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Original rewrites on React, Node.js, TypeScript and AI — practical notes from the same engineering practice behind our operator software. Article bodies are in English.
Tagged: LLM
RAG Explained: How AI Systems Retrieve Fresh Knowledge on Demand
Learn how Retrieval-Augmented Generation works, from chunking and embeddings to vector search, so AI models can answer questions without retraining.
2776 wordsRead articleWhy AI Access, Not Capability, Is Your Real Dependency Risk
This article examines recent export-control incidents with Claude and GPT-5.6 to argue that access to AI models is a volatile variable independent of raw capability.
2598 wordsRead articleAgentic AI Explained: From Language Models to Autonomous Agents
A structured walkthrough of how LLMs evolve into agentic systems through tools, memory, planning, multi-agent architectures, and MCP integration.
4402 wordsRead articleBuilding Multi-Step AI Agent UIs with Next.js and the AI SDK
Learn how to architect a production-ready AI agent interface using typed tools, multi-step loops, and streaming generative UI components in Next.js.
1729 wordsRead articleReAct Explained: How AI Agents Combine Reasoning with Real-World Actions
Learn how the ReAct framework blends reasoning and tool use to power AI agents, and how it differs from Chain-of-Thought, RL, and reasoning models.
1180 wordsRead articleComparing Frontier AI Agents: Astra, Flash, Fable, and Mythos
A breakdown of how the latest GPT, Gemini, and Claude model releases perform on real agentic tasks like coding, browsing, and tool use, not just benchmarks.
2056 wordsRead article
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