## **AI Agents Defined**
Autonomous software entities that perform tasks, make decisions, and collaborate with other agents or humans to achieve business goals, utilizing AI technologies for understanding and adaptation.
* **Key Components**
* **Identity & Goals**: Defines who the agent is and what it aims to achieve.
* **Override Control & Rules**: Safety mechanisms and governance policies.
* **Memory**: Stores past interactions and experiences.
* **Mental Model**: Internal representation of the environment for situational awareness.
* **Knowledge Base**: Repository of facts, data, and learned information.
* **Anticipation**: Predictive capability to prepare for future states.
* **Actions**: Internal operations the agent can execute.
* **Interface**: Means of communicating with users or other systems.
* **Modalities**: Different channels (text, voice, vision) the agent can process or output.
* **Planning**: Strategy formulation to reach goals.
* **Execution Plan**: Step-by-step roadmap for enacting the plan.
* **Tools**: External resources or APIs the agent can leverage.
* **Unique Aspects**
Emphasizes the importance of a **Mental Model** for situational awareness, **Anticipation** for proactive behavior, and a clear distinction between **Actions** (internal operations) and **Tools** (external resources).
* **Holistic Approach**
Unlike traditional models, this framework integrates **safety protocols**, **user expectations**, and **business objectives**, ensuring agents are reliable and aligned with their tasks.
* **Actionable Insights**
1. **Define Clear Identities & Goals**: Establish who the agent is and what success looks like.
2. **Implement Override Mechanisms**: Ensure safety and compliance through control rules.
3. **Leverage Memory & Anticipation**: Use past data and predictions to improve interactions.
4. **Differentiate Actions vs. Tools**: Clarify internal logic versus external capabilities.
5. **Align with Business Objectives**: Integrate safety, user needs, and organizational goals from the start.