I noticed one thing in OpenGradient that kept bothering me: the hardest part does not look like model quality, it looks like coordination after the demo ends. The more I looked into OpenGradient, the more I saw that developer adoption only matters when the tooling, verification path, and node behavior stay useful under real workload, not just in a testnet walkthrough. What stood out to me was how much that changes the signal I trust, because marketing can create attention, but production usage has to survive maintenance, latency, and repeated execution. I could be wrong, but OpenGradient feels more dependent on sustainable incentives than on short-term rewards, and that makes the architecture feel more serious than the headline usually suggests. The practical implication is simple: if usage does not keep compounding on its own, the network spends more energy retaining activity than building it. I’m still trying to figure out where the real retention loop starts in OpenGradient. What matters more here: getting developers to try it once, or making it cheap enough for them to keep using it?