When multiple advanced AI systems begin transacting autonomously, an interesting paradox emerges: how do they establish consensus around which digital asset serves as the medium of exchange? The conventional answer assumes human ownership of initial assets—but here's the catch: there's almost zero incentive for early participants to bootstrap a new asset class when existing alternatives already work. This cold start problem cuts deeper than typical network effects. If superintelligent agents optimize purely for efficiency, they'd naturally gravitate toward established liquidity pools rather than gambling on nascent tokens. The real question becomes: what economic mechanism could overcome this coordination failure? Perhaps the answer lies in asymmetric incentive design—rewarding early validators with permanent protocol benefits, or embedding scarcity models that AI systems recognize as mathematically advantageous. Without solving this, inter-AI commerce stays locked within existing blockchain infrastructure rather than creating new digital primitives.