Agents IA
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AI agents and multi-agent systems, explained
The think-act-observe loop, ReAct, tools, memory and reflection; multi-agent patterns (orchestrator-workers), frameworks, evaluation and failure modes.
12 min read -
MCP: giving tools to AI agents
The Model Context Protocol standardizes connecting LLMs to tools and data: architecture, primitives, transports, security, and the 2026 ecosystem.
9 min read -
Agentic RAG and GraphRAG: reasoning and structure above retrieval
Beyond naive RAG: agentic loops (Self-RAG, CRAG, routing, multi-hop), hybrid + rerank, and GraphRAG (entities, Leiden, summaries). Costs and RAGAS.
12 min read -
AI agent security: prompt injection and guardrails
Why AI agents create new risk: direct/indirect prompt injection, the lethal trifecta, the OWASP LLM Top 10, and defense in depth.
13 min read