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I tried Tesla’s FSD Supervised on a demo drive—Here’s what I learned
Tesla’s Supervised Full Self-Driving (FSD) has been at the center of the company’s long-term strategy for years, and seeing as I’ve been covering the company and its competitors since 2020, I decided it was finally time to try it out myself.
The process of scheduling a demo drive was simple: I scheduled it online through Tesla’s test drive page, and because I was hoping to focus on FSD, I shot an email over to the Loveland team letting them know that I was coming and was planning to try the software out. I got a quick response, in which one of the advisors offered to schedule me for an extended demo drive, effectively giving me a three-hour window to try out FSD Supervised.
On Monday, I headed out from my house in Fort Collins, Colorado, to the next town over, Loveland, to try Tesla’s latest FSD Supervised version available. While I initially scheduled a demo drive for a Model Y with FSD Supervised v13.2.2, one of the Tesla advisors informed me that there was also a Model S on-site with version v13.2.2.1, so I elected to test that one instead.
After getting a quick rundown from the advisor on the Model S, my demo drive officially began. I typed my first destination into the navigation system, pressed and held the blue “Start FSD (Supervised)” button, and off I went.
Tesla’s FSD Supervised: autonomy is definitely on the way
Perhaps many people have this experience when trying FSD out for the first time, but right off the bat, I found myself laughing at how it worked and a little scared that it would make a mistake. This Model S was now driving me out of the Loveland Tesla parking lot to a nearby Target, through busy parking lots, turns and lane changes, and it was pretty uncomfortable at first not to be the one making the maneuvers—let alone the fact that no person was making these maneuvers, but rather it was the vehicle doing it on its own.
I felt like an anxious passenger—my feet pressed firmly on the floor in distrust and disbelief—only I was sitting in the driver’s seat. I really couldn’t do much but laugh at how strange the experience had felt so far.
Then, not long after my first trip, something interesting happened.
My mindset slowly shifted from fear to trust with each correct maneuver, and I managed my first few drives without disengaging at all, offering a true testament to how well FSD Supervised performed on this test. Granted, I went in without too much of a plan and wasn’t targeting fringe cases or particularly tough maneuvers; I just wanted to see if this car could drive me around for a few hours, and to feel what it was like to demo FSD Supervised as a newcomer.
It’s worth noting that I did most of my driving in FSD’s Chill mode, though I also tested a few drives in both Standard and Hurry. Personally, I think I would probably keep it in Chill mode most of the time, as it’s the most similar to how I drive of the three.
Below are a few moments from the drive that show some of the system’s capabilities, even turning onto busy roads that would be difficult for a human driver.
Tesla’s FSD Supervised reverses out of a parking spot… and we’re off
A simple reverse out of a parking spot, a good start! pic.twitter.com/TIx2yDmSxT
— TESLARATI (@Teslarati) January 15, 2025
Tesla’s FSD Supervised takes a few left turns onto busy roads
Another busy left turn – “FSD handled this busy turn with ease.” pic.twitter.com/SncR0Kh7ar
— TESLARATI (@Teslarati) January 15, 2025
Another left turn during a somewhat busy time of day – “I was a little scared, not going to lie, but FSD handled it well.” pic.twitter.com/WNunR05C3h
— TESLARATI (@Teslarati) January 15, 2025
Tesla’s FSD Supervised tackles a two-lane roundabout and parking lot
Roundabout? No problem! – “A two-lane roundabout that FSD handled pretty comfortably.” pic.twitter.com/X9QJIVXb6z
— TESLARATI (@Teslarati) January 15, 2025
Left-hand turn out of a parking lot – “It was pretty busy in there but it was well handled, the car navigated easily through the intersection just as I would have.” pic.twitter.com/Kzxb0aYtFN
— TESLARATI (@Teslarati) January 15, 2025
READ MORE ON TESLA’S FSD SUPERVISED: Tesla Cybertruck receives FSD (Supervised) v13.2.4 update
The temptation not to pay attention, and my most critical disengagement
Elon Musk and others have talked up FSD Supervised v13 since its release, as well as claiming that unsupervised driving is just around the corner. While it does feel closer than ever after years of reporting on small tweaks, improvements and developments, I think it’s also worth emphasizing again that the system still requires the driver to pay attention, even though it’s tempting to believe that it can handle all the driving by itself.
As I drove more and more, or rather as the car drove me, I became more comfortable trusting that FSD Supervised was going to make the right decisions, which it did about 99 percent of the time. I was lulled into somewhat of a false sense of safety that almost had me believing the vehicle didn’t need to be supervised, but that 1 percent of the time (maybe even less) that it did get confused still required my input.
I only had a few interventions for the whole experience, but one in particular had me a little scared after having become a little complacent and too trusting. As you can see in the video below, FSD Supervised was looking to merge into the right lane, when two vehicles slowed down. The Model S attempted to change lanes anyway, requiring me to overtake the wheel and keep driving straight.
Our first bit of adversity – “This was the most dangerous intervention I faced (I only had about three the whole time). FSD was trying to merge right, but the vehicles in that lane slowed down, and the car didn’t seem to understand what was going on. It started merging into the… pic.twitter.com/hJUBnCAjd2
— TESLARATI (@Teslarati) January 15, 2025
Besides the quick moment of fear in deciding I needed to take the wheel, it really was not a big deal once I regained control. It was actually a good wake-up call: this system still needs to be supervised, even if it makes fewer and fewer mistakes with each new version and feels like a solid human driver for the vast majority of the time.
I had a few other disengagements on my drive, mostly when the vehicle seemed to get confused about uncommon traffic circumstances or in confusing parking lot scenarios without clear signage. However, these moments made up a very small portion of my experience, and I can only imagine what another couple of years of development will do.
Tesla’s FSD Supervised: still needs supervision, but I got a good glimpse into a future of autonomy
All in all, I really enjoyed trying out FSD Supervised and I hope to do it again sometime. Additionally, I’d recommend trying it out to anyone, especially if you’re interested in seeing where driving tech is headed.
While I definitely got a glimpse into the future potential for fully autonomous driving, I also think it still requires supervision, even if just for those very seldom moments where the system gets confused. The margin for error with driving safety is obviously extremely low, though I do believe Tesla will eventually make good on its aim to make this system better than human drivers in time—and it already feels pretty close the majority of the time.
I hope to do this again sometime soon, and a major shout out to the Tesla Loveland team for making the experience smooth and for answering all my questions along the way.
What are your thoughts? Let me know at zach@teslarati.com, find me on X at @zacharyvisconti, or send us tips at tips@teslarati.com.
Tesla employees are performing autonomous FSD trials, CEO Elon Musk says
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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:
Supercharger update now shows type of Tesla at charger as well.
Pretty cool. pic.twitter.com/J3NRSIgM0m
— DennisCW | wen my L (@DennisCW_) June 2, 2026
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.
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:
Roughly :31 between first touching the center screen and getting the first nag
— TESLARATI (@Teslarati) June 3, 2026
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.
Here’s an 80-second phone nag test on Tesla FSD v14.3.3.
No alerts, no nagging, no annoyance. https://t.co/1dxvTOw5Cn pic.twitter.com/vYViFpjfoK
— TESLARATI (@Teslarati) May 29, 2026
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:
🎥 Testing Tesla FSD v14.3.3 (via 2026.14.6.7) nags on Mad Max https://t.co/qZALU2OujY pic.twitter.com/XddOJ0D47x
— TESLARATI (@Teslarati) June 3, 2026
As well as adjusting Navigation, when I received two nags:
🎥 Testing Tesla FSD v14.3.3 (via 2026.14.6.7) nag while adjusting navigation
Two nags here https://t.co/qZALU2OujY pic.twitter.com/xa3dtaDG1L
— TESLARATI (@Teslarati) June 3, 2026
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:
Tesla has responded to the skeptics of its Robotaxi program by launching a massive expansion of the unsupervised program in its initial rollout city of Austin.
The company’s geofence, the enabled area of operation for rides, now covers the entire Austin Metropolitan area, an incredible move just days after media headlines attempted to discredit the ride-hailing service.
Those who have access to the Tesla Robotaxi app on their smartphones can now request a ride in any portion of the Austin Metro area. The company confirmed this on the social media platform X:
Unsupervised Robotaxi now in the entire Austin Metro area https://t.co/eXNBdarvVS
— Tesla Robotaxi (@robotaxi) June 3, 2026
This is Tesla’s fifth expansion of the geofence, with the others occurring in July, early August, late August, and late October 2025. It has remained at that size since October 26, but Tesla has now more than doubled that size.
It is now covering the entire area, including suburbs like Pflugerville and Manor, as well as I-35 highways, Gigafactory Texas, and the Austin-Bergstrom Airport.
The move comes just days after various media outlets highlighted the small fleet size of Tesla’s Robotaxi fleet in Austin, something that is a reasonable criticism but an understandable move on the company’s part to prioritize safety.
Tesla has expanded its Robotaxi geofence many times, but its fleet has remained at a relatively conservative size as the company continues to push safety as its most crucial metric.
The latest expansion is a key indicator of Tesla’s comfort level to expand the ride-hailing service. The move shows Tesla is scaling unsupervised autonomy, as it demonstrates that the company’s Full Self-Driving system has reached sufficient reliability for a broader real-world deployment, which is something the company has worked on extensively.
It also shows Tesla is game for a competition with its rivals in the autonomous ride-hailing sector. Tesla has often matched or exceeded competitors like Waymo in coverage area, despite its smaller fleet. This step highlights Tesla’s iterative, data-driven progress toward a high-margin, app-based Robotaxi network.
It’s not the absolute largest area expansion ever, but achieving full unsupervised operations across a major metro is a key moment in the Robotaxi story. It shifts the program from limited pilot/testing toward a more mature commercial service, while gathering the miles needed for faster growth.
Tesla piggybacks recent Supercharger feature with update that takes it further
Tesla Full Self-Driving v14.3.3 driver monitoring: We tested it
