Tesla's push to scale up Optimus humanoid robot production is running into an unexpected obstacle: the very workers tasked with training the robots are resisting because they know these machines are meant to replace them. According to reporting from The Information, factory workers in Texas and California who wore special motion-recording suits to teach Optimus how to perform manual tasks complained about the arrangement, prompting Tesla to move the training work to dedicated teams and newly established "training hubs".

The resistance highlights a fundamental tension in robotics development that goes beyond engineering challenges. Tesla has been relying on imitation learning, a technique where human workers wear motion-capture suits that record their physical movements while performing factory tasks. This data then trains the Optimus robots to replicate those same motions. But when workers realized the end goal was their own displacement, the human data pipeline that Tesla depends on began to crack.

Why Is Tesla Struggling to Scale Optimus Production?

Tesla's challenges extend far beyond worker morale. The company has encountered significant manufacturing hurdles that are slowing its path to mass production. Tesla's Fremont factory in California stopped making the Model S sedan and Model X SUV as of May 2026, with the company redirecting both line workers and engineers to focus entirely on Optimus development.

Despite this pivot, production remains constrained. The newest version, called Optimus V3, has proven difficult to manufacture at scale. Tesla has reportedly scaled up production to hundreds of robots per week, but the company is targeting production numbers surpassing 1,000 robots per week by the end of 2026. Reaching that goal requires solving multiple technical problems simultaneously.

One major bottleneck involves the robot's hands. Optimus hands and forearms contain more than 100 small components such as screws, and human workers must manually assemble them because the precision required exceeds current automation capabilities. Additionally, the touch sensors in the robot's hands have proven unreliable enough that Tesla developed a replaceable glove-like sensor layer that can be swapped without replacing the entire robot hand. Newly produced robots also require immediate fixes once they come off the production line, adding to manufacturing overhead.

What Technical and Supply Chain Obstacles Stand in Tesla's Way?

Beyond manufacturing complexity, Tesla faces supply chain vulnerabilities that mirror broader challenges across the robotics industry. The company continues to rely on Chinese suppliers for robot components, a dependency that persists even as the Trump administration pushes to boost domestic production. In July, the Federal Communications Commission (FCC) banned new foreign-made robots, including humanoid robots, four-legged robot dogs, and robot vacuum cleaners, creating regulatory pressure that could complicate Tesla's sourcing strategy.

Tesla also faces a critical software limitation. Optimus still requires programming in carefully controlled environments, and its artificial intelligence (AI) is reportedly insufficient for general-purpose uses. This means the robot cannot yet handle the wide variety of tasks that Tesla's long-term vision requires. The company's ability to move beyond carefully controlled, programmed tasks depends on resolving the training-data bottleneck and the worker resistance it has surfaced.

How to Understand the Competitive Pressure Tesla Faces

• Boston Dynamics and Hyundai: Hyundai plans to deploy up to 25,000 Atlas humanoid robots developed by Boston Dynamics over the next several years, representing a massive competitive threat to Tesla's market position.
• Toyota's Investment Strategy: Toyota plans to invest billions of dollars in upgrading factories with robots, including humanoid models, signaling that major automakers are betting heavily on humanoid automation.
• Agility Robotics' Head Start: Agility Robotics, based in Oregon, is among the furthest along in commercial deployment, having first put humanoid robots to work at an Atlanta-area warehouse owned by GXO Logistics in 2024.

The competitive landscape adds urgency to Tesla's timeline. While Tesla CEO Elon Musk has described Optimus as potentially "the biggest product ever" during the company's second-quarter 2026 earnings call, he also acknowledged that making an autonomous humanoid robot capable of handling many different tasks is "one of the hardest things to solve". The gap between Musk's ambitions and the technical reality is widening as competitors move faster toward commercial deployment.

The broader business case for humanoid robots still has to be proven through more sustained and cost-effective deployments, and through demonstrating that such robots can work safely around humans. For Tesla, the question is whether it can resolve the training-data bottleneck and worker resistance while simultaneously scaling manufacturing and improving AI capabilities. If the company cannot move past carefully controlled, programmed tasks, Optimus may struggle to justify its position as Tesla's future.