AI Agents
Everything on AI Agents and Agentic AI: fundamentals, architectures, RAG, multi-agent, EU AI Act, GDPR, security, use cases and infrastructure.
What Are AI Agents?
What AI Agents are, how they autonomously plan and execute tasks, and how they differ from simple chatbots.
Agentic AI vs. Classic AI
How Agentic AI differs from classic AI in autonomy, goal orientation, tool use and multi-step decision-making.
Agent Architectures Overview
Overview of common agent architectures such as ReAct, planner-executor and reflection, and their use cases.
LLM Fundamentals for Agents
How LLMs work as the reasoning engine of agents — tokens, context windows, function calling and model selection.
RAG Systems Explained
How RAG systems supply LLMs with external knowledge — retrieval, embeddings, vector databases and accurate answers.
Multi-Agent Systems
How multiple AI Agents collaborate via protocols like A2A and MCP, divide roles and solve complex tasks.
Model Context Protocol (MCP)
Model Context Protocol (MCP) explained: how the open standard connects AI Agents to tools, data and external systems.
Agent-to-Agent (A2A) Protocol
Agent-to-Agent (A2A) Protocol basics: how AI Agents communicate and collaborate across vendors and frameworks.
AI Agent Framework Comparison (LangGraph/CrewAI/AutoGen)
AI Agent framework comparison: LangGraph, CrewAI and AutoGen contrasted by architecture, use case and maturity.
Prompt Engineering for AI Agents
Prompt engineering for agents: techniques for system prompts, tool use and reliable behavior of autonomous 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.
Deploying AI Agents in a GDPR-Compliant Way
GDPR-compliant AI Agent deployment: legal bases, data flows and technical measures for privacy-compliant operation.
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.
NIS2 and the Austrian NISG 2026
Obligations under NIS2 and Austria's NISG 2026 for cybersecurity when deploying AI Agents in affected sectors.
DORA for AI in the Financial Sector
How the DORA regulation governs AI Agents at financial firms: ICT risk, operational resilience and third-party management.
AI Agent Security & OWASP
Attack surfaces of AI Agents and how the OWASP framework mitigates prompt injection, tool misuse and data leakage.
Marketing Automation with AI Agents
How AI Agents drive marketing automation: content, campaigns, lead nurturing and reporting across the customer journey.
B2B Cold Outreach with AI Agents
How AI Agents scale B2B cold outreach: research, personalization, sequences and compliant prospecting in the DACH market.
Content Automation with AI Agents
How AI agents automate content production from research to creation and distribution, including workflows, tools and quality control.
AI Agents for Marketing Agencies
How marketing agencies deploy AI agents: use cases, scaling services, pricing models and integration into daily operations.
Building AI Agent Infrastructure
How to build production-ready AI agent infrastructure: frameworks, RAG, MCP, orchestration, monitoring and security.
The Future of Agentic AI (2026–2028)
Where agentic AI is heading through 2028: trends, standards like A2A and MCP, market shifts and strategic implications.