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# Types of AI Agents: Definitions, Roles, and Examples

**[databricks](https://daily.dev/sources/databricks)** · 13 min read · 1 upvotes · 0 comments

## Summary

AI agents are evolving from simple automation to systems that observe, decide, and act across real workflows. This guide presents a stable framework for understanding five core agent types based on decision behavior: simple reflex agents (condition-action rules), model-based reflex agents (maintain internal state), goal-based agents (plan toward outcomes), utility-based agents (optimize trade-offs), and learning agents (adapt from feedback). The framework helps teams choose appropriate agent designs by matching problem characteristics with agent capabilities, avoiding overengineering, and balancing trade-offs between predictability, adaptability, and operational complexity. Most production agents are hybrids combining multiple approaches for reliability and responsiveness.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.databricks.com/blog/types-ai-agents-definitions-roles-and-examples>

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