AI Agents Demystified: Definitions and Effective Patterns
AI Agents Demystified: Definitions and Effective Patterns
Amid its significant traction, the term “AI Agent” remains somewhat fuzzy, with various interpretations across the tech industry. In this article, Sascha Wolter, Cognigy’s Principal AI/HMI Advocate & Advisor, explains the two types of AI Agents and how to leverage different workflow patterns to meet your enterprise needs.
Content Overview
AI Agents defined
Types of AI Agents:
- AI-Enhanced Workflows: Structured, predefined automation paths that combine Large Language Model (LLM) calls with fixed logic to complete tasks reliably.
- Agentic AI Agents: Dynamic systems capable of making autonomous decisions, adapting to new information, and handling tasks flexibly.
When to use AI Agents
Building blocks for behavior control
Workflow patterns: Customize and combine different patterns to meet your business needs.
- Prompt Chaining
- Evaluator-Optimizer
- Routing and Model Garden
- Orchestration and Concierge