One line, one agent: LLM-native language NERD goes agent-first (www.nerd-lang.org)

The NERD project has announced a shift toward an "agent-first" approach, emphasizing a programming language that prioritizes the orchestration of agents within AI workflows. Initially designed as an LLM-native language for machines to write and humans to audit, NERD aims to streamline agent development by focusing on essential capabilities such as HTTP requests, API calls, and basic orchestration logic. This transition reflects a broader trend where organizations increasingly rely on agents for real-world tasks, supported by powerful developer tools and frameworks. This significant pivot signals an effort to create a language tailored specifically for the evolving needs of AI and its integration into various applications. By minimizing complexity and avoiding the baggage of conventional programming languages, NERD aims to provide a lightweight, purpose-built solution for developers working with LLMs. The language aspires to be compiled, deterministic, and auditable, allowing for easy integration into systems without the overhead of traditional runtimes. As this experimental language develops, it promises to play a crucial role in enhancing agent-driven interactions and streamlining the way developers create AI applications.