Google builds Strike Team to catch Anthropic, even as engineers use Claude Code

Published: 2026-04-21 03:43:02 |

Google DeepMind has quietly formed a “Strike Team” to close the gap with Anthropic in AI coding. The move follows public claims that Claude Code is producing nearly all code at Anthropic, while Google’s own figures suggest AI agents are already writing about 50% of its code. The team is led by Sebastian Borgeaud, previously the head of Gemini model pretraining. Reportedly, Google co-founders Sergey Brin and DeepMind tech lead Koray Kavukcuoglu are also involved, which signals high internal priority. Rather than focusing only on short autocomplete, the Strike Team targets “long-horizon task programming”: models that can understand large codebases, developer intent, and generate complete usable software modules. Google is reportedly training internal, code-specific models that cannot be publicly released due to commercial secrets. A key pressure point is adoption: at least one report says Claude Code has become one of Google engineers’ most used external AI coding tools. When engineers rely on a competitor’s tool to fill gaps, senior leadership is unlikely to ignore it. Related context in the article also notes the Ethereum Foundation forming a “dAI team” to position Ethereum for AI and machine-economy settlement and coordination.

Neutral

This is primarily a Big Tech AI-software competitiveness story, not a direct crypto protocol or regulatory change. For traders, the key linkage is indirect: if Google accelerates AI coding with products like Claude Code, it could influence tech sentiment around AI infrastructure, but it does not clearly change token supply/demand mechanics for ETH. In the short term, markets usually react to “AI arms race” headlines via risk sentiment rather than coin-specific fundamentals. Similar episodes—major model releases or new corporate AI teams—often led to brief, broad tech optimism without sustained crypto price moves unless a concrete crypto integration or policy shift followed. Here, the article’s most concrete crypto element is only the Ethereum Foundation’s dAI positioning, which is narrative-level unless followed by measurable adoption, partnerships, or on-chain activity. Over the long term, if AI tooling adoption grows on Ethereum-related ecosystems (through dAI/settlement/coordination use cases), that could become a gradual bullish tailwind for ETH. However, based on the article alone, there is no confirmed catalyst that immediately affects ETH liquidity, staking flows, or demand. Hence the expected impact on the market is neutral.