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🦸🏻#2: Your Go-To Vocabulary to Navigate the World of AI Agents and Workflows

Intro

In the first installment of our AI Agents series, we dove deep into the fascinating topic of open-endedness, which is highly relevant to the development of autonomous agents.

(you can read it here for free, and if you want to support Turing Post to make more free articles available for everyone, you can do it here. There are options!)

While we’ve explored that core concept, we haven’t yet tackled the many definitions surrounding AI agents or the misconceptions that come with them. Some call them "bots," others "agents," and there are even more terms in use. Is this okay? Yes and no. To truly make sense of the pivotal changes AI agents are bringing, and to effectively communicate about building systems around and with them, we need to understand why these differences matter. Grouping similar concepts together will help us feel more comfortable with the language, clarify distinctions, and address common misconceptions. Think of this as your go-to vocabulary for navigating the complex world of AI agents and workflows!

In today’s episode:

  • Core Agentic Concepts

  • What are Autonomous, Intelligent, and Rational Agents? Core Types

  • What are Task-Oriented, Smart, Simple Agents, and Bots? Varying Levels of Complexity

  • Agentic Interactions and Interfaces: Human-AI Interaction

  • Embodied and Digital Agents: Operating in Different Environments

  • Advanced and Specialized Agents (it’s mostly still in the future)

  • Roadmap for these advanced agents

  • From Bots to Advanced Agents to Agentic Workflows – the paradigm shift

  • Conclusion

Core Agentic Concepts

The term "AI agent" serves as the central concept – an umbrella term – that unifies the entire discussion of agentic behavior and functionality in AI systems. At the heart of AI agents are the ideas of autonomy, perception, decision-making, and action, which manifest differently depending on the complexity and purpose of the agent. To implement these capabilities effectively, AI agents rely on key modules: profiling, which assigns roles to guide behavior; memory, allowing agents to retain and reuse information; knowledge, enabling them to start with domain-specific expertise; reasoning/planning, to break down tasks and orchestrate steps; and actions, which integrate external tools to achieve their goals.

These components (which we will expand on in the upcoming episodes) form the building blocks for creating capable and intelligent autonomous agents. This leads us to the concepts of Autonomous, Intelligent, and Rational Agents.

The rest of this explanatory article is available exclusively to our Premium users. If you're working on, or considering building, an AI agent (or more likely an agentic workflow), it's essential to know the correct terminology →

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