The Rise of Agentic AI: A Technical Breakdown of CROFT, MCP, and Knowledge-Based Agents
Last Updated on November 25, 2025 by Editorial Team
Author(s): Pelin Ece Burgun
Originally published on Towards AI.
A detailed and developer-friendly breakdown of Agentic AI concepts.
Keeping up with AI news can easily become overwhelming…That’s exactly why I attended AI Agents Pulse Day a few weeks ago. I wanted a clearer sense of where agent architectures are headed and how we can build stable and trustworthy agents. This recap pulls together the core ideas from the event, adding deeper technical context and practical examples for anyone interested in building or experimenting with AI agents.
The article discusses the evolution of agentic AI, emphasizing key frameworks and concepts such as CROFT, which aims to reduce model hallucinations, and MCP, which enhances model interactions with external functions. It also differentiates between few-shot learning and prompting, explains the architecture of the FastMCP framework, and highlights the importance of knowledge bases for dynamic interactions. The author concludes by suggesting that structured, tool-aware agents represent the future of AI development, moving beyond merely larger models.
Read the full blog for free on Medium.
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