The tweet outlines a theoretical AI chip architecture using TSMC N6 nodes and LPDDR6 memory to challenge Nvidia's B200 and GB200 NVL72 systems. By prioritizing link latency and a full mesh interconnect over high-end process nodes like N3, the proposed design claims to achieve 20% better token/watt efficiency and 8x more memory capacity (110 TB vs 13.8 TB) at the rack level. The strategy advocates for avoiding expensive HBM and CoWoS technologies in favor of "Mobile SoC level economics" for agentic workloads.