Qianyi Deng is Co-founder and CEO of Piggy Robotics (YC F25).
More money is flooding into robotics than ever before. One of the most prominent labs building a robot “brain” just raised $600 million at a $5.6 billion valuation, and investors are pouring billions more into the race to put AI into physical machines. It’s tempting to read that as a spending contest and to assume the winning response is to build across the entire stack at once, before someone else does. I think that’s backwards. Raising the most money and building the most valuable thing are two different games, and the teams that win the second one are ruthless about what they refuse to build. The single most valuable strategic decision you can make is deciding what not to build.
I co-founded Piggy Robotics to build foundation models that make robots more capable, so I have had to make this call myself. We started out intending to own the entire stack: the robot’s body, the data to train it, the learning model that powers it and the product on top. For a few months, we built a humanoid robot priced around the cost of an iPhone. The engineering was exciting, and it was genuinely good work. But we realized it wasn’t where our long-term competitive advantage would come from. Every layer we chose to own represented an entire company’s worth of work. Trying to master all of them simultaneously almost guaranteed that none would become truly world-class.
Conversations with customers only reinforced what we were already seeing internally. Customers weren’t asking for another robot; they were asking for embodied AI agents that could solve their problems. That convinced us that while hardware would continue to improve, intelligence was the layer where competitive advantage would compound. So we narrowed, hard. We stopped building hardware and put everything behind the intelligence that runs on it. It was the most decisive, and most clarifying, choice we made. Looking back, it was the moment we stopped trying to build everything—and started building what mattered most.
The goal isn’t to do less but to do one thing at a level no one else can match. Before I commit to a hard problem, I now run three questions:
1. Is this the layer where our advantage compounds? Some parts of a stack get cheaper and more crowded every year; others get more valuable with every deployment, every customer and every new piece of data.
2. Can someone else do this part well enough, soon enough? If a capable supplier, partner or open tool already exists, owning that layer yourself is usually vanity dressed up as ambition. For us, robot hardware, for instance, is getting cheaper and better fast as manufacturing scales, whereas the intelligence that runs it is immature. Buy the commodity and build what’s scarce. Owning a layer that’s already turning into a commodity doesn’t make you formidable, only busy.
3. What does saying yes here cost us everywhere else? Every extra layer you own draws attention away from the one thing that has to be world-class. Teams rarely lose because they placed the wrong single bet. They lose because they placed too many at once and did none of them well enough to matter. A yes to a second priority is almost always a no to the first.
None of this is a guarantee—choosing the right layer is hard, and it takes conviction to commit before the market has confirmed you were right. But breadth is the easy, expensive instinct, and the temptation to sprawl grows with every dollar raised. Discipline is the harder, rarer choice, and it’s the one that separates the teams that compound from the teams that merely expand.
The reflex in a boom is to add because there are so many exciting things to do. The harder decision is to subtract. Before your next planning cycle, don’t only ask what else you could build. Ask what you could stop building, and whether the one thing left standing is genuinely where you can be the best in the world.
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