AI Answers & RAG Glossary: Essential Concepts for Developers and Teams

A system prompt is the hidden instruction that defines an AI’s role, behavior, tone, and constraints before any user interaction begins. It guides how the model interprets input and shapes every response it generates.

Prompt engineering is pivotal across various domains like data science and UX design. Crafting well-defined prompts enhances data quality, reduces bias, and boosts user engagement. Key strategies involve clarity, relevance, and consistency.

User-knowledge ingestion enables AI to improve responsiveness by processing diverse user inputs like text and behavior, thereby personalizing experiences in apps like Netflix and Alexa.

Agentic AI systems can autonomously make decisions and take actions to achieve goals, unlike traditional AI. Key features include autonomy, goal orientation, adaptability, and environment interaction.

Agentic AI, a subset of AI, focuses on autonomous, goal-oriented decision-making using reinforcement learning. It adapts to dynamic environments, offering applications in robotics, finance, and healthcare.

A Multi-source Knowledge Workspace is a platform that aggregates, analyzes, and presents data from various sources in a single interface. It facilitates collaboration, data management, and drives informed decision-making within organizations.

Agentic Workflow Orchestration involves the design, management, and execution of work processes to improve efficiency and productivity. It automates the arrangement and coordination of complex computer systems.