AI

Designing Responsible Artificial Intelligence: Security, Ethics, and Governance in Practice Responsible AI is no longer a theoretical concept — it’s a business necessity. As organizations deploy AI systems at scale, ensuring they are ethical, secure, and trustworthy becomes critical for long-term success. Responsible Artificial Intelligence refers to designing, developing, and deploying AI systems in alignment […]

Here are the key mistakes based on expert source analysis, with practical ways to avoid them. The focus is on the most frequently occurring problems. 1. Poor prompting and overestimating agent capabilities One of the most common mistakes is assuming that an agent will „figure out” tasks without detailed instructions, which leads to errors, hallucinations, […]

Research has demonstrated that Large Language Models encode a specific dimension in their input representation space, directly connected to prompt paraphrasing rather than task complexity. By modifying this dimension through representation engineering, researchers have achieved 20-30% better instruction adherence compared to random alterations, which offers a scientific explanation for the effectiveness of prompt engineering techniques. […]

AI Agents: Transforming Business Process Automation Through Advanced Reasoning Artificial Intelligence agents represent a significant evolution in business process automation, transcending traditional Robotic Process Automation (RPA) capabilities by incorporating sophisticated reasoning, contextual adaptation, and cross-system orchestration. These advanced systems can autonomously navigate complex workflows across enterprise architecture components including Customer Relationship Management platforms, Enterprise Resource […]