From “Waiting for Instructions” to “Autonomous Execution”: May 2026, Autonomous AI Agents and Extreme Multimodality Reshape the World
1. Introduction: The Complete Shift of Paradigms As of late May 2026, the global artificial intelligence (AI) development landscape has reached a historic turning point. The era of the “conversational AI assistant (chatbot)” that has dominated the market is practically…
Corpus2Skill — New Standard of Knowledge Architecture for the LLM Era
Executive Summary The core shift in enterprise knowledge systems is no longer just from “documents” to “LLMs.” It is from retrieving snippets toward structuring, navigating, editing, and exploring knowledge in forms that fit different kinds of work. Standard Retrieval-Augmented Generation, or RAG, remains the…
The End of Hierarchy, the Rise of Intelligence: How “Company Brain” and “AI OS” Are Rewriting the Future of Organization
The evolution of AI is no longer just about boosting individual productivity. We are witnessing a fundamental redesign of the very architecture of the enterprise. Tech leaders and management theorists in Silicon Valley and beyond are actively debating three revolutionary…
The Rise of the Forward Deployed Engineer: Bridging the High-Stakes Chasm Between AI Theory and Execution
I. Introduction: The New Vanguard of the AI Revolution Moving Beyond the Model: The Birth of the FDE The initial gold rush of the generative AI era focused heavily on scale. Tech giants and well-funded startups raced to build models…
Integrated AI After the LLM Boom
Executive summary Detailed research report for article writing Background and context. Neural AI’s achievements remain extraordinary. Frontier models now write and summarize text, generate and debug code, handle multimodal inputs, and in many products invoke external tools, search the web, or…
Andrej Karpathy’s latest concept ‘LLM Wiki’ and the future of enterprise knowledge
Executive summary Andrej Karpathy’s public GitHub Gist, published on April 4, 2026, describes LLM Wiki not as a finished product, but as an “idea file” for agentic knowledge work: instead of re-retrieving raw fragments on every question, an LLM incrementally compiles curated…


























