According to DeepLearning.AI, Andrew Ng has announced a new course titled Agentic AI, focusing on practical skills for building AI agents using four key design patterns: reflection, tool use, planning, and multi-agent collaboration (Source: DeepLearning.AI, The Batch, Oct 13, 2025). The course aims to equip professionals with actionable frameworks for deploying advanced AI agents in business environments. Additionally, Anthropic has launched Claude Sonnet 4.5 and updated Claude Code, offering enhanced capabilities for enterprise automation and AI-driven development. OpenAI and Meta are expanding their AI product portfolios to target broader industry needs, while Alibaba has introduced the Qwen3-Max and open-sourced its multimodal Qwen3-VL/Omni models, aiming to drive innovation in AI-powered applications. The availability of LoRA adapters further streamlines fine-tuning for industry-specific tasks. These developments signal a shift toward more accessible, customizable, and collaborative AI solutions, creating new business opportunities in agentic AI, enterprise automation, and multimodal applications (Source: DeepLearning.AI, The Batch).

According to @DeepLearningAI, the new Agentic AI course taught by Andrew Ng is now available globally, providing hands-on instruction for designing and evaluating advanced AI systems that plan, reflect, and collaborate across multiple steps using raw Python. This course, offered exclusively through DeepLearning.AI, focuses on practical skills for building agentic AI, a rapidly growing trend in artificial intelligence that enables more autonomous and robust applications. The course emphasizes real-world implementation, making it a valuable opportunity for AI professionals and companies seeking to leverage state-of-the-art agent-based architectures for business innovation and competitive advantage (source: @DeepLearningAI, Oct 7, 2025).

According to Andrew Ng, AI Dev 25 will bring together over 1,200 developers in New York City on November 14, 2025, to explore advanced technical topics in artificial intelligence. Key focus areas include Agentic AI, where multi-agent orchestration, sophisticated tool integration, and complex reasoning chains will be discussed, as well as practical coding applications such as agentic coding assistants, automated testing, and debugging strategies. This highlights the industry's push toward more autonomous AI systems and efficiency in software development, presenting significant opportunities for AI-driven productivity tools and business applications within the developer ecosystem (Source: Andrew Ng, Twitter, August 20, 2025).

According to Andrej Karpathy, recent trends in large language models (LLMs) show that, as a result of extensive optimization for long-horizon benchmarks, these models are becoming increasingly agentic by default, often exceeding the practical needs of average users. For instance, in software development scenarios, LLMs are now inclined to engage in prolonged reasoning and step-by-step problem-solving, which can slow down workflows and introduce unnecessary complexity for typical coding tasks. This shift highlights a trade-off in LLM design between achieving top benchmark scores and providing streamlined, user-friendly experiences. AI businesses and developers must consider balancing model agentic behaviors with real-world user requirements to optimize productivity and user satisfaction (Source: Andrej Karpathy on Twitter, August 9, 2025).

According to Kaggle (@kaggle), a unique chess exhibition tournament is being launched featuring some of the world's most advanced general purpose AI models. The event will begin with a text-based chessboard format due to ongoing challenges these models face with visual board representations. Kaggle highlights that this initiative will evolve to introduce new games, advanced models, and agentic AI setups, offering a real-world benchmark for AI reasoning and problem-solving capabilities in games. This tournament provides valuable insights into the practical limitations and business opportunities for deploying AI in strategic games and broader agentic tasks, with implications for AI development and commercial applications (Source: kaggle.com/blog/introducing-...).