Breaking Down AI Agents: Frameworks, Features, and Future
The idea of systems that can plan, learn and execute various tasks has been a topic of interest for years. Today, it’s becoming a reality.
AI Agents — not just tools but independent systems that can act like active participants in workflows.
The AI agents market is projected to grow from USD 5.1 billion in 2024 to USD 47.1 billion in 2030, with a CAGR of 44.8% during 2024–2030 source
In this article, we will explore:
- The Advanced Technologies Powering AI Agents
- Why AI Agents Are a Game-Changer in Automation and AI
- Understanding the Core Principles of Agent Building
- The List of Popular Agentic Frameworks
By the end of this article, you’ll have a clear understanding of what AI Agents are, why they matter, and what are available frameworks for agents development.
The Advanced Technologies Powering AI Agents
The core of agentic frameworks lies in the power of using large language models (LLMs). With even recent advancements such as OpenAI’s latest o3 model, Google’s Gemini 2.0 or even DeepSeek-V3, LLMs are achieving unprecedented levels of accuracy and contextual understanding.
