State Management and Context Windows in Agentic AI
AI agents are powerful because they can recognise, think, adapt, and act in dynamic environments. But to reach its full potential, they need a way to manage state (what’s going on right now) and...
Agentic AI Tutorials
Retrieval-Augmented Generation for Agents
One of the most significant limitations of traditional Large Language Models (LLMs) is that they are trained on static datasets. Their knowledge cuts off at a certain point, and they can hallucinate answers when...
Short-Term vs Long-Term Memory in AI Agents
One of the most powerful abilities of Agentic AI is memory. Unlike traditional AI systems that “forget” after each prompt, agents can remember past interactions, recall knowledge, and adapt their behaviour over time. But...
Reflection Pattern – Self-Reflection and Self-Correction in Agentic AI
One key difference between traditional AI and Agentic AI is the ability to learn from mistakes in real time. While older systems simply output answers, Agentic AI can go a step further: it can...
Prompts, System Instructions, and Policies in Agentic AI
In Agentic AI, agents don’t just generate text — they act, plan, and interact with environments. To make sure they behave in practical, predictable, and safe ways, we need a clear control framework. That...
When to Use an AI Agent and When Not To
Agentic AI is gaining attention because it enables AI systems to perceive, reason, and act rather than merely respond passively. But a common mistake businesses and developers make is assuming that every problem requires...
Capabilities vs Constraints: What Agents Can and Can’t Do
Agentic AI is among the most advanced and intelligent AIs today. Unlike traditional models that respond to queries, AI agents can predict, think, solve, act, and adapt to achieve goals. They can use multiple...
Core Pillars of Agentic AI
Traditional AI systems like chatbots or recommendation engines are robust but often limited — they produce outputs but cannot plan, adapt, or learn continuously. Agentic AI changes this by making AI systems act more...
Single Agent vs Multi-Agent Systems in Agentic AI
Artificial Intelligence is no longer restricted to standalone chatbots or automation tools. With the rise of Agentic AI, AI agents can now work individually as Single-Agent Systems or collaborate in groups as Multi-Agent Systems....
Autonomous vs Assistive Agents in Agentic AI – Key Differences
Artificial Intelligence is constantly moving beyond simple chatbots and predictive models. Today, we talk about AI agents — intelligent systems designed to help humans achieve goals. But not all agents are the same. Some...
