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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.
Tesla has reached a notable benchmark in its autonomous driving program after its Robotaxi fleet surpassed one million miles of unsupervised operation. The company made the announcement during its Cybercab event in Austin on September 3.
Tesla Vice President of AI Ashok Elluswamy told attendees he was happy to report the fleet had achieved one million miles of unsupervised Robotaxi operation as a testament to safety.
The new total marked a sharp increase from the 380,000 unsupervised miles Tesla disclosed during its second-quarter 2026 earnings update in late July.
In roughly six weeks, the company added about 620,000 miles. That acceleration followed Tesla’s decision to remove in-vehicle safety monitors from most of its operations outside the San Francisco Bay Area.
Credit: Tesla
Tesla first launched Robotaxi service in Austin in June 2025 with safety drivers present. It later began fully unsupervised rides and expanded into Dallas, Houston, Miami, Orlando, and Tampa. The San Francisco Bay Area remains the exception, where a safety monitor still rides in the vehicle under California permitting rules.
The company has not released a city-by-city breakdown of the one million unsupervised miles.
The milestone arrived as Tesla began offering public Cybercab rides in Austin. The purpose-built vehicle has no steering wheel or pedals and is designed only for autonomous ride-hailing. Production versions joined the existing fleet of modified Tesla vehicles already operating in the service.
Tesla’s unsupervised mileage is growing at a double-digit weekly rate according to earlier company comments, yet its fleet size remains modest compared with established competitors. Waymo has accumulated more than 200 million fully autonomous rider-only miles. Tesla has described its own unsupervised operations as having recorded zero notable incidents in the period leading up to the July update.
The one-million-mile figure reflects Tesla’s shift from supervised testing to broader driverless service in multiple states. It also highlights the company’s strategy of using both existing Model Y vehicles and the new Cybercab to scale its network.
Credit: Tesla
Whether the rapid recent growth continues will depend on further city expansions, regulatory approvals, and the performance of the purpose-built Cybercab in everyday paid rides. Tesla has not specified how many of the latest miles involved the new vehicle versus the rest of the fleet.
The announcement underscores Tesla’s progress toward a larger robotaxi network while illustrating the remaining gap in total autonomous experience relative to longer-operating rivals.
Tesla AI lead Ashok Elluswamy said this week that 24-hour Robotaxi service is close. Replying on X to a rider who wanted Cybercab trips all night, he wrote that the capability would arrive “next month or so” once “the next tech to merge on the v15 plan” is ready.
The comment landed on September 4, one day after Tesla opened public Cybercab rides in Austin. It is the clearest near-term timeline yet for overnight unsupervised operation. Tesla’s paid Robotaxi network currently runs from 6 a.m. to 10 p.m. seven days a week across Austin, Dallas, Houston, Miami, Orlando, and Tampa.
next month or so. the next tech to merge on the v15 plan will enable it.
— Ashok Elluswamy (@aelluswamy) September 4, 2026
That 16-hour window is shorter than the 6 a.m. to 2 a.m. schedule the company used for much of the prior year.
Elluswamy did not name the specific feature or say whether the change would apply first to purpose-built Cybercabs, the existing Model Y fleet, or both. He also offered no city-by-city rollout list. The link to Full Self-Driving v15 is nevertheless significant.
Tesla has described v15 as a step-change architecture with seven parallel improvement tracks and roughly ten times more parameters than earlier builds. Early versions of that software already operate on the Robotaxi fleet and contain about 40 percent of the planned gains.
By July 2026, the unsupervised fleet had logged more than 380,000 miles across six cities in two states with what the company called an impeccable safety record and no notable incidents caused by the vehicles themselves. Tesla has repeatedly argued that camera-based end-to-end neural networks, rather than extra sensors, are the core of the solution.
Overnight service would test that claim in lower-light conditions and would also raise vehicle utilization, a key variable for Robotaxi unit economics. The company has already begun using public Superchargers at night and is building dedicated Robotaxi charging sites.
Riders have asked why software must change if the cars already drive in the dark. The practical answer appears to be reliability and scale: Tesla has held back mass expansion until more of the v15 stack is merged, citing the need for higher confidence before putting thousands of unoccupied vehicles on streets around the clock.
If the next module arrives on the timetable Elluswamy sketched, 24-hour service could begin in October 2026 in at least some markets.
That would mark a shift from a daytime-bounded pilot to a service that can run whenever demand exists, including the late-night hours that have so far remained out of reach.
Tesla is beginning to roll out Full Self-Driving Supervised v14.3.9 with a new active safety layer that can take control even when the driver is operating the car manually.
Tesla AI said the software can activate FSD on the driver’s behalf when an imminent collision is detected and Automatic Emergency Braking may not be enough. It may also engage if the system detects heavy distraction or an accidental FSD disengagement.
FSD Supervised v14.3.9 starting to roll out shortly
This release includes a new active safety feature set: FSD Supervised can now activate on your behalf when an imminent collision is detected and Automatic Emergency Braking (AEB) may not be enough.
It may also engage if we…
— Tesla AI (@Tesla_AI) September 4, 2026
The capability is essentially Automatic Collision Evasion. However, unlike conventional AEB, which mainly applies the brakes in a straight line, this feature can use steering, braking, and acceleration together if the car calculates that stopping alone will not prevent impact and a safer path exists. The system may change lanes or move toward a shoulder when conditions allow, then continue driving after the immediate threat is handled rather than simply coming to a stop.
The intervention is meant as a last-resort safety net, not a replacement for attentive driving.
Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident
Tesla’s own description still frames FSD as supervised assistance. Secondary reports on internal release notes say the feature can fire while the car is being driven manually if cabin-camera monitoring suggests the driver is not sufficiently attentive, such as reaching toward the back seat, or if FSD appears to have been turned off unintentionally.
After the emergency maneuver, the car is expected to alert the driver and request a return to manual control.
The safety case is straightforward. Many collisions happen in the last second because a driver is looking away, fumbles a control, or faces an obstacle that braking cannot fully solve. A system that can both recognize that AEB is insufficient and execute a coordinated evasive path can reduce those remaining high-severity events.
Re-engaging after accidental disengagement also addresses a practical failure mode: a small steering nudge that drops FSD at the worst moment. The advantage is a background safety net that uses the same vision stack already running in v14, instead of leaving the car solely to emergency braking once the driver is no longer in command.
The feature still depends on FSD being enabled and, according to reports, an active FSD purchase or subscription. It does not make the vehicle unsupervised. Drivers remain responsible, and Tesla has not published how often the system is expected to intervene or how it will handle false positives.
If the rollout is conservative and the false-alarm rate stays low, the update is a meaningful step: FSD is no longer only a feature the driver turns on. In the rare moments when disaster is already forming, it can step in.
Tesla crosses major Unsupervised Self-Driving milestone
Tesla Robotaxi will be a 24/7 service: here’s when
