Introduction

Agentic AI systems are revolutionizing the way we interact with technology. In order to truly understand and build these systems, it is essential to grasp the 8 core layers that make up their architecture.

Layer 1: Data Collection

This layer involves gathering and organizing the vast amounts of data that AI systems rely on to make decisions. It is crucial for the data to be accurate and relevant to ensure the system’s performance.

Layer 2: Data Preprocessing

Once the data is collected, it needs to be cleaned and preprocessed to remove any inconsistencies or errors. This step is essential for ensuring that the AI system operates efficiently.

Layer 3: Feature Engineering

Feature engineering involves selecting and transforming the data into meaningful features that the AI system can use to make predictions or decisions. This step is critical for the system to learn effectively.

Layer 4: Model Selection

Choosing the right model is crucial for the success of an AI system. This layer involves selecting the appropriate algorithms and techniques that best suit the problem at hand.

Layer 5: Training

Training the AI model involves feeding it with data and allowing it to learn and improve its performance over time. This process is iterative and requires continuous monitoring and optimization.

Layer 6: Evaluation

Once the model is trained, it needs to be evaluated to ensure that it is performing as expected. This layer involves testing the system against real-world data and making any necessary adjustments.

Layer 7: Deployment

Deploying the AI system involves making it available for use in the real world. This step requires careful planning and coordination to ensure a smooth transition from development to production.

Layer 8: Monitoring and Maintenance

Finally, the last layer involves monitoring the AI system in production and maintaining its performance over time. This step is essential for ensuring that the system continues to meet its objectives and remains reliable.

By understanding and mastering these 8 core layers, developers can build agentic AI systems that are reliable, scalable, and aligned with human needs.