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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.
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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
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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
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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
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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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Elon Musk
SpaceX’s next trillion dollar bet has nothing to do with rockets, Musk tells staff
Elon Musk told SpaceX staff AI revenue will soon dwarf rockets and Starlink combined entirely.
Elon Musk told SpaceX employees this week that artificial intelligence, not rockets, will soon carry the company’s revenue. In a roughly 29 minute internal address posted on SpaceX’s X account on Tuesday, Musk said AI revenue will pass every other line of business at SpaceX “probably in September” and pull further ahead by the fourth quarter.
The numbers he gave are specific. SpaceX currently runs 1.4 gigawatts of AI compute capacity. Musk wants that at 10 gigawatts by the end of 2027, a jump he tied directly to revenue: “if we bring 10GW of AI online by the end of next year, it will be $300 billion to $500 billion a year in revenue.” He called those “big numbers,” which undersells a projection larger than what most countries produce in a year.
We made rockets reusable and are rebuilding the internet in space. The next challenge: making life multiplanetary and understanding the true nature of the universe
Watch @ElonMusk deliver a company update to @SpaceX employees pic.twitter.com/5c8rxoCQfu
— SpaceX (@SpaceX) August 11, 2026
Musk went further on where AI fits into SpaceX’s future. “Probably in four or five years, AI will be 99% of the value of SpaceX,” he told staff, adding that digital intelligence would eventually run “a trillion times” ahead of biological intelligence as computing scales. He tied that growth to the company’s founding mission, telling employees “we must win on AI, because the future is overwhelmingly AI and robots,” with the payoff meant to help fund Starship and a Mars program that increasingly runs through Terafab, the joint Tesla, SpaceX and xAI chip plant.
Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry
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None of this is entirely new territory. SpaceX told investors much the same story during its first earnings call as a public company on August 4, where Musk moved the company’s $1 trillion revenue target up a year to 2030 and said Starlink could someday carry a majority of the world’s internet. What the all hands video adds is a hard deadline and a specific power figure Musk had not given publicly before, along with a franker pitch to his own workforce that AI, not launch cadence, is now the thing SpaceX is betting its future on.
The AI revenue itself is not coming from SpaceX training its own models. It is largely Starlink acting as the network layer for xAI’s workloads, plus SpaceX renting out compute capacity directly, the same approach behind the roughly $16 billion the company spent on AI infrastructure in a single quarter.
Musk closed the video with a pitch aimed at recruiting and retention rather than investors, telling employees that anyone who helps SpaceX win the AI race will eventually get the chance to go to the moon or Mars themselves. Whether SpaceX can turn 1.4 gigawatts into 10 in seventeen months is the more immediate question, and one that will show up in quarterly numbers well before anyone leaves Earth.
In a new note to investors on Tuesday, Morgan Stanley analyst Andrew Percoco said that Tesla has one big financial question to answer for investors regarding its Robotaxi rollout, Full Self-Driving software, and Optimus.
Percoco said in the note that, for the most part, investors are still very positive about the direction the company is headed. However, there are some things the firm would like to see, and they have to do with financials.
Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue
Tesla bulls are more than convinced that the company’s Full Self-Driving software is proof it can develop physical AI. Financially, however, there are still some questions, especially on elevated spending, which CEO Elon Musk said would occur as the company works to roll out Robotaxi faster and continue developing its Optimus robot.
The latter two are where Tesla will have to prove progress to investors, as Percoco writes that both projects “will require clearer evidence that Robotaxi is scaling and more tangible Optimus proof points to support the ROI on elevated capex.”
Percoco said the second quarter earnings call did not change his long-term thesis of where Tesla is positioned in the AI race, which is out in front. However, there are concerns that weaker gross margins and higher R&D spend will stress financials, and that has “sharpened our (and investors’) focus on measurable progress across Robotaxi and Optimus.”
Additionally, Robotaxi still needs to be proven with more operation in existing cities while maintaining safety but improving how many rides it gives in any given time, he said. For Optimus, Percoco wrote that he is “still looking for evidence beyond commentary around SOP.”
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Morgan Stanley put Percoco in charge of covering Tesla after long-time analyst Adam Jonas transitioned to the automotive side.
Currently, Morgan Stanley has a $415 price target on Tesla and a ‘Hold’ rating on the stock. It is trading at around $330 at the time of publication, which was 2:30 P.M. on the East Coast.
SpaceX’s massive investment in AI will make it a big winner, Argus Research said after the company’s successful earnings call last week.
The firm also upgraded shares to a Buy from Hold and set a $160 price target.
SpaceX (NASDAQ: SPCX) is currently recovering from its heavy AI infrastructure investments, as it spent nearly $16 billion in Q2 alone. The company did this primarily by monetizing high-demand GPU compute capacity at a much faster pace than traditional data center economics would suggest.
Company CFO Bret Johnsen said that SpaceX would be able to pay back anything on new deployments within a year.
There are plenty of ways the company can do this:
Leasing excess compute capacity through contracts
SpaceX has already built Colossus and Colossus II, largely for its own model training. However, much of that capacity is already rented out to third parties. It already has major deals with Anthropic, Google, and Reflection AI. These partnerships are adding billions per month to SpaceX’s spreadsheet.
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High utilization driven by industry-wide scarcity
The demand for advanced AI training and inference capacity continues to exceed what is available for use. SpaceX can fill new racks quickly after they come online, so the capital deployed converts into revenue with minimal idle time.
Additionally, management and outside observers have described the new compute capital as behaving more like a cost-of-goods-sold than traditional multi-year capex, especially because of this rapid monetization pattern.
Capacity has already scaled from ~0.4 GW a year to 1.4 GW annually by the end of Q2. There are targets of more than 2 GW by year-end.
High incremental margins on the rental business once capacity is online
GPU cloud providers often operate at strong gross margins. SpaceX can monetize capacity that was already partially built or can be added efficiently. This means that incremental EBITDA margins on the rental revenue are usually high. This accelerates cash recovery relative to the gross capital outlay.
Parallel monetization of its own AI software and applications
Beyond pure infrastructure rental, SpaceX also generates revenue from Grok through subscriptions and usage, from X through ads, data, and other related services, enterprise APIs, and the planned integration of the Cursor coding tools acquisition.
These application layers ride on the same compute infrastructure and provide additional high-margin streams that could offset build-out costs. AI-segment revenue overall rose sharply to about $2.6 billion in Q2, according to Motley Fool. This was driven primarily by the infrastructure contracts, but the software side is also partially responsible.
Efficient, large-scale deployment and vertical integration advantages
SpaceX has emphasized the rapid construction of power and cooling infrastructure and favorable cost-per-megawatt economics relative to industry benchmarks in some disclosures.
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Combined with its ability to scale capacity aggressively and the fact that many contracts start generating revenue within months of capacity coming online, the effective payback compresses dramatically compared with more conventional multi-year data-center projects.
SpaceX’s dominant near-term recovery path will turn the AI clusters into a hyperscale-style compute rental business for other leading AI companies while still using a portion for internal models.
SpaceX’s next trillion dollar bet has nothing to do with rockets, Musk tells staff
Tesla has one big financial question to answer for investors: Morgan Stanley
