I recently spent time digging deep into the humanoid robotics trend while evaluating potential venture ideas. Here are some of my takeaways.
1. Building the Robot Isn’t the Exciting Part
This might sound provocative, but as someone with a hardware background, I don’t believe that building the robot is where the most value lies. Hardware rarely creates defensible moats—only software and networks do.
Some might point to Apple as a counterexample. But Apple’s enduring edge isn’t just hardware—it’s the App Store and the surrounding ecosystem. The ability to close the gap between hardware, OS, and third-party applications is what keeps users locked in.
Tesla never built that layer. Outside of self-driving (which took too long to mature), it didn’t create a platform for others to extend the product. As a result, it feels like competitors are catching up—whether that’s perception or reality.
2. Humanoids Aren’t Lifestyle Products
Unlike Apple, humanoid robots in my opinion won’t be emotional or lifestyle-driven purchases. They’re functional—more like a refrigerator or TV. That means most buyers might make decisions based on price and capability, not brand affinity.
And in function-first markets, margins are razor-thin. It’s a race to the bottom unless you control something more valuable than the hardware itself.
3. Hardware Advantages Don’t Last
Some argue that the real value lies in the neural networks shipped with the robots. But even here, I’m skeptical. As we’ve seen in the LLM space, once one player figures out a compelling method, that knowledge diffuses fast and becomes a commodity.
Today, a robot picking up a vacuum and cleaning a room isn’t even surprising—we’ve seen versions of that in countless demo videos. The “wow” factor is fading quickly. The race is no longer about making robots impressive—it’s about making them useful at scale.
4. China’s Manufacturing Edge—and What It Means for Margins
No one beats China in hardware manufacturing in the short term—not because of cheap labor, but because of deep expertise and massive talent density in areas like injection molding, PCB assembly, and high-speed scaling (famous conclusion by Apple’s CEO Tim Cook https://www.youtube.com/watch?v=L9f5SQQKr5o)
That depth of capability gives China the unique ability to rapidly industrialize entire product categories—faster and cheaper than almost anyone else.
And once China enters a space—as we’ve seen with drones, batteries, and smartphones—margins tend to collapse. If your edge is mostly hardware, you’re on borrowed time.
5. Do We Even Need Legs?
The humanoid form factor has become a kind of religion. But for most practical tasks—sorting parts, moving boxes, stocking shelves—you don’t need legs. Arms, cameras, and good software get you 80% of the way there, at a fraction of the cost.
Most of the advancements in robot neural networks will also benefit cheaper, fixed-base systems just as much as humanoids. The intelligence layer generalizes—what changes is the hardware cost and complexity.
And if that’s true, the total addressable market for full humanoid bodies may be much smaller than people assume.
So What Is Exciting?
Despite all of this, Figure (a major humanoid robotics company in the Bay Area) has done something remarkable—beyond developing impressive hardware and iterating at an incredible pace: they created global excitement.
Now, people are paying attention. Investors, policymakers, and even the broader public are engaged. The narrative has momentum—and that kind of narrative power opens doors: it helps attract funding, talent, partnerships, and deployment opportunities. It builds pressure to make the tech real.
And that leads to the real question: How do we actually put humanoids to work?
The Real Opportunity: The Application and Coordination Layers
Every human entering a new workplace—whether it’s cleaning houses, filling shelves, or assembling parts—goes through onboarding, training, and coordination. There’s no magic. It takes time and human guidance.
If there were an obvious way to remove that coordination layer, most businesses would’ve done it already. But it’s hard.
And that’s where the real opportunity lies:
- First, building the application layer that bridges the gap between humanoids (or other form factors) and actual job execution. Think: not just having a robot capable of reporting stock levels, but making that information actionable and useful across the workflow.
- Second, developing the coordination layer—a system that mimics human workplace hierarchies and gradually reduces the need for human intervention. A single human should be able to supervise and orchestrate hundreds of humanoids, not just one or two.
And critically, this opportunity should be explored as close to the end customer as possible—whether that’s hospitality, healthcare, logistics, or even retail operations in the U.S.; manufacturing and assembly in Europe or China; or aging care in Japan. The real-world context and staying close to the action matters just as much as the product.
Final Thought
If you’re not building the humanoid, you can stay hardware- and form-factor-agnostic—and that’s a powerful position. Focus on putting robots to work, not building the robots themselves. That’s where the moat will be.