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SpaceX backup Starship reaches full height after nosecone installation
SpaceX has installed another Starship’s nosecone, all but completing the second full-size prototype a matter of days before the first fully-assembled Starship’s risky launch debut.
Over the last two months, SpaceX has effectively put Starship number 8 (SN8) through an almost nonstop series of tests, completing at least four separate cryogenic proof tests, four Raptor engine static fires, and much more. The company’s South Texas team have also dodged an array of technical bugs; installed, plumbed, and wired what amounts to ~40% of Starship (the nose section) while fully exposed to the coastal elements; and even narrowly avoided a potentially catastrophic failure.
In spite of the many hurdles thrown up and delays resultant, CEO Elon Musk announced earlier this week that Starship SN8 is scheduled to attempt its 15-kilometer (~50,000 ft) launch debut as early as Monday, November 30th. Musk, however, does not see success as the most probable outcome.
Why, then, push to launch Starship SN8 when, in Musk’s own words, the probability of success is as low as “33%”? As previously discussed many times in the history of Teslarati’s BFR and Starship coverage, SpaceX’s attitude towards technology development is (unfortunately) relatively unique in the aerospace industry. While once a backbone of major parts of NASA’s Apollo Program moonshot, modern aerospace companies simply do not take risks, instead choosing a systems engineering methodology and waterfall-style development approach, attempting to understand and design out every single problem to ensure success on the first try.
The result: extremely predictable, conservative solutions that take huge sums of money and time to field but yield excellent reliability and all but guarantee moderate success. SpaceX, on the other hand, borrows from early US and German rocket groups and, more recently, software companies to end up with a development approach that prioritizes efficiency, speed, and extensive testing, forever pushing the envelope and thus continually improving whatever is built.
In the early stages of any program, the results of that approach can look extremely unusual and rudimentary without context (i.e. Starhopper, above), but building and testing a minimum viable product or prototype is a very intentional foundation. Particularly at the start, those minimal prototypes are extremely cheap and almost singularly focused on narrowing a vast range of design options to something more palatable. As those prototypes rapidly teach their builders what the right and wrong questions and design decisions are, more focused and refined prototypes are simultaneously built and tested.
Done well, the agile approach is often quite similar to evolution, where prototype failures inform necessary design changes and killing off dead-end strategies, designs, and assumptions before they can be built upon. In many cases, compared to cautious waterfall-style development, it will even produce results that are both better, cheaper, and faster to realize. SpaceX’s Starship program is perhaps the most visible example in history, made all the more interesting and controversial by the fact that it’s still somewhere in between its early, chaotic development phase and a clear path to a viable product.
On the build side of things, SpaceX has created a truly incredible ad hoc factory from next to nothing, succeeding to the point that the company is now arguably testing and pushing the envelope too slowly. As of November 2020, no fewer than eight full-size Starships and the first Super Heavy booster prototype are visibly under construction. Most recently, Starship SN9 was stacked to its full height, kicking off nosecone installation while still at the build site (unlike SN8). SN10’s completed tank section is likely ready to begin flap installation within the next few days, while Starship SN11 is perhaps a week or two behind that. Additionally, large tank sections of Starships SN12, SN13, SN14, SN15, and (most likely) SN16 are already completed and have all been spotted in the last few weeks.
Some ~90% of the above work was likely started after Starship SN8 first left the factory and rolled to the launch pad on September 26th. In many regards, SN8 has been the first to reach multiple major milestones, largely explaining the relatively plodding pace of its test program compared to SN4, SN5, and SN6.
Ultimately, SN9’s imminent completion – effectively a superior, more refined copy of SN8 – means that Starship SN8’s utility to SpaceX is rapidly deteriorating. The company would almost assuredly never skip an opportunity to learn, meaning that there’s no plausible future in which SN8 testing doesn’t continue, but that doesn’t mean that SpaceX can’t turn its risk tolerance to 11. In essence, accept a 67% (or higher) chance of Starship SN8’s violent destruction but learn as much as possible in the process. As long as good data is gathered, SN8’s launch debut will be a success for Starship whether the rocket lands in one or several pieces.
News
SpaceX President Gwynne Shotwell details xAI power pledge at White House event
The commitment was announced during an event with United States President Donald Trump.
SpaceX President Gwynne Shotwell stated that xAI will develop 1.2 gigawatts of power at its Memphis-area AI supercomputer site as part of the White House’s new “Ratepayer Protection Pledge.”
The commitment was announced during an event with United States President Donald Trump.
During the White House event, Shotwell stated that xAI’s AI data center near Memphis would include a major energy installation designed to support the facility’s power needs.
“As you know, xAI builds huge supercomputers and data centers and we build them fast. Currently, we’re building one on the Tennessee-Mississippi state line. As part of today’s commitment, we will take extensive additional steps to continue to reduce the costs of electricity for our neighbors…
“xAI will therefore commit to develop 1.2 GW of power as our supercomputer’s primary power source. That will be for every additional data center as well. We will expand what is already the largest global Megapack power installation in the world,” Shotwell said.
She added that the system would provide significant backup power capacity.
“The installation will provide enough backup power to power the city of Memphis, and more than sufficient energy to power the town of Southaven, Mississippi where the data center resides. We will build new substations and invest in electrical infrastructure to provide stability to the area’s grid.”
Shotwell also noted that xAI will be supporting the area’s water supply as well.
“We haven’t talked about it yet, but this is actually quite important. We will build state-of-the-art water recycling plants that will protect approximately 4.7 billion gallons of water from the Memphis aquifer each year. And we will employ thousands of American workers from around the city of Memphis on both sides of the TN-MS border,” she noted.
The Ratepayer Protection Pledge was introduced as part of the federal government’s effort to address concerns about rising electricity costs tied to large AI data centers, as noted in an Insider report. Under the agreement, companies developing major AI infrastructure projects committed to covering their own power generation needs and avoiding additional costs for local ratepayers.
News
Tesla Full Self-Driving v14.2.2.5 might be the most confusing release ever
With each Full Self-Driving release, I am realistic. I know some things are going to get better, and I know some things will regress slightly. However, these instances of improvements are relatively mild, as are the regressions. Yet, this version has shown me that it contains extremes of both.
Tesla Full Self-Driving v14.2.2.5 hit my car back on Valentine’s Day, February 14, and since I’ve had it, it has become, in my opinion, the most confusing release I’ve ever had.
With each Full Self-Driving release, I am realistic. I know some things are going to get better, and I know some things will regress slightly. However, these instances of improvements are relatively mild, as are the regressions. Yet, this version has shown me that it contains extremes of both.
It has been about three weeks of driving on v14.2.2.5; I’ve used it for nearly every mile traveled since it hit my car. I’ve taken short trips of 10 minutes or less, I’ve taken medium trips of an hour or less, and I’ve taken longer trips that are over 100 miles per leg and are over two hours of driving time one way.
These are my thoughts on it thus far:
Speed Profiles Are a Mixed Bag
Speed Profiles are something Tesla seems to tinker with quite frequently, and each version tends to show a drastic difference in how each one behaves compared to the previous version.
I do a vast majority of my FSD travel using Standard and Hurry modes, although in bad weather, I will scale it back to Chill, and when it’s a congested city on a weekend or during rush hour, I’ll throw it into Mad Max so it takes what it needs.
Early on, Speed Profiles really felt great. This is one of those really subjective parts of the FSD where someone might think one mode travels too quickly, whereas another person might see the identical performance as too slow or just right.
To me, I would like to see more consistency from release to release on them, but overall, things are pretty good. There are no real complaints on my end, as I had with previous releases.
In a past release, Mad Max traveled under the speed limit quite frequently, and I only had that experience because Hurry was acting the same way. I’ve had no instances of that with v14.2.2.5.
Strange Turn Signal Behavior
This is the first Full Self-Driving version where I’ve had so many weird things happen with the turn signals.
Two things come to mind: Using a turn signal on a sharp turn, and ignoring the navigation while putting the wrong turn signal on. I’ve encountered both things on v14.2.2.5.
On my way to the Supercharger, I take a road that has one semi-sharp right-hand turn with a driveway entrance right at the beginning of the turn.
Only recently, with the introduction of v14.2.2.5, have I had FSD put on the right turn signal when going around this turn. It’s obviously a minor issue, but it still happens, and it’s not standard practice:
How can we get Full Self-Driving to stop these turn signals?
There’s no need to use one here; the straight path is a driveway, not a public road. The right turn signal here is unnecessary pic.twitter.com/7uLDHnqCfv
— TESLARATI (@Teslarati) February 28, 2026
When sharing this on X, I had Tesla fans (the ones who refuse to acknowledge that the company can make mistakes) tell me that it’s a “valid” behavior that would be taught to anyone who has been “professionally trained” to drive.
Apparently, if you complain about this turn signal, you are also claiming you know more than Tesla engineers…okay.
Nobody in their right mind has ever gone around a sharp turn when driving their car and put on a signal when continuing on the same road. You would put a left turn signal on to indicate you were turning into that driveway if that’s what your intention was.
Like I said, it’s a totally minor issue. However, it’s not really needed, and nor is it normal. If I were in the car with someone who was taking a simple turn on a road they were traveling, and they signaled because the turn was sharp, I’d be scratching my head.
I’ve also had three separate instances of the car completely ignoring the navigation and putting on a signal that is opposite to what the routing says. Really quite strange.
Parking Performance is Still Underwhelming
Parking has been a complaint of mine with FSD for a long time, so much so that it is pretty rare that I allow the vehicle to park itself. More often than not, it is because I want to pick a spot that is relatively isolated.
However, in the times I allow it to pull into a spot, it still does some pretty head-scratching things.
Recently, it tried to back into a spot that was ~60% covered in plowed snow. The snow was piled about six feet high in a Target parking lot.
A few days later, it tried backing into a spot where someone failed the universal litmus test of returning their shopping cart. Both choices were baffling and required me to manually move the car to a different portion of the lot.
I used Autopark on both occasions, and it did a great job of getting into the spot. I notice that the parking performance when I manually choose the spot is much better than when the car does the entire parking process, meaning choosing the spot and parking in it.
It’s Doing Things (For Me) It’s Never Done Before
Two things that FSD has never done before, at least for me, are slow down in School Zones and avoid deer. The first is something I usually take over manually, and the second I surprisingly have not had to deal with yet.
I had my Tesla slow down at a school zone yesterday for the first time, traveling at 20 MPH and not 15 MPH as the sign suggested, but at the speed of other cars in the School Zone. This was impressive and the first time I experienced it.
I would like to see this more consistently, and I think School Zones should be one of those areas where, no matter what, FSD will only travel the speed limit.
Last night, FSD v14.2.2.5 recognized a deer in a roadside field and slowed down for it:
🚨 Cruising home on a rainy, foggy evening and my Tesla on Full Self-Driving begins to slow down suddenly
FSD just wanted Mr. Deer to make it home to his deer family ❤️ pic.twitter.com/cAeqVDgXo5
— TESLARATI (@Teslarati) March 4, 2026
Navigation Still SUCKS
Navigation will be a complaint until Tesla proves it can fix it. For now, it’s just terrible.
It still has not figured out how to leave my neighborhood. I give it the opportunity to prove me wrong each time I leave my house, and it just can’t do it.
It always tries to go out of the primary entrance/exit of the neighborhood when the route needs to take me left, even though that exit is a right turn only. I always leave a voice prompt for Tesla about it.
It still picks incredibly baffling routes for simple navigation. It’s the one thing I still really want Tesla to fix.
Investor's Corner
Tesla gets tip of the hat from major Wall Street firm on self-driving prowess
“Tesla is at the forefront of autonomous driving, supported by a camera-only approach that is technically harder but much cheaper than the multi-sensor systems widely used in the industry. This strategy should allow Tesla to scale more profitably compared to Robotaxi competitors, helped by a growing data engine from its existing fleet,” BoA wrote.
Tesla received a tip of the hat from major Wall Street firm Bank of America on Wednesday, as it reinitiated coverage on Tesla shares with a bullish stance that comes with a ‘Buy’ rating and a $460 price target.
In a new note that marks a sharp reversal from its neutral position earlier in 2025, the bank declared Tesla’s Full Self-Driving (FSD) technology the “leading consumer autonomy solution.”
Analysts highlighted Tesla’s camera-only architecture, known as Tesla Vision, as a strategic masterstroke. While technically more challenging than the multi-sensor setups favored by rivals, the vision-based approach is dramatically cheaper to produce and maintain.
This cost edge, combined with Tesla’s rapidly expanding real-world data engine, positions the company to scale robotaxis far more profitably than competitors, BofA argues in the new note:
“Tesla is at the forefront of autonomous driving, supported by a camera-only approach that is technically harder but much cheaper than the multi-sensor systems widely used in the industry. This strategy should allow Tesla to scale more profitably compared to Robotaxi competitors, helped by a growing data engine from its existing fleet.”
The bank now attributes roughly 52% of Tesla’s total valuation to its Robotaxi ambitions. It also flagged meaningful upside from the Optimus humanoid robot program and the fast-growing energy storage business, suggesting the auto segment’s recent headwinds, including expired incentives, are being eclipsed by these higher-margin opportunities.
Tesla’s own data underscores exactly why Wall Street is waking up to FSD’s potential. According to Tesla’s official safety reporting page, the FSD Supervised fleet has now surpassed 8.4 billion cumulative miles driven.
Tesla FSD (Supervised) fleet passes 8.4 billion cumulative miles
That total ballooned from just 6 million miles in 2021 to 80 million in 2022, 670 million in 2023, 2.25 billion in 2024, and a staggering 4.25 billion in 2025 alone. In the first 50 days of 2026, owners added another 1 billion miles — averaging more than 20 million miles per day.
This avalanche of real-world, camera-captured footage, much of it on complex city streets, gives Tesla an unmatched training dataset. Every mile feeds its neural networks, accelerating improvement cycles that lidar-dependent rivals simply cannot match at scale.
Tesla owners themselves will tell you the suite gets better with every release, bringing new features and improvements to its self-driving project.
The $460 target implies roughly 15 percent upside from recent trading levels around $400. While regulatory and safety hurdles remain, BofA’s endorsement signals growing institutional conviction that Tesla’s data advantage is not hype; it’s a tangible moat already delivering billions of miles of proof.
SpaceX President Gwynne Shotwell details xAI power pledge at White House event
Tesla Full Self-Driving v14.2.2.5 might be the most confusing release ever
