According to @AnthropicAI, the Anthropic Engineering Blog has published Demystifying evals for AI agents, outlining evaluation strategies that have worked across real-world deployments; source: Anthropic (@AnthropicAI), https://www.anthropic.com/engineering/demystifying-evals-for-ai-agents, Jan 9, 2026. The announcement notes that the same capabilities that make agents useful also make them harder to evaluate, underscoring a focus on rigorous, deployment-tested benchmarks; source: Anthropic (@AnthropicAI), https://www.anthropic.com/engineering/demystifying-evals-for-ai-agents, Jan 9, 2026. For traders, the post signals continued emphasis on measurable reliability from a leading AI lab, with no mention of cryptocurrencies, tokens, or partnerships in the announcement; source: Anthropic (@AnthropicAI), https://twitter.com/AnthropicAI/status/2009696515061911674, Jan 9, 2026.

According to @AnthropicAI, a new Engineering Blog post explains that beyond prompt engineering, developers need context engineering to get the most out of AI agents, and the post details how it works, directing readers to the official write-up for methodology and implementation guidance, source: @AnthropicAI. According to @AnthropicAI, the announcement is positioned for developers building AI agents and points to a structured approach to context setup that can inform production workflows in domains such as data retrieval, tool use, and decision pipelines, which is directly relevant to builders of automated research and execution systems in crypto and finance, source: @AnthropicAI.

According to @AnthropicAI, Anthropic published a new Engineering blog post on September 11, 2025 that shares developer tips for writing effective tools for LLM agents and emphasizes that agents are only as powerful as the tools provided, source: @AnthropicAI. The announcement directs readers to the post at anthropic.com/engineering/writing-tools-for-agents for full guidance, source: @AnthropicAI. The source does not mention cryptocurrencies, tokens, or market data, and it provides no trading metrics or price-sensitive information, source: @AnthropicAI.