship, the company’s fully reusable heavy-lift vehicle, is the only rocket capable of delivering the necessary mass at the required cadence.
Each orbital node would enjoy near-constant sunlight, vast radiator surfaces for passive cooling, and zero terrestrial real-estate costs. Musk has predicted that within two to three years, space-based AI inference and training could become cheaper than anything possible on the ground.
This is not a side project; it is the strategic centerpiece Musk has envisioned for SpaceX. Starlink already provides the global low-latency backbone; next-generation V3 satellites will carry onboard AI accelerators. Rockets deliver the hardware, while AI optimizes every aspect of launch, landing, and constellation management.
The feedback loop is self-reinforcing, too. Better AI makes better rockets, which launch more AI infrastructure.
Just yesterday, on April 21, SpaceX doubled down.
It secured an option to acquire Cursor—the fast-growing AI coding tool beloved by software engineers—for $60 billion later this year, or pay a $10 billion partnership fee if the full deal does not close.
Cursor’s models already help engineers write code at superhuman speed. Pairing that technology with SpaceX’s Colossus-scale training clusters (the same ones powering Grok) positions the company to dominate AI developer tools, much as Tesla dominates autonomous driving software.
Why SpaceX just made a $60 billion bet on AI coding ahead of historic IPO
The parallels with Tesla are striking. Both companies began in a single, capital-intensive sector: Tesla with EVs, SpaceX with launch vehicles. Both used early hardware success to fund AI at scale. Tesla’s Dojo supercomputers train neural nets on billions of miles of real-world driving data; SpaceX now trains on telemetry from thousands of orbital assets and re-entries.
Tesla’s FSD chip runs inference on cars; SpaceX’s future satellites will run inference in orbit.
Tesla’s Optimus robot will work in factories; SpaceX envisions lunar factories manufacturing more AI satellites, eventually using electromagnetic mass drivers to fling them into deep space.
Critics once dismissed Musk’s multi-company empire as unfocused. The 2026 moves reveal the opposite: deliberate convergence.
SpaceX is no longer merely a rocket company that sells internet from space. It is an AI company whose competitive moat is literal orbital infrastructure and the only vehicle that can service it at scale. The forthcoming IPO, expected later this year, will almost certainly be pitched not as a space play but as the purest bet on AI infrastructure the public market has ever seen.
Whether the orbital data-center vision survives regulatory scrutiny, astronomical concerns about light pollution, or the sheer engineering challenge remains to be seen.
Yet the strategic direction is unmistakable. Just as Tesla proved that software and AI could redefine the century-old automobile, SpaceX is proving that rockets are merely the delivery mechanism for the next great computing platform—one that floats above the clouds, powered by the sun, and limited only by the physics of orbit.
In that unexpected sense, history is repeating. Tesla stopped being “just a car company” years ago. SpaceX has now stopped being “just a rocket company.” Both are becoming something far larger: AI powerhouses with hardware moats so deep that competitors will need their own reusable megaconstellations to keep up.
The age of terrestrial AI is ending. The age of space-based AI is beginning—and SpaceX is building the launchpad.
Tesla isn’t joking about building Optimus at an industrial scale: Here we go
Tesla (TSLA) Q1 2026 earnings results: beat on EPS and revenues
