The article discusses how agentic AI is reshaping the analytics stack by taking over more execution tasks. It raises the question of which responsibilities should remain with human analysts versus AI agents and explores the importance of this distinction. The piece highlights the evolving role of AI in analytics and the need to define clear boundaries between human and machine work.
By Rashi Desai
Computer scientist Phillip Isola cuts through the hype to explain how AI agents work and what the future might hold for this rapidly advancing technology.
By Adam Zewe | MIT News
What our over-dependence on external consulting teaches us about delegating our minds to machines The post The Big Con of Agentic AI appeared first on Towards Data Science .
By Chinmay Kakatkar
The article reviews the emergence of Agentic AI, covering its evolution, theoretical foundations, working principles, and architectural aspects. It surveys recent scholarly contributions across various domains, highlighting real‑world applications, current research findings, and existing challenges. The review also proposes a framework for stakeholder adoption and outlines future research directions to guide researchers and practitioners.
By AKM Bahalul Haque, Al Amin Islam Ridoy, Mohammad Rayhan, Ivan Porres
The article revisits the author’s 2016 IBM patent on real‑time concert feedback, framing it as an early example of an AI agent that combines multimodal perception, memory‑grounded inference, and human interaction. It reflects on what the patent captured correctly and how a decade of experience informs current agent design practices.
By Mario Noioso
How to set the rules that keep agents effective and out of trouble The post What AI Agents Should Never Do on Their Own appeared first on Towards Data Science .
By Sara Nobrega
The article discusses how the adoption of agentic AI is increasing among EU enterprises and small businesses, based on new analysis. It highlights the current growth trends and identifies areas where deeper use of agentic AI could unlock additional value for these organizations.
The article "How to Work with AI Coding Agents" offers a practical guide aimed at improving code quality rather than merely increasing quantity. It focuses on strategies and best practices for effectively collaborating with AI coding tools to produce better code. The post was originally published on Towards Data Science.
By Sara A. Metwalli
The retrieval layer that helps AI systems navigate, read, and verify information inside even the most complex documents
from custom integrations to a universal standard for tool access The post MCP Explained: How Modern AI Agents Connect to the Real World appeared first on Towards Data Science .
By Maria Mouschoutzi
They aren’t designed, you can’t help perceiving one anyway, and that makes them an engineering problem almost no one is solving. The post Where Does an AI’s Personality Actually Come From?
By Slava Polonski, PhD