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Why Context Engineering is the Key to Successful AI Integration
Context Engineering ist mehr als gutes Prompting: Es ist die Kunst, ein intelligentes, dynamisches Umfeld für KI-Systeme zu gestalten. Dieser Artikel zeigt, warum der Kontext der wahre Erfolgsfaktor für den Einsatz von LLMs ist – und wie Unternehmen davon profitieren können.
Jul 272 min read
Agentic AI in Enterprise Use: Risks You Shouldn’t Underestimate
Agentic AI is seen as the next evolutionary stage of intelligent systems – with the ability to plan, decide, and act autonomously. But amid the hype, many companies overlook that this new autonomy brings new risks. These risks are often less obvious, but they can be critical for business operations.
Jun 282 min read
Agentic AI: What Truly Makes an AI System Agentic?
What distinguishes Agentic AI from automation?
This article highlights the key characteristics of agentic systems – with examples and in-depth analysis.
Jun 103 min read
Agentic AI: Between Conceptual Precision and Hype-Driven Misuse
What distinguishes true Agentic AI from mere automation? An analysis of conceptual confusion, the risks it poses to businesses, and what decision-makers should look out for.
Jun 53 min read
Parameters of Large Language Models (LLMs): Comprehensive Guide to Optimization and Usage
Learn how to optimally utilize the parameters of large language models (LLMs) to enhance efficiency and precision.
Jan 153 min read
Developing Applications with Generative AI: Key Considerations and Decisions
The integration of generative AI language models such as GPT-4 opens up innovative possibilities but also brings complex challenges.
Jan 83 min read
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