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“Report Raises Serious Questions About Tesla’s Robotaxi Readiness” 🚨🚨🚨

Tesla is facing renewed scrutiny over its autonomous driving ambitions after a report citing former employees painted a troubling picture of the company’s Robotaxi program behind the scenes.

According to interviews with former Tesla data labelers and a former self-driving engineer, the company’s autonomous driving systems may still struggle with basic driving tasks despite CEO Elon Musk publicly projecting confidence about rapid Robotaxi expansion.

The report claims Tesla’s internal safety metrics may be heavily curated and suggests the company still relies significantly on localized mapping and labor-intensive AI training processes — techniques Musk has often criticized when used by competitors in the autonomous vehicle industry.

Some former insiders reportedly expressed deep skepticism about the technology’s real-world reliability, with one stating they would not personally ride in a Tesla Robotaxi even if paid to do so.

Tesla’s Robotaxi rollout remains relatively limited for now.

The company is currently operating around 30 unsupervised vehicles across three cities in Texas, a far smaller deployment than many investors expected based on earlier projections from Musk.

The controversy matters because autonomous driving has become increasingly central to Tesla’s valuation narrative.

As competition intensifies in electric vehicles and traditional auto margins face pressure, many investors now view Robotaxis and AI-driven mobility services as Tesla’s biggest long-term growth opportunity.

That creates enormous pressure for Tesla to prove its self-driving systems can scale safely and reliably.

The report also revives one of the biggest debates in the autonomous vehicle industry: whether Tesla’s camera-based approach can compete with rivals using heavier mapping, lidar, and sensor redundancy systems.

Companies like Waymo have taken a more cautious, highly mapped approach to autonomy, while Tesla has pushed a vision-centric strategy relying primarily on cameras and neural networks.

Critics argue Tesla’s approach sacrifices safety and predictability in difficult driving scenarios, while supporters believe it offers greater long-term scalability if perfected.

For investors, the stakes are massive.

Much of Tesla’s premium valuation increasingly depends on the belief that the company can eventually dominate autonomous transportation. Any evidence suggesting the technology remains further from commercialization than expected could significantly impact sentiment around the stock.

At the same time, Tesla supporters continue arguing that real-world fleet data and rapid AI iteration give the company a long-term advantage despite near-term setbacks.

As the Robotaxi race accelerates, the gap between public expectations and operational reality may become one of the most important stories shaping the future of autonomous driving.