What is a Agentic AI?
Agentic AI represents a transformative shift in the capabilities of artificial intelligence, moving beyond simple input-output systems to intelligent agents that can independently plan, act, and adapt to achieve specific goals. Unlike traditional AI, which requires human prompts and executes single, isolated tasks, Agentic AI operates with autonomy, meaning it can set objectives, make decisions, and take initiative without continuous human intervention. These systems are designed to understand complex environments, break down goals into actionable steps, and respond dynamically to feedback or changes. For example, an Agentic AI can be tasked with organizing a marketing campaign, and it will not only generate content but also schedule posts, analyze engagement metrics, and adjust its strategy in real time.
Beyond the Chatbot: How Agentic AI Really Works
Weighted Input Processing: In an Agentic AI system like those powered by Gupshup.ai, each virtual agent processes input data from previous layers by assigning significance through weights
Non-Linear Decision Making (Activation Functions: To enable dynamic and human-like responses, this weighted sum is passed through an activation function, introducing essential non-linearity. Common activation functions include:
Skill Guidelines: Instructions tailored for different service scenarios (e.g., sales, support, technical).
Guard-Rails: Boundaries to keep responses appropriate and on-topic.
Engagement Rules: How the AI should interact – friendly, empathetic, formal.
Tool Call Prompting (The “Action” Layer): “This is a key differentiator. When your request requires data from external systems (like your CRM, inventory, or billing system) or needs an action to be performed (like updating your profile or placing an order), the Agentic AI doesn’t give up. Instead, it generates a “tool call prompt,” instructing itself to connect with relevant external APIs and custom functions. This allows the AI to act on your behalf, fetching real-time information or triggering necessary processes.
Advanced topics
Summary: Agentic AI, powered by advanced neural networks, is transforming customer experiences by enabling systems to understand, learn, and respond with human-like intelligence. These AI models are capable of identifying complex patterns in user interactions, allowing them to deliver personalized and context-aware responses across various platforms. With ongoing advancements in deep learning architectures and training techniques, systems like Gupshup.ai are becoming more efficient and effective. To ensure reliability, especially when handling diverse and unpredictable customer queries, techniques such as regularization, dropout, and cross-validation are used to prevent overfitting. Fine-tuning hyperparameters—like the number of layers, neurons, and learning rate—is also essential for optimal performance. Though training such models can be computationally demanding, often requiring GPUs, the results are intelligent, adaptive agents that elevate customer engagement to a new level of speed, personalization, and accuracy.