How Gemini 4 Argon Upleveled Agents on Antigravity: Trillion-Edge Graphs and Custom TPU Kernels

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Recently, we introduced Gemini 4 Argon in Google Antigravity , showing how Argon’s 1-million-token context window, tunable reasoning, and native sub-agent orchestration upleveled Teamwork —our structured multi-agent framework—to optimize datacenter memory and rewrite legacy C++ libraries into safe Rust. Today, we are sharing how Google’s Graph Mining and Graph Learning teams used Gemini 4 Argon with Teamwork to solve a different class of internal engineering bottleneck: compressing months of low-level RDMA networking and custom TPU kernel development into hours. In just days of agentic collaboration, a small team of researchers and engineers used Teamwork powered by Gemini 4 Argon to build and deploy two foundational capabilities inside our internal Distributed Graph Flow stack: Planet-Scale Distributed Graph Mining (FarArray) : Compressing an estimated one-year distributed systems roadmap into a 5-hour gated engineering sprint , the team built FarArray , a hardware-accelerated Partitioned Global Address Space (PGAS) over RDMA. …

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