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Tesla Cybertruck lead engineer shares insights on deep integration and vehicle development

Credit: @wmorrill3/X

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Tesla Cybertruck Lead Engineer Wes Morrill recently shared some insights on the electric vehicle maker’s deep integration and unique approach to car design in a recent post on social media platform X. As could be seen in the engineer’s post, it is Tesla’s intense attention to detail that ultimately makes the company’s vehicles as disruptive as they are today. 

Anyone informed who looks at the Tesla Cybertruck would know that the vehicle is a symphony of automotive engineering. Tesla, however, took some time before it reached this point. As per Morrill in his post, Tesla in its early days utilized different teams with collaborative goals in vehicle design. Adopting this system allowed the company to make great cars, but the designs of the vehicles themselves were not optimal. 

“A well known example – early days of Tesla there was a battery team and separately a vehicle structures team. Structures team designed their vehicle body to meet given requirements of strength, crashworthiness, torsional stiffness, etc. Likewise, the battery team designed their part to be self contained, it could survive durability, accidentally being dropped, being hit in a crash, etc.

“As a result, we ended up with was a super dense battery in a strong box like structure, which was then Installed into the vehicle which had a nice space for it to mate into. There were no issues with integration, everything fit together perfectly and met all product goals. It achieved one of the highest crash safety ratings measured at the time.

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“But we had a box full of battery cells that was installed into another empty box shaped receptacle on the body. A box in a box. When you simplify it down that far it sounds obviously wrong. The two organizations had achieved their goals, worked together without friction, and the product met its overall goals. Yet the product ended up with a clear lack of optimization as a result of the organizational boundaries of the two teams working in isolation. Nothing was wrong, but it wasn’t optimal,” Morrill wrote. 

The Cybertruck Lead Engineer noted that Tesla learned from these experiences, and the company adapted. This is how innovations such as the structural battery pack—which is now being simulated by electric car makers in China—came about. Morrill stated, however, that such changes may require large organizational changes, and there has to be a drive to make the best product regardless of ego. 

“Before the next product was designed, the battery team gave responsibility of the battery structures also to the vehicle structures team. On this iteration, we ended up with the structural battery, which is an integral part of the body and crash structure. Without it, the vehicle body will not work. It’s the literal floor for the vehicle. But the redundancy is gone and the design is more efficient as a result. This vehicle also achieved one of the highest crash safety ratings measured at the time.

“This is a super obvious example (in retrospect) and solved with a fairly large organizational change but you can also see this happen in small technical decisions and doesn’t require structural change to fix. Someone just needs to question if there is a better solution in a team open to criticism. This mindset to work together to make the best product regardless of ego is where you end up with the most innovative products.

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“Some smaller examples have been seen when inspecting Cybertruck design. The chassis air suspension which is used to pressurize the battery pack to prevent water ingress. The subwoofer which utilizes the air volume of the body side instead of making the enclosure larger. Centralized zonal vehicle controllers instead of many small distributed controllers. Doors which use the exterior surface as a crash intrusion beam. The pedestrian warning system used as a horn. The list goes on. The excitement and motivation by everyone involved to work across boundaries and actively break down Conway’s Law is one of the many reasons I love working at Tesla,” Morrill wrote. 

Don’t hesitate to contact us with news tips. Just send a message to simon@teslarati.com to give us a heads up.

Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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SpaceXAI just launched into your kitchen with their new app

SpaceXAI just powered its first consumer app and it predicts what you want to buy.

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SpaceXAI just made its first move into consumer AI, and it involves your grocery cart. On June 3, 2026, Gopuff and SpaceXAI announced the launch of Go, a Grok-powered shopping assistant built directly into the Gopuff app that predicts what you need before you even start searching for it.

Gopuff is an instant delivery platform that operates more than 400 micro-fulfillment centers across the U.S., delivering everyday essentials, snacks, drinks, and household items in as little as 15 minutes. It is not a restaurant delivery app or a marketplace. It owns its inventory, controls its warehouses, and handles its own logistics, which means it has built one of the most detailed consumer behavior datasets in retail over its 13-year history.

Go combines SpaceXAI’s advanced reasoning, voice, and image generation models with Gopuff’s dataset of hundreds of millions of orders and real-time cultural signals from X to prepare a suggested cart the moment a customer opens the app. It learns each shopper’s habits and automatically builds a personalized cart based on time of day, location, order history, and real-time indicators. Returning customers can check out with a single tap.


Rather than searching for specific items, users can describe a situation like a game-day party or the desire for a healthy breakfast and Go will assemble a cart automatically. It can also predict when shoppers are running low on items like coffee or paper towels and have them packed and delivered in under 15 minutes. Grok voice integration lets users talk to the app in plain conversational language and check out completely hands-free.

Gopuff co-founder and co-CEO Yakir Gola said: “Today, we believe the greatest friction left in commerce is not delivery or instantaneous access to the essentials customers need. It’s the moment before: the thinking, the deciding, the remembering. We’re combining Gopuff’s demand intelligence with xAI’s frontier reasoning to create an everyday shopping experience that feels like a true extension of you.”

Why SpaceX just made a $60 billion bet on AI coding ahead of historic IPO

The timing carries context beyond the product launch. SpaceXAI was formed after SpaceX completed an all-stock merger with Elon Musk’s xAI earlier this year, folding one of the most advanced AI labs in the world into the same corporate structure as the company preparing what could be the largest IPO in history. SpaceXAI is dipping into consumer-focused AI just as it prepares for its public debut, and while Musk has openly discussed building an everything app, this launch uses Grok to power another company’s product rather than launching a standalone consumer platform. Every consumer-facing deployment of Grok ahead of the IPO roadshow adds tangible evidence that SpaceXAI is not just an infrastructure play but a direct competitor in the AI application layer where OpenAI and Google are already fighting for dominance.

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Tesla piggybacks recent Supercharger feature with update that takes it further

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Credit: Tesla

Tesla has introduced an enhanced visualization in its Supercharger navigation system, building directly on the Site Maps feature rolled out a few months ago.

This latest software update adds detailed 3D icons that represent specific vehicle models parked at charging stalls, offering drivers a more precise view of site occupancy and layout.

The Site Maps debuted in Tesla’s 2025 Holiday Update, providing 3D overviews of select Supercharger locations with real-time stall availability.

Tesla supplements Holiday Update by sneaking in new Full Self-Driving version

Drivers could see which spots were open, occupied, or out of service when navigating to supported stations.

Now, the system takes this capability further by rendering accurate representations of Tesla vehicles, including distinctions between models such as the Model 3, Model Y, Model S, Model X, and Cybertruck. These icons appear as lifelike 3D renderings, complete with recognizable shapes and proportions that match the actual cars charging at the site:

This refinement improves the user experience during road trips and daily charging stops. As drivers approach a Supercharger, the navigation display now shows not just generic occupied markers but identifiable vehicle types plugged into each stall.

Blue indicators highlight active charging sessions, while other visual cues denote availability or maintenance status. The feature integrates seamlessly with the existing map interface, allowing quick assessment of the best available spot based on vehicle size and positioning.

Tesla continues to expand the availability of these detailed Site Maps across its global network. Initially piloted at a limited number of locations, the rollout has progressed steadily, with more stations gaining support in recent software versions.

Owners benefit from better planning, as the system helps identify compatible stalls and reduces uncertainty upon arrival. The update reflects Tesla’s ongoing commitment to refining its navigation and charging ecosystem through iterative software improvements.

In addition to model-specific icons, the enhanced maps maintain all prior functionalities, such as integration with nearby amenities and energy usage predictions. This ensures a comprehensive tool for efficient Supercharging.

As Tesla’s fleet grows and the network scales, such features play a key role in optimizing the overall ownership experience. Future updates may extend similar visualizations to additional sites and incorporate even more data points for drivers.

With this piggyback enhancement, Tesla demonstrates how small but thoughtful additions can elevate an already useful tool, making Supercharger visits smoother and more informed for its customers. The company is expected to broaden the feature’s reach in upcoming releases, further solidifying its leadership in EV charging infrastructure.

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Tesla Full Self-Driving v14.3.3 driver monitoring: We tested it

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Credit: TESLARATI

Tesla Full Self-Driving v14.3.3 driver monitoring was reportedly scaled back in recent releases, but a new version that was released in the early hours of June 3 aimed to do a better job of keeping those in control of their cars honest, according to release notes.

The release notes for FSD v14.3.3, via Software Version 2026.14.6.7 added:

“Improved driver monitoring system sensitivity with better eye gaze tracking, eye wear handling, and higher accuracy in variable lighting conditions.”
However, Tesla said this was already enabled in the first rollout of FSD v14.3.3 in late May. We tested it anyway, especially as the Standard Speed Profile seemed less-than-worried about what you were doing during operation.

I decided to try out the Hurry and Mad Max Speed Profiles for this test, and it gave me results that I would have expected. Tesla has evidently ramped up driver monitoring based on the Speed Profile you are using to travel.

The more aggressive the Speed Profile, the more on the hook you will be for taking your attention away from the road. Our testing showed that Mad Max was less likely to allow you to do normal things like change music or adjust navigation without getting an on-screen warning or nag from the driver monitoring system.

Hurry Mode Results

On Hurry, the driver monitoring system on FSD v14.3.3, via Software Version 2026.14.6.7, was more restrictive than Standard but less restrictive than Mad Max. I found that I could scroll through music options for a considerable amount of time, more than 30 seconds:

Standard gave me about 80 seconds of phone scrolling with absolutely no nags or warnings in a previous test. It is worth noting that this was a previous branch of v14.3.3, but Standard is such a goodie-two-shoes on the road that it is my impression it would not change much.

Mad Max Results

I spent the majority of the drive on Mad Max to see how it truly reacted to the driver having their attention elsewhere. While I did do a short phone test, I am aiming to steer away from those and use the center screen. I think it is a valid criticism that the phone test is dangerous and, not to mention, illegal in Pennsylvania. Changing the navigation and music is a more reasonable, more responsible, and safer test.

With Mad Max being the fastest and most aggressive Speed Profile, I anticipated this being the quickest mode to give me an alert that I needed to look at the road. That was the case with music:

As well as adjusting Navigation, when I received two nags:

These nags were more than reasonable, and I think it’s probably good that Tesla is ramping up the driver monitoring. I do believe that it should be relatively strict across all of the Speed Profiles, especially with phone use. When using the center screen, the nag intervals should be based on the speed profile you are utilizing at the time.

These driver monitoring adjustments are a great thing to have while FSD is still under its “Supervised” moniker, but I expect Tesla to continue pushing the limits on what it will allow, especially considering CEO Elon Musk has hinted that phone use is capable with the more recent versions.

You can watch the full drive on YouTube below:

 

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