Tesla’s Optimus robot has once again captured attention, but recent reports highlight significant production bottlenecks, specifically centered on the robot’s hands rather than its legs, AI, or sensors. The hands of the Optimus robot face challenges such as low load capacity, a short lifespan for transmission components, and difficulties in integrating precision mechanics, miniature actuators, and AI-driven control systems. This bottleneck underscores a critical challenge in robotic development, emphasizing that human-like dexterity, rather than merely a humanoid shape, is the key to achieving versatile robotic functionality. The current hand design, limited to 11 degrees of freedom, falls short of the human hand’s approximately 25 degrees, restricting the robot’s ability to perform complex tasks effectively. To address these hand-related production issues, Tesla is pursuing a multifaceted approach, beginning with a comprehensive redesign of the hand architecture. By moving actuators to the forearm to mimic human tendon-based muscle control, Tesla aims to reduce hand weight and enhance flexibility, likely adopting a tendon-driven system with lightweight, high-strength cables to distribute mechanical stress evenly. This design could simplify assembly, reduce production costs, and align with Tesla’s biomimetic engineering focus, potentially incorporating modular forearm actuators for easier upgrades and maintenance. Tesla may leverage 3D-printed components for rapid prototyping, flexible joints for improved grip adaptability, and materials like carbon fiber for durability and weight reduction. The redesign is expected to enhance the hand’s ability to handle both delicate and heavy objects, integrating force-feedback sensors for precise tendon control and reducing overheating in compact designs. By lowering wiring complexity, simulating tendon dynamics with computational models, and prioritizing energy efficiency, Tesla could extend operational time while using bioinspired lubricants to minimize friction. Faster hand movements for dynamic tasks, standardized tendon lengths, and self-diagnostic sensors for real-time maintenance alerts are also likely, with testing in controlled factory environments to ensure reliability before full deployment. Additionally, Tesla aims to increase the hand’s degrees of freedom to 22, approaching human capabilities, by designing modular finger joints with miniaturized motors and AI-driven kinematics for optimized movement. Flexible materials, tactile sensors, and hybrid mechanical-soft robotics systems may be tested to balance dexterity and reliability, with rapid prototyping and extensive stress testing to ensure durability. Machine learning could predict joint failures, and standardized components may reduce costs, with Tesla likely patenting this design for a competitive edge. Retaining a tendon-based design path, Tesla is expected to refine tendon materials using high-tensile polymers or synthetic fibers inspired by human muscles, reducing wear on transmission components and enabling replaceable tendon modules for simpler repairs. Adjustable tension systems, real-time wear sensors, and AI-optimized tendon routing could enhance precision, grip strength, and energy efficiency, with biodegradable materials considered for sustainability and automated tensioning systems for consistency, all scalable for cost-effective manufacturing. Tesla is also engaging in extensive collaboration and research to tackle the hand problem. By consulting with hand surgeons, Tesla’s engineers are likely to gain insights into human hand biomechanics, studying cadaveric hands to map tendon and muscle interactions and developing a proprietary biomechanical model.