Tesla has added an easter egg on the Cybertruck that lets you smash the vehicle's windows
wmorrill3/X
A new Tesla easter egg was recently discovered over the holiday weekend. The easter egg appears to be exclusive to the Cybertruck and goes back to the now famous window-shattering event during the Cybertruck's reveal in 2019.
During the unveiling, Tesla's chief designer threw a steel ball at the Cybertruck's window to show off the truck's strong armored glass. To everyone's surprise, the ball shattered the glass and Elon Musk exclaimed, "Oh my f****** God."
Von Holzhausen then suggested trying the rear window, which Tesla apparently tried multiple times before the event, but the rear window also shattered upon meeting the large steel bearing. This time, Musk replied, "it didn't go through."
Musk cleverly makes a joke out of the situation, saying there's “room for improvement,” and continues the presentation in front of the now-smashed Cybertruck.
The window shattering has become part of Tesla culture and now Tesla has built it into the Cybertruck as an easter egg.
Window Smashing Easter Egg
Tesla has immortalized this event by building it into the Cybertruck as an easter egg. The easter egg was accidentally discovered by DennisCW on X who was tapping around on the Cybertruck's display.
While parked, the vehicle's visualization is displayed front and center on the display, a feature that's expected to come to all vehicles in an upcoming software v12 release. If you tap multiple times on the truck's front or rear (driver's side) windows the window will shatter and an audio clip will be played.
After shattering the front window, an audio clip will play Musk saying OMFG, and the audio snippet for the rear window will be of Musk saying, "at least it didn't go through."
OMFG one of many small delights maximizing the area under the happiness curve pic.twitter.com/pkDo8cBRKR
The windows will automatically fix themselves after not interacting with the display for several seconds, at which point you can tap on them again if desired.
Tesla has mostly gone away from incorporating true easter eggs into their vehicles, instead adding them to the ToyBox for more people to be able to find and enjoy them, but this appears to be an exception, adding homage to the now famous event.
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With Tesla’s first major expansion of the Robotaxi Geofence now complete and operational, they’ve been hard at work with validation in new locations - and some are quite the drive from the current Austin Geofence.
Validation fleet vehicles have been spotted operating in a wider perimeter around the city, from rural roads in the west end to the more complex area closer to the airport. Tesla mentioned during their earnings call that the Robotaxi has already completed 7,000 miles in Austin, and it will expand its area of operation to roughly 10 times what it is now. This lines up with the validation vehicles we’ve been tracking around Austin.
Based on the spread of the new sightings, the potential next geofence could cover a staggering 450 square miles - a tenfold increase from the current service area of roughly 42 square miles. You can check this out in our map below with the sightings we’re tracking.
If Tesla decides to expand into these new areas, it would represent a tenfold increase over their current geofence, matching Tesla’s statement. The new area would cover approximately 10% of the 4,500-square-mile Austin metropolitan area. If Tesla can offer Robotaxi services in that entire area, it would prove they can tackle just about any city in the United States.
From Urban Core to Rural Roads
The locations of the validation vehicles show a clear intent to move beyond the initial urban and suburban core and prepare the Robotaxi service for a much wider range of uses.
In the west, validation fleet vehicles have been spotted as far as Marble Falls - a much more rural environment that features different road types, higher speed limits, and potentially different challenges.
In the south, Tesla has been expanding towards Kyle, which is part of the growing Austin-San Antonio suburban corridor spanning Highway 35. San Antonio is only 80 miles (roughly a 90-minute drive) away, and could easily become part of the existing Robotaxi area if Tesla obtains regulatory approval there.
In the East, we haven’t spotted any new validation vehicles. This is likely because Tesla’s validation vehicles originate from Giga Texas, which is located East of Austin. We won’t really know if Tesla is expanding in this direction until they start pushing past Giga Texas and toward Houston.
Finally, there have been some validation vehicles spotted just North of the new expanded boundaries, meaning that Tesla isn’t done in that direction either. This direction consists of the largest suburban areas of Austin, which have so far not been serviced by any form of autonomous vehicle.
Rapid Scaling
This new, widespread validation effort confirms what we already know. Tesla is pushing for an intensive period of public data gathering and system testing in a new area, right before conducting geofence expansions. The sheer scale of this new validation zone tells us that Tesla isn’t taking this slowly - the next step is going to be a great leap instead, and they essentially confirmed this during this Q&A session on the recent call. The goal is clearly to bring the entire Austin Metropolitan area into the Robotaxi Network.
While the previous expansion showed off just how Tesla can scale the network, this new phase of validation testing is a demonstration of just how fast they can validate and expand their network. The move to validate across rural, suburban, and urban areas simultaneously shows their confidence in these new Robotaxi FSD builds.
Eventually, all these improvements from Robotaxi will make their way to customer FSD builds sometime in Q3 2025, so there is a lot to look forward to.
For years, the progress of Tesla’s FSD has been measured by smoother turns, better lane centering, and more confident unprotected left turns. But as the system matures, a new, more subtle form of intelligence is emerging - one that shifts its attention to the human nuances of navigating roads. A new video posted to X shows the most recent FSD build, V13.2.9, demonstrating this in a remarkable real-world scenario.
Toll Booth Magic
In the video, a Model Y running FSD pulls up to a toll booth and smoothly comes to a stop, allowing the driver to handle payment. The car waits patiently as the driver interacts with the attendant. Then, at the precise moment the toll booth operator finishes the transaction and says “Have a great day”, the vehicle starts moving, proceeding through the booth - all without any input from the driver.
If you notice, there’s no gate here at this toll booth. This interaction all happened naturally with FSD.
While the timing was perfect, the FSD wasn’t listening to the conversation for clues (maybe one day, with Grok?) The reality, as explained by Ashok Elluswamy, Tesla’s VP of AI, is even more impressive.
It can see the transaction happening using the repeater & pillar cameras. Hence FSD proceeds on its own when the transaction is complete 😎
FSD is simply using the cameras on the side of the vehicle to watch the exchange between the driver and attendant. The neural network has been trained on enough data that it can visually recognize the conclusion of a transaction - the exchange of money or a card and the hands pulling away - and understands that this is the trigger to proceed.
The Bigger Picture
This capability is far more significant than just a simple party trick. FSD is gaining the ability to perceive and navigate a world built for humans in the most human-like fashion possible.
If FSD can learn what a completed toll transaction looks like, it’s an example of the countless other complex scenarios it’ll be able to handle in the future. This same visual understanding could be applied to navigating a fast-food drive-thru, interacting with a parking garage attendant, passing through a security checkpoint, or boarding a ferry or vehicle train — all things we thought that would come much later.
These human-focused interactions will eventually become even more useful, as FSD becomes ever more confident in responding to humans on the road, like when a police officer tells a vehicle to go a certain direction, or a construction worker flags you through a site. These are real-world events that happen every day, and it isn’t surprising to see FSD picking up on the subtleties and nuances of human interaction.
This isn’t a pre-programmed feature for a specific toll booth. It is an emergent capability of the end-to-end AI neural nets. By learning from millions of videos across billions of miles, FSD is beginning to build a true contextual understanding of the world. The best part - with a 10x context increase on its way, this understanding will grow rapidly and become far more powerful.
These small, subtle moments of intelligence are the necessary steps to a truly robust autonomous system that can handle the messy, unpredictable nature of human society.
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