According to Andrej Karpathy (@karpathy), in his recent appearance on the Dwarkesh Podcast, his analysis of AGI timelines has attracted significant attention. Karpathy emphasizes that while large language models (LLMs) have made remarkable progress, achieving Artificial General Intelligence (AGI) within the next decade is ambitious but realistic, provided the necessary 'grunt work' in integration, real-world interfacing, and safety is addressed (source: x.com/karpathy/status/1882544526033924438). Karpathy critiques the current over-hyping of fully autonomous LLM agents, advocating instead for tools that foster human-AI collaboration and manageable code output. He highlights the limitations of reinforcement learning and proposes alternative agentic interaction paradigms, such as system prompt learning, as more scalable paths to advanced AI (sources: x.com/karpathy/status/1960803117689397543, x.com/karpathy/status/1921368644069765486). On job automation, Karpathy notes that roles like radiologists remain resilient, while others are more susceptible to automation based on task characteristics (source: x.com/karpathy/status/1971220449515516391). His insights provide actionable direction for AI businesses to focus on collaborative agent development, robust safety protocols, and targeted automation solutions.

According to Anthropic (@AnthropicAI), the company has published a detailed guide on its Engineering blog focused on writing effective tools for large language model (LLM) agents. The post emphasizes that the capabilities of AI agents are directly tied to the power and design of the tools available to them. Anthropic provides actionable tips for developers, such as structuring APIs for clarity, handling agent errors gracefully, and designing interfaces that maximize agent autonomy and reliability. These guidelines aim to help AI developers build more robust, business-ready LLM agent solutions, ultimately enabling more advanced enterprise automation and smarter AI-driven workflows (Source: Anthropic Engineering Blog, 2025).