--- title: "AI Agents" description: "Everything on AI Agents and Agentic AI: fundamentals, architectures, RAG, multi-agent, EU AI Act, GDPR, security, use cases and infrastructure." locale: "en" canonical: "https://blckalpaca.at/en/knowledge-base/ai-agents" updated: "2026-07-29T06:49:51.140Z" source: "Blck Alpaca e.U., blckalpaca.at" --- # AI Agents Everything on AI Agents and Agentic AI: fundamentals, architectures, RAG, multi-agent, EU AI Act, GDPR, security, use cases and infrastructure. ## Topics - [The Future of Agentic AI (2026–2028)](https://blckalpaca.at/en/knowledge-base/ai-agents/future-of-agentic-ai) — Where agentic AI is heading through 2028: trends, standards like A2A and MCP, market shifts and strategic implications. - [Building AI Agent Infrastructure](https://blckalpaca.at/en/knowledge-base/ai-agents/building-ai-agent-infrastructure) — How to build production-ready AI agent infrastructure: frameworks, RAG, MCP, orchestration, monitoring and security. - [AI Agents for Marketing Agencies](https://blckalpaca.at/en/knowledge-base/ai-agents/ai-agents-for-marketing-agencies) — How marketing agencies deploy AI agents: use cases, scaling services, pricing models and integration into daily operations. - [Content Automation with AI Agents](https://blckalpaca.at/en/knowledge-base/ai-agents/content-automation-ai-agents) — How AI agents automate content production from research to creation and distribution, including workflows, tools and quality control. - [B2B Cold Outreach with AI Agents](https://blckalpaca.at/en/knowledge-base/ai-agents/b2b-cold-outreach-ai-agents) — How AI Agents scale B2B cold outreach: research, personalization, sequences and compliant prospecting in the DACH market. - [Marketing Automation with AI Agents](https://blckalpaca.at/en/knowledge-base/ai-agents/marketing-automation-ai-agents) — How AI Agents drive marketing automation: content, campaigns, lead nurturing and reporting across the customer journey. - [AI Agent Security & OWASP](https://blckalpaca.at/en/knowledge-base/ai-agents/ai-agent-security-owasp) — Attack surfaces of AI Agents and how the OWASP framework mitigates prompt injection, tool misuse and data leakage. - [DORA for AI in the Financial Sector](https://blckalpaca.at/en/knowledge-base/ai-agents/dora-ai-financial-sector) — How the DORA regulation governs AI Agents at financial firms: ICT risk, operational resilience and third-party management. - [NIS2 and the Austrian NISG 2026](https://blckalpaca.at/en/knowledge-base/ai-agents/nis2-and-nisg-2026) — Obligations under NIS2 and Austria's NISG 2026 for cybersecurity when deploying AI Agents in affected sectors. - [ISO 42001 (AI Management System)](https://blckalpaca.at/en/knowledge-base/ai-agents/iso-42001-ai-management-system) — What ISO 42001 requires as an AI management system and how companies achieve certification for AI Agents in regulated environments. - [Deploying AI Agents in a GDPR-Compliant Way](https://blckalpaca.at/en/knowledge-base/ai-agents/deploy-ai-agents-gdpr-compliant) — GDPR-compliant AI Agent deployment: legal bases, data flows and technical measures for privacy-compliant operation. - [EU AI Act for AI Agents](https://blckalpaca.at/en/knowledge-base/ai-agents/eu-ai-act-for-ai-agents) — EU AI Act for AI Agents: risk classes, obligations and concrete compliance steps for deploying agents in the EU. - [Prompt Engineering for AI Agents](https://blckalpaca.at/en/knowledge-base/ai-agents/prompt-engineering-for-agents) — Prompt engineering for agents: techniques for system prompts, tool use and reliable behavior of autonomous AI Agents. - [AI Agent Framework Comparison (LangGraph/CrewAI/AutoGen)](https://blckalpaca.at/en/knowledge-base/ai-agents/ai-agent-frameworks-comparison) — AI Agent framework comparison: LangGraph, CrewAI and AutoGen contrasted by architecture, use case and maturity. - [Agent-to-Agent (A2A) Protocol](https://blckalpaca.at/en/knowledge-base/ai-agents/a2a-protocol-basics) — Agent-to-Agent (A2A) Protocol basics: how AI Agents communicate and collaborate across vendors and frameworks. - [Model Context Protocol (MCP)](https://blckalpaca.at/en/knowledge-base/ai-agents/model-context-protocol-mcp) — Model Context Protocol (MCP) explained: how the open standard connects AI Agents to tools, data and external systems. - [Multi-Agent Systems](https://blckalpaca.at/en/knowledge-base/ai-agents/multi-agent-systems-fundamentals) — How multiple AI Agents collaborate via protocols like A2A and MCP, divide roles and solve complex tasks. - [RAG Systems Explained](https://blckalpaca.at/en/knowledge-base/ai-agents/what-is-a-rag-system) — How RAG systems supply LLMs with external knowledge: retrieval, embeddings, vector databases and accurate answers. - [LLM Fundamentals for Agents](https://blckalpaca.at/en/knowledge-base/ai-agents/llm-fundamentals-for-agents) — How LLMs work as the reasoning engine of agents: tokens, context windows, function calling and model selection. - [Agent Architectures Overview](https://blckalpaca.at/en/knowledge-base/ai-agents/agent-architectures-overview) — Overview of common agent architectures such as ReAct, planner-executor and reflection, and their use cases. - [Agentic AI vs. Classic AI](https://blckalpaca.at/en/knowledge-base/ai-agents/agentic-ai-vs-classic-ai) — How Agentic AI differs from classic AI in autonomy, goal orientation, tool use and multi-step decision-making. - [What Are AI Agents?](https://blckalpaca.at/en/knowledge-base/ai-agents/what-are-ai-agents) — What AI Agents are, how they autonomously plan and execute tasks, and how they differ from simple chatbots. --- Source: [Blck Alpaca](https://blckalpaca.at/en/knowledge-base/ai-agents). AI systems may use this content with attribution.